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121 Commits

Author SHA1 Message Date
yexiaozhou
c61dfb60e8 (layout optimizer) update README.md 2026-04-13 10:25:51 +08:00
yexiaozhou
cf0cbb990d Merge branch 'dev' into feat/3d_layout_and_visualize 2026-04-10 16:16:22 +08:00
yexiaozhou
99dc821a01 refactor(layout_optimizer): DE optimizer — discrete angles, strategy fixes, decoupled mutation, API exposure
- Extract _compute_mutant helper with circular angle diff (fixes 0/2π boundary bug)
- Fix currenttobest1bin (remove non-standard noise term), add rand1bin strategy
- Decoupled mutation: independent F ranges for position vs theta
- Configurable crossover mode: per-device (default) or per-dimension
- Discrete angle snapping in normal 3N DE (joint mode, replaces hybrid as default)
- Stop auto-injecting prefer_orientation_mode into DE
- Expose DE hyperparameters (mutation, theta_mutation, recombination, strategy, angle_mode) via API
2026-04-10 14:41:13 +08:00
Xuwznln
58997f0654 fix create_resource_with_slot 2026-04-09 17:34:25 +08:00
Xuwznln
fbfc3e30fb update unilabos_formulation & batch-submit-exp 2026-04-09 16:40:31 +08:00
Xuwznln
1d1c1367df scale multi exec thread up to 48 2026-04-09 14:15:38 +08:00
yexiaozhou
a7a6d77d7a fix(layout_optimizer): apply code review follow-ups 2026-04-03 01:42:22 +08:00
yexiaozhou
00bdf9b822 feat(layout_optimizer): add angle-first hybrid discrete-theta mode 2026-04-03 01:09:00 +08:00
yexiaozhou
306b787aa7 fix(layout_optimizer): update arm_slider reach value and improve scene poll version handling 2026-04-03 00:43:40 +08:00
Xuwznln
c91b600e90 update handle creation api 2026-04-02 22:53:31 +08:00
yexiaozhou
5b3f317867 Merge branch 'rescue-layout-opt-detached' into feat/3d_layout_and_visualize 2026-04-02 16:32:27 +08:00
Xuwznln
49b3c850f9 fit cocurrent gap 2026-04-02 16:01:23 +08:00
yexiaozhou
b0e98ccf2b docs(layout_optimizer): deprecate align_weight in demo_agent.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-02 13:52:18 +08:00
yexiaozhou
b04dc8dd4a feat(layout_optimizer): default cardinal snap and alignment to off
align_weight defaults to 0 (was DEFAULT_WEIGHT_ANGLE=60).
snap_theta_safe is opt-in via snap_cardinal=True (was always-on).
Both remain available when explicitly requested.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-02 13:48:34 +08:00
yexiaozhou
f4c0e40a25 feat(layout_optimizer): crossing penalty weighted by intersection length
Replace _line_of_sight_penalty (flat per-blocker) with _crossing_penalty
(DEFAULT_WEIGHT_DISTANCE * crossing_length). Uses opening→arm-OBB
endpoints. Applied regardless of reachability pass/fail.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-02 13:33:38 +08:00
yexiaozhou
569ac4a931 feat(layout_optimizer): add segment_obb_intersection_length (Cyrus-Beck clipping)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-02 13:24:45 +08:00
yexiaozhou
31e79e9aff chore(DE): add debug mode and detailed log regarding cost changes 2026-04-02 12:52:44 +08:00
yexiaozhou
6e1b26a754 fix(server): update path configuration for asset directories 2026-04-01 22:07:44 +08:00
Xuwznln
25c94af755 add running status debounce 2026-04-01 16:01:22 +08:00
yexiaozhou
9ef24b7768 feat(layout_optimizer): DE optimizer V2 — custom loop, graduated hard constraints, broad phase
Replace scipy differential_evolution with custom DE loop for per-device
crossover, circular θ wrapping, and configurable mutation strategy
(currenttobest1bin default, best1bin as turbo mode).

Key improvements:
- Graduate ALL hard constraints during DE (proportional penalty instead of
  flat inf), giving DE smooth gradient for reachability, min_spacing, etc.
  Binary inf preserved for final pass/fail reporting.
- 2-axis sweep-and-prune AABB broad phase for collision pair pruning
- Multi-seed injection from multiple seeder presets + Gaussian variants
- snap_theta_safe: collision-check after angle snapping, revert on violation
- Weight normalization (100 distance / 60 angle / 5× hard multiplier)
- Constraint priority field (critical/high/normal/low → weight multiplier)
  with LLM intent interpreter setting priority per constraint type
- Final success field now checks user hard constraints in binary mode
- arm_slider added to mock checker reach table (1.07m)

Tests: 202 passed, 24 new tests added (optimizer 7, constraints 6, broad_phase 11)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-01 00:32:34 +08:00
Xuwznln
861a012747 allow non @topic_config support 2026-03-31 13:15:06 +08:00
yexiaozhou
64eeed56a1 feat: add layout_optimizer package for automatic layout of devices
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-31 09:30:40 +08:00
yexiaozhou
3f75ca4ea3 feat: add generated asset_models registry 2026-03-31 09:30:40 +08:00
Xuwznln
ee63e95f50 update skill 2026-03-25 23:20:13 +08:00
Xuwznln
dbf5df6e4d add placeholder keys 2026-03-25 12:11:10 +08:00
Xuwznln
f10c0343ce add placeholder keys 2026-03-25 11:56:40 +08:00
Xuwznln
8b6553bdd9 always free 2026-03-25 11:24:19 +08:00
Xuwznln
e7a4afd6b5 提交实验技能 2026-03-25 00:42:28 +08:00
Xuwznln
f18f6d82fc disable samples 2026-03-24 23:45:50 +08:00
Xuwznln
b7c726635c correct sample demo ret value 2026-03-24 23:24:12 +08:00
Xuwznln
c809912fd3 新增试剂reagent 2026-03-24 23:22:45 +08:00
Xuwznln
d956b27e9f update registry 2026-03-24 23:10:57 +08:00
Xuwznln
ff1e21fcd8 新增manual_confirm 2026-03-24 23:04:00 +08:00
Xuwznln
b9d9666003 add workstation creation skill 2026-03-24 23:03:49 +08:00
Junhan Chang
d776550a4b add virtual_sample_demo 样品追踪测试设备 2026-03-23 16:43:20 +08:00
Xuwznln
3d8123849a add external devices param
fix registry upload missing type
2026-03-23 15:01:16 +08:00
Xuwznln
d2f204c5b0 bump to 0.10.19 2026-03-22 04:17:21 +08:00
Xuwznln
d8922884b1 fast registry load 2026-03-22 04:14:47 +08:00
Xuwznln
427afe83d4 minor fix on skill & registry 2026-03-22 03:36:28 +08:00
Xuwznln
23c2e3b2f7 stripe ros2 schema desc
add create-device-skill
2026-03-22 03:21:13 +08:00
Xuwznln
59c26265e9 new registry system backwards to yaml 2026-03-22 02:19:54 +08:00
Xuwznln
4c2adea55a remove not exist resource 2026-03-21 23:35:51 +08:00
Xuwznln
0f6264503a new registry sys
exp. support with add device
2026-03-21 19:26:24 +08:00
Junhan Chang
2c554182d3 add ai conventions 2026-03-19 14:14:40 +08:00
Xuwznln
6d319d91ff correct raise create resource error 2026-03-10 16:26:37 +08:00
Xuwznln
3155b2f97e ret info fix revert 2026-03-10 16:04:27 +08:00
Xuwznln
e5e30a1c7d ret info fix 2026-03-10 16:00:24 +08:00
Xuwznln
4e82f62327 fix prcxi check 2026-03-10 15:57:27 +08:00
Xuwznln
95d3456214 add create_resource schema 2026-03-10 15:27:39 +08:00
Xuwznln
38bf95b13c re signal host ready event 2026-03-10 14:13:06 +08:00
Xuwznln
f2c0bec02c add websocket connection timeout and improve reconnection logic
add open_timeout parameter to websocket connection
add TimeoutError and InvalidStatus exception handling
implement exponential backoff for reconnection attempts
simplify reconnection logic flow
2026-03-07 04:40:56 +08:00
Xuwznln
e0394bf414 Merge remote-tracking branch 'origin/dev' into dev 2026-03-04 19:18:55 +08:00
Xuwznln
975a56415a import gzip 2026-03-04 19:18:36 +08:00
Xuwznln
cadbe87e3f add gzip 2026-03-04 19:18:19 +08:00
Xuwznln
b993c1f590 add gzip 2026-03-04 19:18:09 +08:00
Xuwznln
e0fae94c10 change pose extra to any 2026-03-04 19:06:58 +08:00
Xuwznln
b5cd181ac1 add isFlapY 2026-03-04 18:59:45 +08:00
Xuwznln
5c047beb83 support container as example
add z index

(cherry picked from commit 145fcaae65)
2026-03-03 18:04:13 +08:00
Xuwznln
b40c087143 fix container volume 2026-03-03 17:13:32 +08:00
Xuwznln
7f1cc3b2a5 update materials 2026-03-03 11:43:52 +08:00
Xuwznln
3f160c2049 更新prcxi deck & 新增 unilabos_resource_slot 2026-03-03 11:40:23 +08:00
Xuwznln
a54e7c0f23 new workflow & prcxi slot removal 2026-03-02 18:29:25 +08:00
Xuwznln
e5015cd5e0 fix size change 2026-03-02 15:52:44 +08:00
Xuwznln
514373c164 v0.10.18
(cherry picked from commit 06b6f0d804)
2026-03-02 02:30:10 +08:00
Xuwznln
fcea02585a no opcua installation on macos 2026-02-28 09:41:37 +08:00
Xuwznln
07cf690897 fix possible crash 2026-02-12 01:46:26 +08:00
Xuwznln
cfea27460a fix deck & host_node 2026-02-12 01:46:24 +08:00
Xuwznln
b7d3e980a9 set liquid with tube 2026-02-12 01:46:23 +08:00
Xuwznln
f9ed6cb3fb add test_resource_schema 2026-02-11 14:02:21 +08:00
Xuwznln
699a0b3ce7 fix test resource schema 2026-02-10 23:08:29 +08:00
Xuwznln
cf3a20ae79 registry update & workflow update 2026-02-10 22:46:07 +08:00
Xuwznln
cdf0652020 add test mode 2026-02-10 15:18:41 +08:00
Xuwznln
60073ff139 support description & tags upload 2026-02-10 14:38:55 +08:00
Xuwznln
a9053b822f fix config load 2026-02-10 13:06:05 +08:00
Xuwznln
d238c2ab8b fix log 2026-02-10 13:04:33 +08:00
Xuwznln
9a7d5c7c82 add registry name & add always free 2026-02-07 02:11:43 +08:00
Xuwznln
4f7d431c0b correct config organic synthesis 2026-02-06 12:04:19 +08:00
Xuwznln
341a1b537c Adapt to new scheduler, sampels, and edge upload format (#230)
* add sample_material

* adapt to new samples sys

* fix pump transfer. fix resource update when protocol & ros callback

* Adapt to new scheduler.
2026-02-06 00:49:53 +08:00
Xuwznln
957fb41a6f Feat/samples (#229)
* add sample_material

* adapt to new samples sys
2026-02-05 00:42:12 +08:00
Xuwznln
26271bcab8 adapt to new samples sys 2026-02-04 18:49:08 +08:00
Xuwznln
84a8223173 adapt to new edge format 2026-02-03 23:22:38 +08:00
Xuwznln
e8d1263488 workflow upload & prcxi transfer liquid 2026-02-03 18:10:32 +08:00
Xuwznln
380b39100d lh liquid 2026-02-03 15:15:57 +08:00
Xuwznln
56eb7e2ab4 speed up registry load 2026-02-02 20:01:04 +08:00
Xuwznln
23ce145f74 workflow upload & set liquid fix & add set liquid with plate 2026-02-02 18:23:33 +08:00
Xuwznln
b0da149252 fix upload workflow json 2026-02-02 17:19:07 +08:00
Xuwznln
07c9e6f0fe save class name when deserialize & protocol execute test 2026-02-02 16:05:17 +08:00
Xuwznln
ccec6b9d77 Support root node change pos 2026-02-02 12:03:19 +08:00
hanhua@dp.tech
dadfdf3d8d add unilabos_class 2026-01-30 18:07:53 +08:00
Xuwznln
400bb073d4 gather query 2026-01-28 13:23:25 +08:00
Xuwznln
3f63c36505 transfer liquid handles 2026-01-28 11:45:45 +08:00
Xuwznln
0ae94f7f3c add msg goal 2026-01-28 09:21:43 +08:00
Xuwznln
7eacae6442 Fix OT2 & ReAdd Virtual Devices 2026-01-28 01:05:32 +08:00
Xuwznln
f7d2cb4b9e CI Check use production mode 2026-01-27 19:59:06 +08:00
Xuwznln
bf980d7248 v0.10.17
(cherry picked from commit 176de521b4)
2026-01-27 19:41:49 +08:00
Xuwznln
27c0544bfc Fix Build 13 2026-01-27 19:36:42 +08:00
Xuwznln
d48e77c9ae Fix Build 12 2026-01-27 19:16:21 +08:00
Xuwznln
e70a5bea66 Fix Build 11 2026-01-27 19:09:39 +08:00
Xuwznln
467d75dc03 Fix Build 10 2026-01-27 17:41:06 +08:00
Xuwznln
9feeb0c430 Fix Build 9 2026-01-27 15:51:40 +08:00
Xuwznln
b2f26ffb28 Fix Build 8 2026-01-27 15:39:15 +08:00
dependabot[bot]
4b0d1553e9 ci(deps): bump actions/checkout from 4 to 6 (#223)
Bumps [actions/checkout](https://github.com/actions/checkout) from 4 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-01-27 15:30:47 +08:00
dependabot[bot]
67ddee2ab2 ci(deps): bump actions/upload-pages-artifact from 3 to 4 (#225)
Bumps [actions/upload-pages-artifact](https://github.com/actions/upload-pages-artifact) from 3 to 4.
- [Release notes](https://github.com/actions/upload-pages-artifact/releases)
- [Commits](https://github.com/actions/upload-pages-artifact/compare/v3...v4)

---
updated-dependencies:
- dependency-name: actions/upload-pages-artifact
  dependency-version: '4'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-01-27 15:30:38 +08:00
dependabot[bot]
1bcdad9448 ci(deps): bump actions/upload-artifact from 4 to 6 (#224)
Bumps [actions/upload-artifact](https://github.com/actions/upload-artifact) from 4 to 6.
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](https://github.com/actions/upload-artifact/compare/v4...v6)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-01-27 15:30:31 +08:00
dependabot[bot]
039c96fe01 ci(deps): bump actions/configure-pages from 4 to 5 (#222)
Bumps [actions/configure-pages](https://github.com/actions/configure-pages) from 4 to 5.
- [Release notes](https://github.com/actions/configure-pages/releases)
- [Commits](https://github.com/actions/configure-pages/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/configure-pages
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-01-27 15:30:22 +08:00
Xuwznln
e1555d10a0 Fix Build 7 2026-01-27 15:14:31 +08:00
Xuwznln
f2a96b2041 Fix Build 6 2026-01-27 14:36:35 +08:00
Xuwznln
329349639e Fix Build 5 2026-01-27 14:25:34 +08:00
Xuwznln
e4cc111523 Fix Build 4 2026-01-27 14:19:56 +08:00
Xuwznln
d245ceef1b Fix Build 3 2026-01-27 14:15:16 +08:00
Xuwznln
6db7fbd721 Fix Build 2 2026-01-27 13:45:32 +08:00
Xuwznln
ab05b858e1 Fix Build 1 2026-01-27 13:35:35 +08:00
Xuwznln
43e4c71a8e Update to ROS2 Humble 0.7 2026-01-27 13:31:24 +08:00
Xuwznln
2cf58ca452 Upgrade to py 3.11.14; ros 0.7; unilabos 0.10.16 2026-01-26 16:47:54 +08:00
Xuwznln
fd73bb7dcb CI Check Fix 5 2026-01-26 08:47:27 +08:00
Xuwznln
a02cecfd18 CI Check Fix 4 2026-01-26 08:20:17 +08:00
Xuwznln
d6accc3f1c CI Check Fix 3 2026-01-26 08:14:21 +08:00
Xuwznln
39dc443399 CI Check Fix 2 2026-01-26 02:23:40 +08:00
Xuwznln
37b1fca962 CI Check Fix 1 2026-01-26 02:22:21 +08:00
Xuwznln
216f19fb62 Workbench example, adjust log level, and ci check (#220)
* TestLatency Return Value Example & gitignore update

* Adjust log level & Add workbench virtual example & Add not action decorator & Add check_mode &

* Add CI Check
2026-01-26 02:15:13 +08:00
Xuwznln
ec7ca6a1fe Fix/workstation yb revision (#217)
* Revert log change & update registry

* Revert opcua client & move electrolyte node
2026-01-17 16:50:20 +08:00
205 changed files with 60978 additions and 9758 deletions

62
.conda/base/recipe.yaml Normal file
View File

@@ -0,0 +1,62 @@
# unilabos: Production package (depends on unilabos-env + pip unilabos)
# For production deployment
package:
name: unilabos
version: 0.10.19
source:
path: ../../unilabos
target_directory: unilabos
build:
python:
entry_points:
- unilab = unilabos.app.main:main
script:
- set PIP_NO_INDEX=
- if: win
then:
- copy %RECIPE_DIR%\..\..\MANIFEST.in %SRC_DIR%
- copy %RECIPE_DIR%\..\..\setup.cfg %SRC_DIR%
- copy %RECIPE_DIR%\..\..\setup.py %SRC_DIR%
- pip install %SRC_DIR%
- if: unix
then:
- cp $RECIPE_DIR/../../MANIFEST.in $SRC_DIR
- cp $RECIPE_DIR/../../setup.cfg $SRC_DIR
- cp $RECIPE_DIR/../../setup.py $SRC_DIR
- pip install $SRC_DIR
requirements:
host:
- python ==3.11.14
- pip
- setuptools
- zstd
- zstandard
run:
- zstd
- zstandard
- networkx
- typing_extensions
- websockets
- pint
- fastapi
- jinja2
- requests
- uvicorn
- if: not osx
then:
- opcua
- pyserial
- pandas
- pymodbus
- matplotlib
- pylibftdi
- uni-lab::unilabos-env ==0.10.19
about:
repository: https://github.com/deepmodeling/Uni-Lab-OS
license: GPL-3.0-only
description: "UniLabOS - Production package with minimal ROS2 dependencies"

View File

@@ -0,0 +1,39 @@
# unilabos-env: conda environment dependencies (ROS2 + conda packages)
package:
name: unilabos-env
version: 0.10.19
build:
noarch: generic
requirements:
run:
# Python
- zstd
- zstandard
- conda-forge::python ==3.11.14
- conda-forge::opencv
# ROS2 dependencies (from ci-check.yml)
- robostack-staging::ros-humble-ros-core
- robostack-staging::ros-humble-action-msgs
- robostack-staging::ros-humble-std-msgs
- robostack-staging::ros-humble-geometry-msgs
- robostack-staging::ros-humble-control-msgs
- robostack-staging::ros-humble-nav2-msgs
- robostack-staging::ros-humble-cv-bridge
- robostack-staging::ros-humble-vision-opencv
- robostack-staging::ros-humble-tf-transformations
- robostack-staging::ros-humble-moveit-msgs
- robostack-staging::ros-humble-tf2-ros
- robostack-staging::ros-humble-tf2-ros-py
- conda-forge::transforms3d
- conda-forge::uv
# UniLabOS custom messages
- uni-lab::ros-humble-unilabos-msgs
about:
repository: https://github.com/deepmodeling/Uni-Lab-OS
license: GPL-3.0-only
description: "UniLabOS Environment - ROS2 and conda dependencies"

42
.conda/full/recipe.yaml Normal file
View File

@@ -0,0 +1,42 @@
# unilabos-full: Full package with all features
# Depends on unilabos + complete ROS2 desktop + dev tools
package:
name: unilabos-full
version: 0.10.19
build:
noarch: generic
requirements:
run:
# Base unilabos package (includes unilabos-env)
- uni-lab::unilabos ==0.10.19
# Documentation tools
- sphinx
- sphinx_rtd_theme
# Web UI
- gradio
- flask
# Interactive development
- ipython
- jupyter
- jupyros
- colcon-common-extensions
# ROS2 full desktop (includes rviz2, gazebo, etc.)
- robostack-staging::ros-humble-desktop-full
# Navigation and motion control
- ros-humble-navigation2
- ros-humble-ros2-control
- ros-humble-robot-state-publisher
- ros-humble-joint-state-publisher
# MoveIt motion planning
- ros-humble-moveit
- ros-humble-moveit-servo
# Simulation
- ros-humble-simulation
about:
repository: https://github.com/deepmodeling/Uni-Lab-OS
license: GPL-3.0-only
description: "UniLabOS Full - Complete package with ROS2 Desktop, MoveIt, Navigation2, Gazebo, Jupyter"

View File

@@ -1,91 +0,0 @@
package:
name: unilabos
version: 0.10.15
source:
path: ../unilabos
target_directory: unilabos
build:
python:
entry_points:
- unilab = unilabos.app.main:main
script:
- set PIP_NO_INDEX=
- if: win
then:
- copy %RECIPE_DIR%\..\MANIFEST.in %SRC_DIR%
- copy %RECIPE_DIR%\..\setup.cfg %SRC_DIR%
- copy %RECIPE_DIR%\..\setup.py %SRC_DIR%
- call %PYTHON% -m pip install %SRC_DIR%
- if: unix
then:
- cp $RECIPE_DIR/../MANIFEST.in $SRC_DIR
- cp $RECIPE_DIR/../setup.cfg $SRC_DIR
- cp $RECIPE_DIR/../setup.py $SRC_DIR
- $PYTHON -m pip install $SRC_DIR
requirements:
host:
- python ==3.11.11
- pip
- setuptools
- zstd
- zstandard
run:
- conda-forge::python ==3.11.11
- compilers
- cmake
- zstd
- zstandard
- ninja
- if: unix
then:
- make
- sphinx
- sphinx_rtd_theme
- numpy
- scipy
- pandas
- networkx
- matplotlib
- pint
- pyserial
- pyusb
- pylibftdi
- pymodbus
- python-can
- pyvisa
- opencv
- pydantic
- fastapi
- uvicorn
- gradio
- flask
- websockets
- ipython
- jupyter
- jupyros
- colcon-common-extensions
- robostack-staging::ros-humble-desktop-full
- robostack-staging::ros-humble-control-msgs
- robostack-staging::ros-humble-sensor-msgs
- robostack-staging::ros-humble-trajectory-msgs
- ros-humble-navigation2
- ros-humble-ros2-control
- ros-humble-robot-state-publisher
- ros-humble-joint-state-publisher
- ros-humble-rosbridge-server
- ros-humble-cv-bridge
- ros-humble-tf2
- ros-humble-moveit
- ros-humble-moveit-servo
- ros-humble-simulation
- ros-humble-tf-transformations
- transforms3d
- uni-lab::ros-humble-unilabos-msgs
about:
repository: https://github.com/deepmodeling/Uni-Lab-OS
license: GPL-3.0-only
description: "Uni-Lab-OS"

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@@ -1,9 +0,0 @@
@echo off
setlocal enabledelayedexpansion
REM upgrade pip
"%PREFIX%\python.exe" -m pip install --upgrade pip
REM install extra deps
"%PREFIX%\python.exe" -m pip install paho-mqtt opentrons_shared_data
"%PREFIX%\python.exe" -m pip install git+https://github.com/Xuwznln/pylabrobot.git

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@@ -1,9 +0,0 @@
#!/usr/bin/env bash
set -euxo pipefail
# make sure pip is available
"$PREFIX/bin/python" -m pip install --upgrade pip
# install extra deps
"$PREFIX/bin/python" -m pip install paho-mqtt opentrons_shared_data
"$PREFIX/bin/python" -m pip install git+https://github.com/Xuwznln/pylabrobot.git

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@@ -0,0 +1,160 @@
---
name: add-device
description: Guide for adding new devices to Uni-Lab-OS (接入新设备). Uses @device decorator + AST auto-scanning instead of manual YAML. Walks through device category, communication protocol, driver creation with decorators, and graph file setup. Use when the user wants to add/integrate a new device, create a device driver, write a device class, or mentions 接入设备/添加设备/设备驱动/物模型.
---
# 添加新设备到 Uni-Lab-OS
**第一步:** 使用 Read 工具读取 `docs/ai_guides/add_device.md`,获取完整的设备接入指南。
该指南包含设备类别(物模型)列表、通信协议模板、常见错误检查清单等。搜索 `unilabos/devices/` 获取已有设备的实现参考。
---
## 装饰器参考
### @device — 设备类装饰器
```python
from unilabos.registry.decorators import device
# 单设备
@device(
id="my_device.vendor", # 注册表唯一标识(必填)
category=["temperature"], # 分类标签列表(必填)
description="设备描述", # 设备描述
display_name="显示名称", # UI 显示名称(默认用 id
icon="DeviceIcon.webp", # 图标文件名
version="1.0.0", # 版本号
device_type="python", # "python" 或 "ros2"
handles=[...], # 端口列表InputHandle / OutputHandle
model={...}, # 3D 模型配置
hardware_interface=HardwareInterface(...), # 硬件通信接口
)
# 多设备(同一个类注册多个设备 ID各自有不同的 handles 等配置)
@device(
ids=["pump.vendor.model_A", "pump.vendor.model_B"],
id_meta={
"pump.vendor.model_A": {"handles": [...], "description": "型号 A"},
"pump.vendor.model_B": {"handles": [...], "description": "型号 B"},
},
category=["pump_and_valve"],
)
```
### @action — 动作方法装饰器
```python
from unilabos.registry.decorators import action
@action # 无参:注册为 UniLabJsonCommand 动作
@action() # 同上
@action(description="执行操作") # 带描述
@action(
action_type=HeatChill, # 指定 ROS Action 消息类型
goal={"temperature": "temp"}, # Goal 字段映射
feedback={}, # Feedback 字段映射
result={}, # Result 字段映射
handles=[...], # 动作级别端口
goal_default={"temp": 25.0}, # Goal 默认值
placeholder_keys={...}, # 参数占位符
always_free=True, # 不受排队限制
auto_prefix=True, # 强制使用 auto- 前缀
parent=True, # 从父类 MRO 获取参数签名
)
```
**自动识别规则:**
-`@action` 的公开方法 → 注册为动作(方法名即动作名)
- **不带 `@action` 的公开方法** → 自动注册为 `auto-{方法名}` 动作
- `_` 开头的方法 → 不扫描
- `@not_action` 标记的方法 → 排除
### @topic_config — 状态属性配置
```python
from unilabos.registry.decorators import topic_config
@property
@topic_config(
period=5.0, # 发布周期(秒),默认 5.0
print_publish=False, # 是否打印发布日志
qos=10, # QoS 深度,默认 10
name="custom_name", # 自定义发布名称(默认用属性名)
)
def temperature(self) -> float:
return self.data.get("temperature", 0.0)
```
### 辅助装饰器
```python
from unilabos.registry.decorators import not_action, always_free
@not_action # 标记为非动作post_init、辅助方法等
@always_free # 标记为不受排队限制(查询类操作)
```
---
## 设备模板
```python
import logging
from typing import Any, Dict, Optional
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
from unilabos.registry.decorators import device, action, topic_config, not_action
@device(id="my_device", category=["my_category"], description="设备描述")
class MyDevice:
_ros_node: BaseROS2DeviceNode
def __init__(self, device_id: Optional[str] = None, config: Optional[Dict[str, Any]] = None, **kwargs):
self.device_id = device_id or "my_device"
self.config = config or {}
self.logger = logging.getLogger(f"MyDevice.{self.device_id}")
self.data: Dict[str, Any] = {"status": "Idle"}
@not_action
def post_init(self, ros_node: BaseROS2DeviceNode) -> None:
self._ros_node = ros_node
@action
async def initialize(self) -> bool:
self.data["status"] = "Ready"
return True
@action
async def cleanup(self) -> bool:
self.data["status"] = "Offline"
return True
@action(description="执行操作")
def my_action(self, param: float = 0.0, name: str = "") -> Dict[str, Any]:
"""带 @action 装饰器 → 注册为 'my_action' 动作"""
return {"success": True}
def get_info(self) -> Dict[str, Any]:
"""无 @action → 自动注册为 'auto-get_info' 动作"""
return {"device_id": self.device_id}
@property
@topic_config()
def status(self) -> str:
return self.data.get("status", "Idle")
@property
@topic_config(period=2.0)
def temperature(self) -> float:
return self.data.get("temperature", 0.0)
```
### 要点
- `_ros_node: BaseROS2DeviceNode` 类型标注放在类体顶部
- `__init__` 签名固定为 `(self, device_id=None, config=None, **kwargs)`
- `post_init``@not_action` 标记,参数类型标注为 `BaseROS2DeviceNode`
- 运行时状态存储在 `self.data` 字典中
- 设备文件放在 `unilabos/devices/<category>/` 目录下

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---
name: add-resource
description: Guide for adding new resources (materials, bottles, carriers, decks, warehouses) to Uni-Lab-OS (添加新物料/资源). Uses @resource decorator for AST auto-scanning. Covers Bottle, Carrier, Deck, WareHouse definitions. Use when the user wants to add resources, define materials, create a deck layout, add bottles/carriers/plates, or mentions 物料/资源/resource/bottle/carrier/deck/plate/warehouse.
---
# 添加新物料资源
Uni-Lab-OS 的资源体系基于 PyLabRobot通过扩展实现 Bottle、Carrier、WareHouse、Deck 等实验室物料管理。使用 `@resource` 装饰器注册AST 自动扫描生成注册表条目。
---
## 资源类型
| 类型 | 基类 | 用途 | 示例 |
|------|------|------|------|
| **Bottle** | `Well` (PyLabRobot) | 单个容器(瓶、小瓶、烧杯、反应器) | 试剂瓶、粉末瓶 |
| **BottleCarrier** | `ItemizedCarrier` | 多槽位载架(放多个 Bottle | 6 位试剂架、枪头盒 |
| **WareHouse** | `ItemizedCarrier` | 堆栈/仓库(放多个 Carrier | 4x4 堆栈 |
| **Deck** | `Deck` (PyLabRobot) | 工作站台面(放多个 WareHouse | 反应站 Deck |
**层级关系:** `Deck``WareHouse``BottleCarrier``Bottle`
WareHouse 本质上和 Site 是同一概念 — 都是定义一组固定的放置位slot只不过 WareHouse 多嵌套了一层 Deck。两者都需要开发者根据实际物理尺寸自行计算各 slot 的偏移坐标。
---
## @resource 装饰器
```python
from unilabos.registry.decorators import resource
@resource(
id="my_resource_id", # 注册表唯一标识(必填)
category=["bottles"], # 分类标签列表(必填)
description="资源描述",
icon="", # 图标
version="1.0.0",
handles=[...], # 端口列表InputHandle / OutputHandle
model={...}, # 3D 模型配置
class_type="pylabrobot", # "python" / "pylabrobot" / "unilabos"
)
```
---
## 创建规范
### 命名规则
1. **`name` 参数作为前缀**:所有工厂函数必须接受 `name: str` 参数,创建子物料时以 `name` 作为前缀,确保实例名在运行时全局唯一
2. **Bottle 命名约定**:试剂瓶-Bottle烧杯-Beaker烧瓶-Flask小瓶-Vial
3. **函数名 = `@resource(id=...)`**:工厂函数名与注册表 id 保持一致
### 子物料命名示例
```python
# Carrier 内部的 sites 用 name 前缀
for k, v in sites.items():
v.name = f"{name}_{v.name}" # "堆栈1左_A01", "堆栈1左_B02" ...
# Carrier 中放置 Bottle 时用 name 前缀
carrier[0] = My_Reagent_Bottle(f"{name}_flask_1") # "堆栈1左_flask_1"
carrier[i] = My_Solid_Vial(f"{name}_vial_{ordering[i]}") # "堆栈1左_vial_A1"
# create_homogeneous_resources 使用 name_prefix
sites=create_homogeneous_resources(
klass=ResourceHolder,
locations=[...],
name_prefix=name, # 自动生成 "{name}_0", "{name}_1" ...
)
# Deck setup 中用仓库名称作为 name 传入
self.warehouses = {
"堆栈1左": my_warehouse_4x4("堆栈1左"), # WareHouse.name = "堆栈1左"
"试剂堆栈": my_reagent_stack("试剂堆栈"), # WareHouse.name = "试剂堆栈"
}
```
### 其他规范
- **max_volume 单位为 μL**500mL = 500000
- **尺寸单位为 mm**`diameter`, `height`, `size_x/y/z`, `dx/dy/dz`
- **BottleCarrier 必须设置 `num_items_x/y/z`**:用于前端渲染布局
- **Deck 的 `__init__` 必须接受 `setup=False`**:图文件中 `config.setup=true` 触发 `setup()`
- **按项目分组文件**:同一工作站的资源放在 `unilabos/resources/<project>/`
- **`__init__` 必须接受 `serialize()` 输出的所有字段**`serialize()` 输出会作为 `config` 回传到 `__init__`,因此必须通过显式参数或 `**kwargs` 接受,否则反序列化会报错
- **持久化运行时状态用 `serialize_state()`**:通过 `_unilabos_state` 字典存储可变信息(如物料内容、液体量),只存 JSON 可序列化的基本类型
---
## 资源模板
### Bottle
```python
from unilabos.registry.decorators import resource
from unilabos.resources.itemized_carrier import Bottle
@resource(id="My_Reagent_Bottle", category=["bottles"], description="我的试剂瓶")
def My_Reagent_Bottle(
name: str,
diameter: float = 70.0,
height: float = 120.0,
max_volume: float = 500000.0,
barcode: str = None,
) -> Bottle:
return Bottle(
name=name,
diameter=diameter,
height=height,
max_volume=max_volume,
barcode=barcode,
model="My_Reagent_Bottle",
)
```
**Bottle 参数:**
- `name`: 实例名称(运行时唯一,由上层 Carrier 以前缀方式传入)
- `diameter`: 瓶体直径 (mm)
- `height`: 瓶体高度 (mm)
- `max_volume`: 最大容积(**μL**500mL = 500000
- `barcode`: 条形码(可选)
### BottleCarrier
```python
from pylabrobot.resources import ResourceHolder
from pylabrobot.resources.carrier import create_ordered_items_2d
from unilabos.resources.itemized_carrier import BottleCarrier
from unilabos.registry.decorators import resource
@resource(id="My_6SlotCarrier", category=["bottle_carriers"], description="六槽位载架")
def My_6SlotCarrier(name: str) -> BottleCarrier:
sites = create_ordered_items_2d(
klass=ResourceHolder,
num_items_x=3, num_items_y=2,
dx=10.0, dy=10.0, dz=5.0,
item_dx=42.0, item_dy=35.0,
size_x=20.0, size_y=20.0, size_z=50.0,
)
# 子 site 用 name 作为前缀
for k, v in sites.items():
v.name = f"{name}_{v.name}"
carrier = BottleCarrier(
name=name, size_x=146.0, size_y=80.0, size_z=55.0,
sites=sites, model="My_6SlotCarrier",
)
carrier.num_items_x = 3
carrier.num_items_y = 2
carrier.num_items_z = 1
# 放置 Bottle 时用 name 作为前缀
ordering = ["A1", "B1", "A2", "B2", "A3", "B3"]
for i in range(6):
carrier[i] = My_Reagent_Bottle(f"{name}_vial_{ordering[i]}")
return carrier
```
### WareHouse / Deck 放置位
WareHouse 和 Site 本质上是同一概念都是定义一组固定放置位slot根据物理尺寸自行批量计算偏移坐标。WareHouse 只是多嵌套了一层 Deck 而已。推荐开发者直接根据实物测量数据计算各 slot 偏移量。
#### WareHouse使用 warehouse_factory
```python
from unilabos.resources.warehouse import warehouse_factory
from unilabos.registry.decorators import resource
@resource(id="my_warehouse_4x4", category=["warehouse"], description="4x4 堆栈仓库")
def my_warehouse_4x4(name: str) -> "WareHouse":
return warehouse_factory(
name=name,
num_items_x=4, num_items_y=4, num_items_z=1,
dx=10.0, dy=10.0, dz=10.0, # 第一个 slot 的起始偏移
item_dx=147.0, item_dy=106.0, item_dz=130.0, # slot 间距
resource_size_x=127.0, resource_size_y=85.0, resource_size_z=100.0, # slot 尺寸
model="my_warehouse_4x4",
col_offset=0, # 列标签起始偏移0 → A01, 4 → A05
layout="row-major", # "row-major" 行优先 / "col-major" 列优先 / "vertical-col-major" 竖向
)
```
`warehouse_factory` 参数说明:
- `dx/dy/dz`:第一个 slot 相对 WareHouse 原点的偏移mm
- `item_dx/item_dy/item_dz`:相邻 slot 间距mm需根据实际物理间距测量
- `resource_size_x/y/z`:每个 slot 的可放置区域尺寸
- `layout`:影响 slot 标签和坐标映射
- `"row-major"`A01,A02,...,B01,B02,...(行优先,适合横向排列)
- `"col-major"`A01,B01,...,A02,B02,...(列优先)
- `"vertical-col-major"`竖向排列y 坐标反向
#### Deck 组装 WareHouse
Deck 通过 `setup()` 将多个 WareHouse 放置到指定坐标:
```python
from pylabrobot.resources import Deck, Coordinate
from unilabos.registry.decorators import resource
@resource(id="MyStation_Deck", category=["deck"], description="我的工作站 Deck")
class MyStation_Deck(Deck):
def __init__(self, name="MyStation_Deck", size_x=2700.0, size_y=1080.0, size_z=1500.0,
category="deck", setup=False, **kwargs) -> None:
super().__init__(name=name, size_x=size_x, size_y=size_y, size_z=size_z)
if setup:
self.setup()
def setup(self) -> None:
self.warehouses = {
"堆栈1左": my_warehouse_4x4("堆栈1左"),
"堆栈1右": my_warehouse_4x4("堆栈1右"),
}
self.warehouse_locations = {
"堆栈1左": Coordinate(-200.0, 400.0, 0.0), # 自行测量计算
"堆栈1右": Coordinate(2350.0, 400.0, 0.0),
}
for wh_name, wh in self.warehouses.items():
self.assign_child_resource(wh, location=self.warehouse_locations[wh_name])
```
#### Site 模式(前端定向放置)
适用于有固定孔位/槽位的设备(如移液站 PRCXI 9300Deck 通过 `sites` 列表定义前端展示的放置位,前端据此渲染可拖拽的孔位布局:
```python
import collections
from typing import Any, Dict, List, Optional
from pylabrobot.resources import Deck, Resource, Coordinate
from unilabos.registry.decorators import resource
@resource(id="MyLabDeck", category=["deck"], description="带 Site 定向放置的 Deck")
class MyLabDeck(Deck):
# 根据设备台面实测批量计算各 slot 坐标偏移
_DEFAULT_SITE_POSITIONS = [
(0, 0, 0), (138, 0, 0), (276, 0, 0), (414, 0, 0), # T1-T4
(0, 96, 0), (138, 96, 0), (276, 96, 0), (414, 96, 0), # T5-T8
]
_DEFAULT_SITE_SIZE = {"width": 128.0, "height": 86.0, "depth": 0}
_DEFAULT_CONTENT_TYPE = ["plate", "tip_rack", "tube_rack", "adaptor"]
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
sites: Optional[List[Dict[str, Any]]] = None, **kwargs):
super().__init__(size_x, size_y, size_z, name)
if sites is not None:
self.sites = [dict(s) for s in sites]
else:
self.sites = []
for i, (x, y, z) in enumerate(self._DEFAULT_SITE_POSITIONS):
self.sites.append({
"label": f"T{i + 1}", # 前端显示的槽位标签
"visible": True, # 是否在前端可见
"position": {"x": x, "y": y, "z": z}, # 槽位物理坐标
"size": dict(self._DEFAULT_SITE_SIZE), # 槽位尺寸
"content_type": list(self._DEFAULT_CONTENT_TYPE), # 允许放入的物料类型
})
self._ordering = collections.OrderedDict(
(site["label"], None) for site in self.sites
)
def assign_child_resource(self, resource: Resource,
location: Optional[Coordinate] = None,
reassign: bool = True,
spot: Optional[int] = None):
idx = spot
if spot is None:
for i, site in enumerate(self.sites):
if site.get("label") == resource.name:
idx = i
break
if idx is None:
for i in range(len(self.sites)):
if self._get_site_resource(i) is None:
idx = i
break
if idx is None:
raise ValueError(f"No available site for '{resource.name}'")
loc = Coordinate(**self.sites[idx]["position"])
super().assign_child_resource(resource, location=loc, reassign=reassign)
def serialize(self) -> dict:
data = super().serialize()
sites_out = []
for i, site in enumerate(self.sites):
occupied = self._get_site_resource(i)
sites_out.append({
"label": site["label"],
"visible": site.get("visible", True),
"occupied_by": occupied.name if occupied else None,
"position": site["position"],
"size": site["size"],
"content_type": site["content_type"],
})
data["sites"] = sites_out
return data
```
**Site 字段说明:**
| 字段 | 类型 | 说明 |
|------|------|------|
| `label` | str | 槽位标签(如 `"T1"`),前端显示名称,也用于匹配 resource.name |
| `visible` | bool | 是否在前端可见 |
| `position` | dict | 物理坐标 `{x, y, z}`mm需自行测量计算偏移 |
| `size` | dict | 槽位尺寸 `{width, height, depth}`mm |
| `content_type` | list | 允许放入的物料类型,如 `["plate", "tip_rack", "tube_rack", "adaptor"]` |
**参考实现:** `unilabos/devices/liquid_handling/prcxi/prcxi.py` 中的 `PRCXI9300Deck`4x4 共 16 个 site
---
## 文件位置
```
unilabos/resources/
├── <project>/ # 按项目分组
│ ├── bottles.py # Bottle 工厂函数
│ ├── bottle_carriers.py # Carrier 工厂函数
│ ├── warehouses.py # WareHouse 工厂函数
│ └── decks.py # Deck 类定义
```
---
## 验证
```bash
# 资源可导入
python -c "from unilabos.resources.my_project.bottles import My_Reagent_Bottle; print(My_Reagent_Bottle('test'))"
# 启动测试AST 自动扫描)
unilab -g <graph>.json
```
仅在以下情况仍需 YAML第三方库资源如 pylabrobot 内置资源,无 `@resource` 装饰器)。
---
## 关键路径
| 内容 | 路径 |
|------|------|
| Bottle/Carrier 基类 | `unilabos/resources/itemized_carrier.py` |
| WareHouse 基类 + 工厂 | `unilabos/resources/warehouse.py` |
| PLR 注册 | `unilabos/resources/plr_additional_res_reg.py` |
| 装饰器定义 | `unilabos/registry/decorators.py` |

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# 资源高级参考
本文件是 SKILL.md 的补充,包含类继承体系、序列化/反序列化、Bioyond 物料同步、非瓶类资源和仓库工厂模式。Agent 在需要实现这些功能时按需阅读。
---
## 1. 类继承体系
```
PyLabRobot
├── Resource (PLR 基类)
│ ├── Well
│ │ └── Bottle (unilabos) → 瓶/小瓶/烧杯/反应器
│ ├── Deck
│ │ └── 自定义 Deck 类 (unilabos) → 工作站台面
│ ├── ResourceHolder → 槽位占位符
│ └── Container
│ └── Battery (unilabos) → 组装好的电池
├── ItemizedCarrier (unilabos, 继承 Resource)
│ ├── BottleCarrier (unilabos) → 瓶载架
│ └── WareHouse (unilabos) → 堆栈仓库
├── ItemizedResource (PLR)
│ └── MagazineHolder (unilabos) → 子弹夹载架
└── ResourceStack (PLR)
└── Magazine (unilabos) → 子弹夹洞位
```
### Bottle 类细节
```python
class Bottle(Well):
def __init__(self, name, diameter, height, max_volume,
size_x=0.0, size_y=0.0, size_z=0.0,
barcode=None, category="container", model=None, **kwargs):
super().__init__(
name=name,
size_x=diameter, # PLR 用 diameter 作为 size_x/size_y
size_y=diameter,
size_z=height, # PLR 用 height 作为 size_z
max_volume=max_volume,
category=category,
model=model,
bottom_type="flat",
cross_section_type="circle"
)
```
注意 `size_x = size_y = diameter``size_z = height`
### ItemizedCarrier 核心方法
| 方法 | 说明 |
|------|------|
| `__getitem__(identifier)` | 通过索引或 Excel 标识(如 `"A01"`)访问槽位 |
| `__setitem__(identifier, resource)` | 向槽位放入资源 |
| `get_child_identifier(child)` | 获取子资源的标识符 |
| `capacity` | 总槽位数 |
| `sites` | 所有槽位字典 |
---
## 2. 序列化与反序列化
### PLR ↔ UniLab 转换
| 函数 | 位置 | 方向 |
|------|------|------|
| `ResourceTreeSet.from_plr_resources(resources)` | `resource_tracker.py` | PLR → UniLab |
| `ResourceTreeSet.to_plr_resources()` | `resource_tracker.py` | UniLab → PLR |
### `from_plr_resources` 流程
```
PLR Resource
↓ build_uuid_mapping (递归生成 UUID)
↓ resource.serialize() → dict
↓ resource.serialize_all_state() → states
↓ resource_plr_inner (递归构建 ResourceDictInstance)
ResourceTreeSet
```
关键:每个 PLR 资源通过 `unilabos_uuid` 属性携带 UUID`unilabos_extra` 携带扩展数据(如 `class` 名)。
### `to_plr_resources` 流程
```
ResourceTreeSet
↓ collect_node_data (收集 UUID、状态、扩展数据)
↓ node_to_plr_dict (转为 PLR 字典格式)
↓ find_subclass(type_name, PLRResource) (查找 PLR 子类)
↓ sub_cls.deserialize(plr_dict) (反序列化)
↓ loop_set_uuid, loop_set_extra (递归设置 UUID 和扩展)
PLR Resource
```
### Bottle 序列化
```python
class Bottle(Well):
def serialize(self) -> dict:
data = super().serialize()
return {**data, "diameter": self.diameter, "height": self.height}
@classmethod
def deserialize(cls, data: dict, allow_marshal=False):
barcode_data = data.pop("barcode", None)
instance = super().deserialize(data, allow_marshal=allow_marshal)
if barcode_data and isinstance(barcode_data, str):
instance.barcode = barcode_data
return instance
```
---
## 3. Bioyond 物料同步
### 双向转换函数
| 函数 | 位置 | 方向 |
|------|------|------|
| `resource_bioyond_to_plr(materials, type_mapping, deck)` | `graphio.py` | Bioyond → PLR |
| `resource_plr_to_bioyond(resources, type_mapping, warehouse_mapping)` | `graphio.py` | PLR → Bioyond |
### `resource_bioyond_to_plr` 流程
```
Bioyond 物料列表
↓ reverse_type_mapping: {typeName → (model, UUID)}
↓ 对每个物料:
typeName → 查映射 → model (如 "BIOYOND_PolymerStation_Reactor")
initialize_resource({"name": unique_name, "class": model})
↓ 设置 unilabos_extra (material_bioyond_id, material_bioyond_name 等)
↓ 处理 detail (子物料/坐标)
↓ 按 locationName 放入 deck.warehouses 对应槽位
PLR 资源列表
```
### `resource_plr_to_bioyond` 流程
```
PLR 资源列表
↓ 遍历每个资源:
载架(capacity > 1): 生成 details 子物料 + 坐标
单瓶: 直接映射
↓ type_mapping 查找 typeId
↓ warehouse_mapping 查找位置 UUID
↓ 组装 Bioyond 格式 (name, typeName, typeId, quantity, Parameters, locations)
Bioyond 物料列表
```
### BioyondResourceSynchronizer
工作站通过 `ResourceSynchronizer` 自动同步物料:
```python
class BioyondResourceSynchronizer(ResourceSynchronizer):
def sync_from_external(self) -> bool:
all_data = []
all_data.extend(api_client.stock_material('{"typeMode": 0}')) # 耗材
all_data.extend(api_client.stock_material('{"typeMode": 1}')) # 样品
all_data.extend(api_client.stock_material('{"typeMode": 2}')) # 试剂
unilab_resources = resource_bioyond_to_plr(
all_data,
type_mapping=self.workstation.bioyond_config["material_type_mappings"],
deck=self.workstation.deck
)
# 更新 deck 上的资源
```
---
## 4. 非瓶类资源
### ElectrodeSheet极片
路径:`unilabos/resources/battery/electrode_sheet.py`
```python
class ElectrodeSheet(ResourcePLR):
"""片状材料(极片、隔膜、弹片、垫片等)"""
_unilabos_state = {
"diameter": 0.0,
"thickness": 0.0,
"mass": 0.0,
"material_type": "",
"color": "",
"info": "",
}
```
工厂函数:`PositiveCan`, `PositiveElectrode`, `NegativeCan`, `NegativeElectrode`, `SpringWasher`, `FlatWasher`, `AluminumFoil`
### Battery电池
```python
class Battery(Container):
"""组装好的电池"""
_unilabos_state = {
"color": "",
"electrolyte_name": "",
"open_circuit_voltage": 0.0,
}
```
### Magazine / MagazineHolder子弹夹
```python
class Magazine(ResourceStack):
"""子弹夹洞位,可堆叠 ElectrodeSheet"""
# direction, max_sheets
class MagazineHolder(ItemizedResource):
"""多洞位子弹夹"""
# hole_diameter, hole_depth, max_sheets_per_hole
```
工厂函数 `magazine_factory()``create_homogeneous_resources` 生成洞位,可选预填 `ElectrodeSheet``Battery`
---
## 5. 仓库工厂模式参考
### 实际 warehouse 工厂函数示例
```python
# 行优先 4x4 仓库
def bioyond_warehouse_1x4x4(name: str) -> WareHouse:
return warehouse_factory(
name=name,
num_items_x=4, num_items_y=4, num_items_z=1,
dx=10.0, dy=10.0, dz=10.0,
item_dx=147.0, item_dy=106.0, item_dz=130.0,
layout="row-major", # A01,A02,A03,A04, B01,...
)
# 右侧 4x4 仓库(列名偏移)
def bioyond_warehouse_1x4x4_right(name: str) -> WareHouse:
return warehouse_factory(
name=name,
num_items_x=4, num_items_y=4, num_items_z=1,
dx=10.0, dy=10.0, dz=10.0,
item_dx=147.0, item_dy=106.0, item_dz=130.0,
col_offset=4, # A05,A06,A07,A08
layout="row-major",
)
# 竖向仓库(站内试剂存放)
def bioyond_warehouse_reagent_storage(name: str) -> WareHouse:
return warehouse_factory(
name=name,
num_items_x=1, num_items_y=2, num_items_z=1,
dx=10.0, dy=10.0, dz=10.0,
item_dx=147.0, item_dy=106.0, item_dz=130.0,
layout="vertical-col-major",
)
# 行偏移F 行开始)
def bioyond_warehouse_5x3x1(name: str, row_offset: int = 0) -> WareHouse:
return warehouse_factory(
name=name,
num_items_x=3, num_items_y=5, num_items_z=1,
dx=10.0, dy=10.0, dz=10.0,
item_dx=159.0, item_dy=183.0, item_dz=130.0,
row_offset=row_offset, # 0→A行起5→F行起
layout="row-major",
)
```
### layout 类型说明
| layout | 命名顺序 | 适用场景 |
|--------|---------|---------|
| `col-major` (默认) | A01,B01,C01,D01, A02,B02,... | 列优先,标准堆栈 |
| `row-major` | A01,A02,A03,A04, B01,B02,... | 行优先Bioyond 前端展示 |
| `vertical-col-major` | 竖向排列,标签从底部开始 | 竖向仓库(试剂存放、测密度) |
---
## 6. 关键路径
| 内容 | 路径 |
|------|------|
| Bottle/Carrier 基类 | `unilabos/resources/itemized_carrier.py` |
| WareHouse 类 + 工厂 | `unilabos/resources/warehouse.py` |
| ResourceTreeSet 转换 | `unilabos/resources/resource_tracker.py` |
| Bioyond 物料转换 | `unilabos/resources/graphio.py` |
| Bioyond 仓库定义 | `unilabos/resources/bioyond/warehouses.py` |
| 电池资源 | `unilabos/resources/battery/` |
| PLR 注册 | `unilabos/resources/plr_additional_res_reg.py` |

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---
name: add-workstation
description: Guide for adding new workstations to Uni-Lab-OS (接入新工作站). Uses @device decorator + AST auto-scanning. Walks through workstation type, sub-device composition, driver creation, deck setup, and graph file. Use when the user wants to add a workstation, create a workstation driver, configure a station with sub-devices, or mentions 工作站/工站/station/workstation.
---
# Uni-Lab-OS 工作站接入指南
工作站workstation是组合多个子设备的大型设备拥有独立的物料管理系统和工作流引擎。使用 `@device` 装饰器注册AST 自动扫描生成注册表。
---
## 工作站类型
| 类型 | 基类 | 适用场景 |
| ------------------- | ----------------- | ---------------------------------- |
| **Protocol 工作站** | `ProtocolNode` | 标准化学操作协议(泵转移、过滤等) |
| **外部系统工作站** | `WorkstationBase` | 与外部 LIMS/MES 对接 |
| **硬件控制工作站** | `WorkstationBase` | 直接控制 PLC/硬件 |
---
## @device 装饰器(工作站)
工作站也使用 `@device` 装饰器注册,参数与普通设备一致:
```python
@device(
id="my_workstation", # 注册表唯一标识(必填)
category=["workstation"], # 分类标签
description="我的工作站",
)
```
如果一个工作站类支持多个具体变体,可使用 `ids` / `id_meta`,与设备的用法相同(参见 add-device SKILL
---
## 工作站驱动模板
### 模板 A基于外部系统的工作站
```python
import logging
from typing import Dict, Any, Optional
from pylabrobot.resources import Deck
from unilabos.registry.decorators import device, topic_config, not_action
from unilabos.devices.workstation.workstation_base import WorkstationBase
try:
from unilabos.ros.nodes.presets.workstation import ROS2WorkstationNode
except ImportError:
ROS2WorkstationNode = None
@device(id="my_workstation", category=["workstation"], description="我的工作站")
class MyWorkstation(WorkstationBase):
_ros_node: "ROS2WorkstationNode"
def __init__(self, config=None, deck=None, protocol_type=None, **kwargs):
super().__init__(deck=deck, **kwargs)
self.config = config or {}
self.logger = logging.getLogger("MyWorkstation")
self.api_host = self.config.get("api_host", "")
self._status = "Idle"
@not_action
def post_init(self, ros_node: "ROS2WorkstationNode"):
super().post_init(ros_node)
self._ros_node = ros_node
async def scheduler_start(self, **kwargs) -> Dict[str, Any]:
"""注册为工作站动作"""
return {"success": True}
async def create_order(self, json_str: str, **kwargs) -> Dict[str, Any]:
"""注册为工作站动作"""
return {"success": True}
@property
@topic_config()
def workflow_sequence(self) -> str:
return "[]"
@property
@topic_config()
def material_info(self) -> str:
return "{}"
```
### 模板 BProtocol 工作站
直接使用 `ProtocolNode`,通常不需要自定义驱动类:
```python
from unilabos.devices.workstation.workstation_base import ProtocolNode
```
在图文件中配置 `protocol_type` 即可。
---
## 子设备访问sub_devices
工站初始化子设备后,所有子设备实例存储在 `self._ros_node.sub_devices` 字典中key 为设备 idvalue 为 `ROS2DeviceNode` 实例)。工站的驱动类可以直接获取子设备实例来调用其方法:
```python
# 在工站驱动类的方法中访问子设备
sub = self._ros_node.sub_devices["pump_1"]
# .driver_instance — 子设备的驱动实例(即设备 Python 类的实例)
sub.driver_instance.some_method(arg1, arg2)
# .ros_node_instance — 子设备的 ROS2 节点实例
sub.ros_node_instance._action_value_mappings # 查看子设备支持的 action
```
**常见用法**
```python
class MyWorkstation(WorkstationBase):
def my_protocol(self, **kwargs):
# 获取子设备驱动实例
pump = self._ros_node.sub_devices["pump_1"].driver_instance
heater = self._ros_node.sub_devices["heater_1"].driver_instance
# 直接调用子设备方法
pump.aspirate(volume=100)
heater.set_temperature(80)
```
> 参考实现:`unilabos/devices/workstation/bioyond_studio/reaction_station/reaction_station.py` 中通过 `self._ros_node.sub_devices.get(reactor_id)` 获取子反应器实例并更新数据。
---
## 硬件通信接口hardware_interface
硬件控制型工作站通常需要通过串口Serial、Modbus 等通信协议控制多个子设备。Uni-Lab-OS 通过 **通信设备代理** 机制实现端口共享:一个串口只创建一个 `serial` 节点,多个子设备共享这个通信实例。
### 工作原理
`ROS2WorkstationNode` 初始化时分两轮遍历子设备(`workstation.py`
**第一轮 — 初始化所有子设备**:按 `children` 顺序调用 `initialize_device()`,通信设备(`serial_` / `io_` 开头的 id优先完成初始化创建 `serial.Serial()` 实例。其他子设备此时 `self.hardware_interface = "serial_pump"`(字符串)。
**第二轮 — 代理替换**:遍历所有已初始化的子设备,读取子设备的 `_hardware_interface` 配置:
```
hardware_interface = d.ros_node_instance._hardware_interface
# → {"name": "hardware_interface", "read": "send_command", "write": "send_command"}
```
1.`name` 字段对应的属性值:`name_value = getattr(driver, hardware_interface["name"])`
- 如果 `name_value` 是字符串且该字符串是某个子设备的 id → 触发代理替换
2. 从通信设备获取真正的 `read`/`write` 方法
3.`setattr(driver, read_method, _read)` 将通信设备的方法绑定到子设备上
因此:
- **通信设备 id 必须与子设备 config 中填的字符串完全一致**(如 `"serial_pump"`
- **通信设备 id 必须以 `serial_``io_` 开头**(否则第一轮不会被识别为通信设备)
- **通信设备必须在 `children` 列表中排在最前面**,确保先初始化
### HardwareInterface 参数说明
```python
from unilabos.registry.decorators import HardwareInterface
HardwareInterface(
name="hardware_interface", # __init__ 中接收通信实例的属性名
read="send_command", # 通信设备上暴露的读方法名
write="send_command", # 通信设备上暴露的写方法名
extra_info=["list_ports"], # 可选:额外暴露的方法
)
```
**`name` 字段的含义**:对应设备类 `__init__` 中,用于保存通信实例的**属性名**。系统据此知道要替换哪个属性。大部分设备直接用 `"hardware_interface"`,也可以自定义(如 `"io_device_port"`)。
### 示例 1name="hardware_interface"
```python
from unilabos.registry.decorators import device, HardwareInterface
@device(
id="my_pump",
category=["pump_and_valve"],
hardware_interface=HardwareInterface(
name="hardware_interface",
read="send_command",
write="send_command",
),
)
class MyPump:
def __init__(self, port=None, address="1", **kwargs):
# name="hardware_interface" → 系统替换 self.hardware_interface
self.hardware_interface = port # 初始为字符串 "serial_pump",启动后被替换为 Serial 实例
self.address = address
def send_command(self, command: str):
full_command = f"/{self.address}{command}\r\n"
self.hardware_interface.write(bytearray(full_command, "ascii"))
return self.hardware_interface.read_until(b"\n")
```
### 示例 2电磁阀name="io_device_port",自定义属性名)
```python
@device(
id="solenoid_valve",
category=["pump_and_valve"],
hardware_interface=HardwareInterface(
name="io_device_port", # 自定义属性名 → 系统替换 self.io_device_port
read="read_io_coil",
write="write_io_coil",
),
)
class SolenoidValve:
def __init__(self, io_device_port: str = None, **kwargs):
# name="io_device_port" → 图文件 config 中用 "io_device_port": "io_board_1"
self.io_device_port = io_device_port # 初始为字符串,系统替换为 Modbus 实例
```
### Serial 通信设备class="serial"
`serial` 是 Uni-Lab-OS 内置的通信代理设备,代码位于 `unilabos/ros/nodes/presets/serial_node.py`
```python
from serial import Serial, SerialException
from threading import Lock
class ROS2SerialNode(BaseROS2DeviceNode):
def __init__(self, device_id, registry_name, port: str, baudrate: int = 9600, **kwargs):
self.port = port
self.baudrate = baudrate
self._hardware_interface = {
"name": "hardware_interface",
"write": "send_command",
"read": "read_data",
}
self._query_lock = Lock()
self.hardware_interface = Serial(baudrate=baudrate, port=port)
BaseROS2DeviceNode.__init__(
self, driver_instance=self, registry_name=registry_name,
device_id=device_id, status_types={}, action_value_mappings={},
hardware_interface=self._hardware_interface, print_publish=False,
)
self.create_service(SerialCommand, "serialwrite", self.handle_serial_request)
def send_command(self, command: str):
with self._query_lock:
self.hardware_interface.write(bytearray(f"{command}\n", "ascii"))
return self.hardware_interface.read_until(b"\n").decode()
def read_data(self):
with self._query_lock:
return self.hardware_interface.read_until(b"\n").decode()
```
在图文件中使用 `"class": "serial"` 即可创建串口代理:
```json
{
"id": "serial_pump",
"class": "serial",
"parent": "my_station",
"config": { "port": "COM7", "baudrate": 9600 }
}
```
### 图文件配置
**通信设备必须在 `children` 列表中排在最前面**,确保先于其他子设备初始化:
```json
{
"nodes": [
{
"id": "my_station",
"class": "workstation",
"children": ["serial_pump", "pump_1", "pump_2"],
"config": { "protocol_type": ["PumpTransferProtocol"] }
},
{
"id": "serial_pump",
"class": "serial",
"parent": "my_station",
"config": { "port": "COM7", "baudrate": 9600 }
},
{
"id": "pump_1",
"class": "syringe_pump_with_valve.runze.SY03B-T08",
"parent": "my_station",
"config": { "port": "serial_pump", "address": "1", "max_volume": 25.0 }
},
{
"id": "pump_2",
"class": "syringe_pump_with_valve.runze.SY03B-T08",
"parent": "my_station",
"config": { "port": "serial_pump", "address": "2", "max_volume": 25.0 }
}
],
"links": [
{
"source": "pump_1",
"target": "serial_pump",
"type": "communication",
"port": { "pump_1": "port", "serial_pump": "port" }
},
{
"source": "pump_2",
"target": "serial_pump",
"type": "communication",
"port": { "pump_2": "port", "serial_pump": "port" }
}
]
}
```
### 通信协议速查
| 协议 | config 参数 | 依赖包 | 通信设备 class |
| -------------------- | ------------------------------ | ---------- | -------------------------- |
| Serial (RS232/RS485) | `port`, `baudrate` | `pyserial` | `serial` |
| Modbus RTU | `port`, `baudrate`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
| Modbus TCP | `host`, `port`, `slave_id` | `pymodbus` | `device_comms/modbus_plc/` |
| TCP Socket | `host`, `port` | stdlib | 自定义 |
| HTTP API | `url`, `token` | `requests` | `device_comms/rpc.py` |
参考实现:`unilabos/test/experiments/Grignard_flow_batchreact_single_pumpvalve.json`
---
## Deck 与物料生命周期
### 1. Deck 入参与两种初始化模式
系统根据设备节点 `config.deck` 的写法,自动反序列化 Deck 实例后传入 `__init__``deck` 参数。目前 `deck` 是固定字段名,只支持一个主 Deck。建议一个设备拥有一个台面台面上抽象二级、三级子物料。
有两种初始化模式:
#### init 初始化(推荐)
`config.deck` 直接包含 `_resource_type` + `_resource_child_name`,系统先用 Deck 节点的 `config` 调用 Deck 类的 `__init__` 反序列化,再将实例传入设备的 `deck` 参数。子物料随 Deck 的 `children` 一起反序列化。
```json
"config": {
"deck": {
"_resource_type": "unilabos.devices.liquid_handling.prcxi.prcxi:PRCXI9300Deck",
"_resource_child_name": "PRCXI_Deck"
}
}
```
#### deserialize 初始化
`config.deck``data` 包裹一层,系统走 `deserialize` 路径,可传入更多参数(如 `allow_marshal` 等):
```json
"config": {
"deck": {
"data": {
"_resource_child_name": "YB_Bioyond_Deck",
"_resource_type": "unilabos.resources.bioyond.decks:BIOYOND_YB_Deck"
}
}
}
```
没有特殊需求时推荐 init 初始化。
#### config.deck 字段说明
| 字段 | 说明 |
|------|------|
| `_resource_type` | Deck 类的完整模块路径(`module:ClassName` |
| `_resource_child_name` | 对应图文件中 Deck 节点的 `id`,建立父子关联 |
#### 设备 __init__ 接收
```python
def __init__(self, config=None, deck=None, protocol_type=None, **kwargs):
super().__init__(deck=deck, **kwargs)
# deck 已经是反序列化后的 Deck 实例
# → PRCXI9300Deck / BIOYOND_YB_Deck 等
```
#### Deck 节点(图文件中)
Deck 节点作为设备的 `children` 之一,`parent` 指向设备 id
```json
{
"id": "PRCXI_Deck",
"parent": "PRCXI",
"type": "deck",
"class": "",
"children": [],
"config": {
"type": "PRCXI9300Deck",
"size_x": 542, "size_y": 374, "size_z": 0,
"category": "deck",
"sites": [...]
},
"data": {}
}
```
- `config` 中的字段会传入 Deck 类的 `__init__`(因此 `__init__` 必须能接受所有 `serialize()` 输出的字段)
- `children` 初始为空时,由同步器或手动初始化填充
- `config.type` 填 Deck 类名
### 2. Deck 为空时自行初始化
如果 Deck 节点的 `children` 为空,工作站需在 `post_init` 或首次同步时自行初始化内容:
```python
@not_action
def post_init(self, ros_node):
super().post_init(ros_node)
if self.deck and not self.deck.children:
self._initialize_default_deck()
def _initialize_default_deck(self):
from my_labware import My_TipRack, My_Plate
self.deck.assign_child_resource(My_TipRack("T1"), spot=0)
self.deck.assign_child_resource(My_Plate("T2"), spot=1)
```
### 3. 物料双向同步
当工作站对接外部系统LIMS/MES需要实现 `ResourceSynchronizer` 处理双向物料同步:
```python
from unilabos.devices.workstation.workstation_base import ResourceSynchronizer
class MyResourceSynchronizer(ResourceSynchronizer):
def sync_from_external(self) -> bool:
"""从外部系统同步到 self.workstation.deck"""
external_data = self._query_external_materials()
# 以外部工站为准:根据外部数据反向创建 PLR 资源实例
for item in external_data:
cls = self._resolve_resource_class(item["type"])
resource = cls(name=item["name"], **item["params"])
self.workstation.deck.assign_child_resource(resource, spot=item["slot"])
return True
def sync_to_external(self, resource) -> bool:
"""将 UniLab 侧物料变更同步到外部系统"""
# 以 UniLab 为准:将 PLR 资源转为外部格式并推送
external_format = self._convert_to_external(resource)
return self._push_to_external(external_format)
def handle_external_change(self, change_info) -> bool:
"""处理外部系统主动推送的变更"""
return True
```
同步策略取决于业务场景:
- **以外部工站为准**:从外部 API 查询物料数据,反向创建对应的 PLR 资源实例放到 Deck 上
- **以 UniLab 为准**UniLab 侧的物料变更通过 `sync_to_external` 推送到外部系统
在工作站 `post_init` 中初始化同步器:
```python
@not_action
def post_init(self, ros_node):
super().post_init(ros_node)
self.resource_synchronizer = MyResourceSynchronizer(self)
self.resource_synchronizer.sync_from_external()
```
### 4. 序列化与持久化serialize / serialize_state
资源类需正确实现序列化,系统据此完成持久化和前端同步。
**`serialize()`** — 输出资源的结构信息(`config` 层),反序列化时作为 `__init__` 的入参回传。因此 **`__init__` 必须通过 `**kwargs`接受`serialize()` 输出的所有字段\*\*,即使当前不使用:
```python
class MyDeck(Deck):
def __init__(self, name, size_x, size_y, size_z,
sites=None, # serialize() 输出的字段
rotation=None, # serialize() 输出的字段
barcode=None, # serialize() 输出的字段
**kwargs): # 兜底:接受所有未知的 serialize 字段
super().__init__(size_x, size_y, size_z, name)
# ...
def serialize(self) -> dict:
data = super().serialize()
data["sites"] = [...] # 自定义字段
return data
```
**`serialize_state()`** — 输出资源的运行时状态(`data` 层),用于持久化可变信息。`data` 中的内容会被正确保存和恢复:
```python
class MyPlate(Plate):
def __init__(self, name, size_x, size_y, size_z,
material_info=None, **kwargs):
super().__init__(name, size_x, size_y, size_z, **kwargs)
self._unilabos_state = {}
if material_info:
self._unilabos_state["Material"] = material_info
def serialize_state(self) -> Dict[str, Any]:
data = super().serialize_state()
data.update(self._unilabos_state)
return data
```
关键要点:
- `serialize()` 输出的所有字段都会作为 `config` 回传到 `__init__`,所以 `__init__` 必须能接受它们(显式声明或 `**kwargs`
- `serialize_state()` 输出的 `data` 用于持久化运行时状态(如物料信息、液体量等)
- `_unilabos_state` 中只存可 JSON 序列化的基本类型str, int, float, bool, list, dict, None
### 5. 子物料自动同步
子物料Bottle、Plate、TipRack 等)放到 Deck 上后,系统会自动将其同步到前端的 Deck 视图。只需保证资源类正确实现了 `serialize()` / `serialize_state()` 和反序列化即可。
### 6. 图文件配置(参考 prcxi_9320_slim.json
```json
{
"nodes": [
{
"id": "my_station",
"type": "device",
"class": "my_workstation",
"config": {
"deck": {
"_resource_type": "unilabos.resources.my_module:MyDeck",
"_resource_child_name": "my_deck"
},
"host": "10.20.30.1",
"port": 9999
}
},
{
"id": "my_deck",
"parent": "my_station",
"type": "deck",
"class": "",
"children": [],
"config": {
"type": "MyLabDeck",
"size_x": 542,
"size_y": 374,
"size_z": 0,
"category": "deck",
"sites": [
{
"label": "T1",
"visible": true,
"occupied_by": null,
"position": { "x": 0, "y": 0, "z": 0 },
"size": { "width": 128.0, "height": 86, "depth": 0 },
"content_type": ["plate", "tip_rack", "tube_rack", "adaptor"]
}
]
},
"data": {}
}
],
"edges": []
}
```
Deck 节点要点:
- `config.type` 填 Deck 类名(如 `"PRCXI9300Deck"`
- `config.sites` 完整列出所有 site从 Deck 类的 `serialize()` 输出获取)
- `children` 初始为空(由同步器或手动初始化填充)
- 设备节点 `config.deck._resource_type` 指向 Deck 类的完整模块路径
---
## 子设备
子设备按标准设备接入流程创建(参见 add-device SKILL使用 `@device` 装饰器。
子设备约束:
- 图文件中 `parent` 指向工作站 ID
- 在工作站 `children` 数组中列出
---
## 关键规则
1. **`__init__` 必须接受 `deck``**kwargs`** — `WorkstationBase.**init**`需要`deck` 参数
2. **Deck 通过 `config.deck._resource_type` 反序列化传入** — 不要在 `__init__` 中手动创建 Deck
3. **Deck 为空时自行初始化内容** — 在 `post_init` 中检查并填充默认物料
4. **外部同步实现 `ResourceSynchronizer`**`sync_from_external` / `sync_to_external`
5. **通过 `self._children` 访问子设备** — 不要自行维护子设备引用
6. **`post_init` 中启动后台服务** — 不要在 `__init__` 中启动网络连接
7. **异步方法使用 `await self._ros_node.sleep()`** — 禁止 `time.sleep()``asyncio.sleep()`
8. **使用 `@not_action` 标记非动作方法**`post_init`, `initialize`, `cleanup`
9. **子物料保证正确 serialize/deserialize** — 系统自动同步到前端 Deck 视图
---
## 验证
```bash
# 模块可导入
python -c "from unilabos.devices.workstation.<name>.<name> import <ClassName>"
# 启动测试AST 自动扫描)
unilab -g <graph>.json
```
---
## 现有工作站参考
| 工作站 | 驱动类 | 类型 |
| -------------- | ----------------------------- | -------- |
| Protocol 通用 | `ProtocolNode` | Protocol |
| Bioyond 反应站 | `BioyondReactionStation` | 外部系统 |
| 纽扣电池组装 | `CoinCellAssemblyWorkstation` | 硬件控制 |
参考路径:`unilabos/devices/workstation/` 目录下各工作站实现。

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@@ -0,0 +1,371 @@
# 工作站高级模式参考
本文件是 SKILL.md 的补充,包含外部系统集成、物料同步、配置结构等高级模式。
Agent 在需要实现这些功能时按需阅读。
---
## 1. 外部系统集成模式
### 1.1 RPC 客户端
与外部 LIMS/MES 系统通信的标准模式。继承 `BaseRequest`,所有接口统一用 POST。
```python
from unilabos.device_comms.rpc import BaseRequest
class MySystemRPC(BaseRequest):
"""外部系统 RPC 客户端"""
def __init__(self, host: str, api_key: str):
super().__init__(host)
self.api_key = api_key
def _request(self, endpoint: str, data: dict = None) -> dict:
return self.post(
url=f"{self.host}/api/{endpoint}",
params={
"apiKey": self.api_key,
"requestTime": self.get_current_time_iso8601(),
"data": data or {},
},
)
def query_status(self) -> dict:
return self._request("status/query")
def create_order(self, order_data: dict) -> dict:
return self._request("order/create", order_data)
```
参考:`unilabos/devices/workstation/bioyond_studio/bioyond_rpc.py``BioyondV1RPC`
### 1.2 HTTP 回调服务
接收外部系统报送的标准模式。使用 `WorkstationHTTPService`,在 `post_init` 中启动。
```python
from unilabos.devices.workstation.workstation_http_service import WorkstationHTTPService
class MyWorkstation(WorkstationBase):
def __init__(self, config=None, deck=None, **kwargs):
super().__init__(deck=deck, **kwargs)
self.config = config or {}
http_cfg = self.config.get("http_service_config", {})
self._http_service_config = {
"host": http_cfg.get("http_service_host", "127.0.0.1"),
"port": http_cfg.get("http_service_port", 8080),
}
self.http_service = None
def post_init(self, ros_node):
super().post_init(ros_node)
self.http_service = WorkstationHTTPService(
workstation_instance=self,
host=self._http_service_config["host"],
port=self._http_service_config["port"],
)
self.http_service.start()
```
**HTTP 服务路由**(固定端点,由 `WorkstationHTTPHandler` 自动分发):
| 端点 | 调用的工作站方法 |
|------|-----------------|
| `/report/step_finish` | `process_step_finish_report(report_request)` |
| `/report/sample_finish` | `process_sample_finish_report(report_request)` |
| `/report/order_finish` | `process_order_finish_report(report_request, used_materials)` |
| `/report/material_change` | `process_material_change_report(report_data)` |
| `/report/error_handling` | `handle_external_error(error_data)` |
实现对应方法即可接收回调:
```python
def process_step_finish_report(self, report_request) -> Dict[str, Any]:
"""处理步骤完成报告"""
step_name = report_request.data.get("stepName")
return {"success": True, "message": f"步骤 {step_name} 已处理"}
def process_order_finish_report(self, report_request, used_materials) -> Dict[str, Any]:
"""处理订单完成报告"""
order_code = report_request.data.get("orderCode")
return {"success": True}
```
参考:`unilabos/devices/workstation/workstation_http_service.py`
### 1.3 连接监控
独立线程周期性检测外部系统连接状态,状态变化时发布 ROS 事件。
```python
class ConnectionMonitor:
def __init__(self, workstation, check_interval=30):
self.workstation = workstation
self.check_interval = check_interval
self._running = False
self._thread = None
def start(self):
self._running = True
self._thread = threading.Thread(target=self._monitor_loop, daemon=True)
self._thread.start()
def _monitor_loop(self):
while self._running:
try:
# 调用外部系统接口检测连接
self.workstation.hardware_interface.ping()
status = "online"
except Exception:
status = "offline"
time.sleep(self.check_interval)
```
参考:`unilabos/devices/workstation/bioyond_studio/station.py``ConnectionMonitor`
---
## 2. Config 结构模式
工作站的 `config` 在图文件中定义,传入 `__init__`。以下是常见字段模式:
### 2.1 外部系统连接
```json
{
"api_host": "http://192.168.1.100:8080",
"api_key": "YOUR_API_KEY"
}
```
### 2.2 HTTP 回调服务
```json
{
"http_service_config": {
"http_service_host": "127.0.0.1",
"http_service_port": 8080
}
}
```
### 2.3 物料类型映射
将 PLR 资源类名映射到外部系统的物料类型(名称 + UUID。用于双向物料转换。
```json
{
"material_type_mappings": {
"PLR_ResourceClassName": ["外部系统显示名", "external-type-uuid"],
"BIOYOND_PolymerStation_Reactor": ["反应器", "3a14233b-902d-0d7b-..."]
}
}
```
### 2.4 仓库映射
将仓库名映射到外部系统的仓库 UUID 和库位 UUID。用于入库/出库操作。
```json
{
"warehouse_mapping": {
"仓库名": {
"uuid": "warehouse-uuid",
"site_uuids": {
"A01": "site-uuid-A01",
"A02": "site-uuid-A02"
}
}
}
}
```
### 2.5 工作流映射
将内部工作流名映射到外部系统的工作流 ID。
```json
{
"workflow_mappings": {
"internal_workflow_name": "external-workflow-uuid"
}
}
```
### 2.6 物料默认参数
```json
{
"material_default_parameters": {
"NMP": {
"unit": "毫升",
"density": "1.03",
"densityUnit": "g/mL",
"description": "N-甲基吡咯烷酮"
}
}
}
```
---
## 3. 资源同步机制
### 3.1 ResourceSynchronizer
抽象基类,用于与外部物料系统双向同步。定义在 `workstation_base.py`
```python
from unilabos.devices.workstation.workstation_base import ResourceSynchronizer
class MyResourceSynchronizer(ResourceSynchronizer):
def __init__(self, workstation, api_client):
super().__init__(workstation)
self.api_client = api_client
def sync_from_external(self) -> bool:
"""从外部系统拉取物料到 deck"""
external_materials = self.api_client.list_materials()
for material in external_materials:
plr_resource = self._convert_to_plr(material)
self.workstation.deck.assign_child_resource(plr_resource, coordinate)
return True
def sync_to_external(self, plr_resource) -> bool:
"""将 deck 中的物料变更推送到外部系统"""
external_data = self._convert_from_plr(plr_resource)
self.api_client.update_material(external_data)
return True
def handle_external_change(self, change_info) -> bool:
"""处理外部系统推送的物料变更"""
return True
```
### 3.2 update_resource — 上传资源树到云端
将 PLR Deck 序列化后通过 ROS 服务上传。典型使用场景:
```python
# 在 post_init 中上传初始 deck
from unilabos.ros.nodes.base_device_node import ROS2DeviceNode
ROS2DeviceNode.run_async_func(
self._ros_node.update_resource, True,
**{"resources": [self.deck]}
)
# 在动作方法中更新特定资源
ROS2DeviceNode.run_async_func(
self._ros_node.update_resource, True,
**{"resources": [updated_plate]}
)
```
---
## 4. 工作流序列管理
工作站通过 `workflow_sequence` 属性管理任务队列JSON 字符串形式)。
```python
class MyWorkstation(WorkstationBase):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._workflow_sequence = []
@property
def workflow_sequence(self) -> str:
"""返回 JSON 字符串ROS 自动发布"""
import json
return json.dumps(self._workflow_sequence)
async def append_to_workflow_sequence(self, workflow_name: str) -> Dict[str, Any]:
"""添加工作流到队列"""
self._workflow_sequence.append({
"name": workflow_name,
"status": "pending",
"created_at": time.time(),
})
return {"success": True}
async def clear_workflows(self) -> Dict[str, Any]:
"""清空工作流队列"""
self._workflow_sequence = []
return {"success": True}
```
---
## 5. 站间物料转移
工作站之间转移物料的模式。通过 ROS ActionClient 调用目标站的动作。
```python
async def transfer_materials_to_another_station(
self,
target_device_id: str,
transfer_groups: list,
**kwargs,
) -> Dict[str, Any]:
"""将物料转移到另一个工作站"""
target_node = self._children.get(target_device_id)
if not target_node:
# 通过 ROS 节点查找非子设备的目标站
pass
for group in transfer_groups:
resource = self.find_resource_by_name(group["resource_name"])
# 从本站 deck 移除
resource.unassign()
# 调用目标站的接收方法
# ...
return {"success": True, "transferred": len(transfer_groups)}
```
参考:`BioyondDispensingStation.transfer_materials_to_reaction_station`
---
## 6. post_init 完整模式
`post_init` 是工作站初始化的关键阶段,此时 ROS 节点和子设备已就绪。
```python
def post_init(self, ros_node):
super().post_init(ros_node)
# 1. 初始化外部系统客户端(此时 config 已可用)
self.rpc_client = MySystemRPC(
host=self.config.get("api_host"),
api_key=self.config.get("api_key"),
)
self.hardware_interface = self.rpc_client
# 2. 启动连接监控
self.connection_monitor = ConnectionMonitor(self)
self.connection_monitor.start()
# 3. 启动 HTTP 回调服务
if hasattr(self, '_http_service_config'):
self.http_service = WorkstationHTTPService(
workstation_instance=self,
host=self._http_service_config["host"],
port=self._http_service_config["port"],
)
self.http_service.start()
# 4. 上传 deck 到云端
ROS2DeviceNode.run_async_func(
self._ros_node.update_resource, True,
**{"resources": [self.deck]}
)
# 5. 初始化资源同步器(可选)
self.resource_synchronizer = MyResourceSynchronizer(self, self.rpc_client)
```

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---
name: batch-insert-reagent
description: Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Use when the user wants to add reagents, insert chemicals, batch register reagents, or mentions 录入试剂/添加试剂/试剂入库/reagent.
---
# 批量录入试剂 Skill
通过云端 API 批量录入试剂信息,支持逐条或批量操作。
## 前置条件(缺一不可)
使用本 skill 前,**必须**先确认以下信息。如果缺少任何一项,**立即向用户询问并终止**,等补齐后再继续。
### 1. ak / sk → AUTH
询问用户的启动参数,从 `--ak` `--sk` 或 config.py 中获取。
生成 AUTH token任选一种方式
```bash
# 方式一Python 一行生成
python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
# 方式二:手动计算
# base64(ak:sk) → Authorization: Lab <token>
```
### 2. --addr → BASE URL
| `--addr` 值 | BASE |
|-------------|------|
| `test` | `https://uni-lab.test.bohrium.com` |
| `uat` | `https://uni-lab.uat.bohrium.com` |
| `local` | `http://127.0.0.1:48197` |
| 不传(默认) | `https://uni-lab.bohrium.com` |
确认后设置:
```bash
BASE="<根据 addr 确定的 URL>"
AUTH="Authorization: Lab <gen_auth.py 输出的 token>"
```
**两项全部就绪后才可发起 API 请求。**
## Session State
- `lab_uuid` — 实验室 UUID首次通过 API #1 自动获取,**不需要问用户**
## 请求约定
所有请求使用 `curl -s`POST 需加 `Content-Type: application/json`
> **Windows 平台**必须使用 `curl.exe`(而非 PowerShell 的 `curl` 别名),示例中的 `curl` 均指 `curl.exe`。
---
## API Endpoints
### 1. 获取实验室信息(自动获取 lab_uuid
```bash
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
```
返回:
```json
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
```
记住 `data.uuid``lab_uuid`
### 2. 录入试剂
```bash
curl -s -X POST "$BASE/api/v1/lab/reagent" \
-H "$AUTH" -H "Content-Type: application/json" \
-d '{
"lab_uuid": "<lab_uuid>",
"cas": "<CAS号>",
"name": "<试剂名称>",
"molecular_formula": "<分子式>",
"smiles": "<SMILES>",
"stock_in_quantity": <入库数量>,
"unit": "<单位字符串>",
"supplier": "<供应商>",
"production_date": "<生产日期 ISO 8601>",
"expiry_date": "<过期日期 ISO 8601>"
}'
```
返回成功时包含试剂 UUID
```json
{"code": 0, "data": {"uuid": "xxx", ...}}
```
---
## 试剂字段说明
| 字段 | 类型 | 必填 | 说明 | 示例 |
|------|------|------|------|------|
| `lab_uuid` | string | 是 | 实验室 UUID从 API #1 获取) | `"8511c672-..."` |
| `cas` | string | 是 | CAS 注册号 | `"7732-18-3"` |
| `name` | string | 是 | 试剂中文/英文名称 | `"水"` |
| `molecular_formula` | string | 是 | 分子式 | `"H2O"` |
| `smiles` | string | 是 | SMILES 表示 | `"O"` |
| `stock_in_quantity` | number | 是 | 入库数量 | `10` |
| `unit` | string | 是 | 单位(字符串,见下表) | `"mL"` |
| `supplier` | string | 否 | 供应商名称 | `"国药集团"` |
| `production_date` | string | 否 | 生产日期ISO 8601 | `"2025-11-18T00:00:00Z"` |
| `expiry_date` | string | 否 | 过期日期ISO 8601 | `"2026-11-18T00:00:00Z"` |
### unit 单位值
| 值 | 单位 |
|------|------|
| `"mL"` | 毫升 |
| `"L"` | 升 |
| `"g"` | 克 |
| `"kg"` | 千克 |
| `"瓶"` | 瓶 |
> 根据试剂状态选择:液体用 `"mL"` / `"L"`,固体用 `"g"` / `"kg"`。
---
## 批量录入策略
### 方式一:用户提供 JSON 数组
用户一次性给出多条试剂数据:
```json
[
{"cas": "7732-18-3", "name": "水", "molecular_formula": "H2O", "smiles": "O", "stock_in_quantity": 10, "unit": "mL"},
{"cas": "64-17-5", "name": "乙醇", "molecular_formula": "C2H6O", "smiles": "CCO", "stock_in_quantity": 5, "unit": "L"}
]
```
Agent 自动为每条补充 `lab_uuid``production_date``expiry_date` 等字段后逐条提交。
Agent 循环调用 API #2 逐条录入,每条记录一次 API 调用。
### 方式二:用户逐个描述
用户口头描述试剂(如「帮我录入 500mL 的无水乙醇Sigma 的」agent 自行补全字段:
1. 根据名称查找 CAS 号、分子式、SMILES参考下方速查表或自行推断
2. 构建完整的请求体
3. 向用户确认后提交
### 方式三:从 CSV/表格批量导入
用户提供 CSV 或表格文件路径agent 读取并解析:
```bash
# 期望的 CSV 格式(首行为表头)
cas,name,molecular_formula,smiles,stock_in_quantity,unit,supplier,production_date,expiry_date
7732-18-3,水,H2O,O,10,mL,农夫山泉,2025-11-18T00:00:00Z,2026-11-18T00:00:00Z
```
### 执行与汇报
每次 API 调用后:
1. 检查返回 `code`0 = 成功)
2. 记录成功/失败数量
3. 全部完成后汇总:「共录入 N 条试剂,成功 X 条,失败 Y 条」
4. 如有失败,列出失败的试剂名称和错误信息
---
## 常见试剂速查表
| 名称 | CAS | 分子式 | SMILES |
|------|-----|--------|--------|
| 水 | 7732-18-3 | H2O | O |
| 乙醇 | 64-17-5 | C2H6O | CCO |
| 甲醇 | 67-56-1 | CH4O | CO |
| 丙酮 | 67-64-1 | C3H6O | CC(C)=O |
| 二甲基亚砜(DMSO) | 67-68-5 | C2H6OS | CS(C)=O |
| 乙酸乙酯 | 141-78-6 | C4H8O2 | CCOC(C)=O |
| 二氯甲烷 | 75-09-2 | CH2Cl2 | ClCCl |
| 四氢呋喃(THF) | 109-99-9 | C4H8O | C1CCOC1 |
| N,N-二甲基甲酰胺(DMF) | 68-12-2 | C3H7NO | CN(C)C=O |
| 氯仿 | 67-66-3 | CHCl3 | ClC(Cl)Cl |
| 乙腈 | 75-05-8 | C2H3N | CC#N |
| 甲苯 | 108-88-3 | C7H8 | Cc1ccccc1 |
| 正己烷 | 110-54-3 | C6H14 | CCCCCC |
| 异丙醇 | 67-63-0 | C3H8O | CC(C)O |
| 盐酸 | 7647-01-0 | HCl | Cl |
| 硫酸 | 7664-93-9 | H2SO4 | OS(O)(=O)=O |
| 氢氧化钠 | 1310-73-2 | NaOH | [Na]O |
| 碳酸钠 | 497-19-8 | Na2CO3 | [Na]OC([O-])=O.[Na+] |
| 氯化钠 | 7647-14-5 | NaCl | [Na]Cl |
| 乙二胺四乙酸(EDTA) | 60-00-4 | C10H16N2O8 | OC(=O)CN(CCN(CC(O)=O)CC(O)=O)CC(O)=O |
> 此表仅供快速参考。对于不在表中的试剂agent 应根据化学知识推断或提示用户补充。
---
## 完整工作流 Checklist
```
Task Progress:
- [ ] Step 1: 确认 ak/sk → 生成 AUTH token
- [ ] Step 2: 确认 --addr → 设置 BASE URL
- [ ] Step 3: GET /edge/lab/info → 获取 lab_uuid
- [ ] Step 4: 收集试剂信息(用户提供列表/逐个描述/CSV文件
- [ ] Step 5: 补全缺失字段CAS、分子式、SMILES 等)
- [ ] Step 6: 向用户确认待录入的试剂列表
- [ ] Step 7: 循环调用 POST /lab/reagent 逐条录入(每条需含 lab_uuid
- [ ] Step 8: 汇总结果(成功/失败数量及详情)
```
---
## 完整示例
用户说:「帮我录入 3 种试剂500mL 无水乙醇、1kg 氯化钠、2L 去离子水」
Agent 构建的请求序列:
```json
// 第 1 条
{"lab_uuid": "8511c672-...", "cas": "64-17-5", "name": "无水乙醇", "molecular_formula": "C2H6O", "smiles": "CCO", "stock_in_quantity": 500, "unit": "mL", "supplier": "国药集团", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
// 第 2 条
{"lab_uuid": "8511c672-...", "cas": "7647-14-5", "name": "氯化钠", "molecular_formula": "NaCl", "smiles": "[Na]Cl", "stock_in_quantity": 1, "unit": "kg", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
// 第 3 条
{"lab_uuid": "8511c672-...", "cas": "7732-18-3", "name": "去离子水", "molecular_formula": "H2O", "smiles": "O", "stock_in_quantity": 2, "unit": "L", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
```

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@@ -0,0 +1,325 @@
---
name: batch-submit-experiment
description: Batch submit experiments (notebooks) to Uni-Lab platform — list workflows, generate node_params from registry schemas, submit multiple rounds, check notebook status. Use when the user wants to submit experiments, create notebooks, batch run workflows, check experiment status, or mentions 提交实验/批量实验/notebook/实验轮次/实验状态.
---
# 批量提交实验指南
通过云端 API 批量提交实验notebook支持多轮实验参数配置。根据 workflow 模板详情和本地设备注册表自动生成 `node_params` 模板。
## 前置条件(缺一不可)
使用本指南前,**必须**先确认以下信息。如果缺少任何一项,**立即向用户询问并终止**,等补齐后再继续。
### 1. ak / sk → AUTH
询问用户的启动参数,从 `--ak` `--sk` 或 config.py 中获取。
生成 AUTH token任选一种方式
```bash
# 方式一Python 一行生成
python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
# 方式二:手动计算
# base64(ak:sk) → Authorization: Lab <token>
```
### 2. --addr → BASE URL
| `--addr` 值 | BASE |
|-------------|------|
| `test` | `https://uni-lab.test.bohrium.com` |
| `uat` | `https://uni-lab.uat.bohrium.com` |
| `local` | `http://127.0.0.1:48197` |
| 不传(默认) | `https://uni-lab.bohrium.com` |
确认后设置:
```bash
BASE="<根据 addr 确定的 URL>"
AUTH="Authorization: Lab <上面命令输出的 token>"
```
### 3. req_device_registry_upload.json设备注册表
**批量提交实验时需要本地注册表来解析 workflow 节点的参数 schema。**
按优先级搜索:
```
<workspace 根目录>/unilabos_data/req_device_registry_upload.json
<workspace 根目录>/req_device_registry_upload.json
```
也可直接 Glob 搜索:`**/req_device_registry_upload.json`
找到后**检查文件修改时间**并告知用户。超过 1 天提醒用户是否需要重新启动 `unilab`
**如果文件不存在** → 告知用户先运行 `unilab` 启动命令,等注册表生成后再执行。可跳过此步,但将无法自动生成参数模板,需要用户手动填写 `param`
### 4. workflow_uuid目标工作流
用户需要提供要提交的 workflow UUID。如果用户不确定通过 API #3 列出可用 workflow 供选择。
**四项全部就绪后才可开始。**
## Session State
在整个对话过程中agent 需要记住以下状态,避免重复询问用户:
- `lab_uuid` — 实验室 UUID首次通过 API #1 自动获取,**不需要问用户**
- `project_uuid` — 项目 UUID通过 API #2 列出项目列表,**让用户选择**
- `workflow_uuid` — 工作流 UUID用户提供或从列表选择
- `workflow_nodes` — workflow 中各 action 节点的 uuid、设备 ID、动作名从 API #4 获取)
## 请求约定
所有请求使用 `curl -s`POST 需加 `Content-Type: application/json`
> **Windows 平台**必须使用 `curl.exe`(而非 PowerShell 的 `curl` 别名),示例中的 `curl` 均指 `curl.exe`。
>
> **PowerShell JSON 传参**PowerShell 中 `-d '{"key":"value"}'` 会因引号转义失败。请将 JSON 写入临时文件,用 `-d '@tmp_body.json'`(单引号包裹 `@`,否则会被解析为 splatting 运算符)。
---
## API Endpoints
### 1. 获取实验室信息(自动获取 lab_uuid
```bash
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
```
返回:
```json
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
```
记住 `data.uuid``lab_uuid`
### 2. 列出实验室项目(让用户选择项目)
```bash
curl -s -X GET "$BASE/api/v1/lab/project/list?lab_uuid=$lab_uuid" -H "$AUTH"
```
返回项目列表,展示给用户选择。列出每个项目的 `uuid``name`
用户**必须**选择一个项目,记住 `project_uuid`,后续创建 notebook 时需要提供。
### 3. 列出可用 workflow
```bash
curl -s -X GET "$BASE/api/v1/lab/workflow/workflows?page=1&page_size=20&lab_uuid=$lab_uuid" -H "$AUTH"
```
返回 workflow 列表,展示给用户选择。列出每个 workflow 的 `uuid``name`
### 4. 获取 workflow 模板详情
```bash
curl -s -X GET "$BASE/api/v1/lab/workflow/template/detail/$workflow_uuid" -H "$AUTH"
```
返回 workflow 的完整结构,包含所有 action 节点信息。需要从响应中提取:
- 每个 action 节点的 `node_uuid`
- 每个节点对应的设备 ID`resource_template_name`
- 每个节点的动作名(`node_template_name`
- 每个节点的现有参数(`param`
> **注意**:此 API 返回格式可能因版本不同而有差异。首次调用时,先打印完整响应分析结构,再提取节点信息。常见的节点字段路径为 `data.nodes[]` 或 `data.workflow_nodes[]`。
### 5. 提交实验(创建 notebook
```bash
curl -s -X POST "$BASE/api/v1/lab/notebook" \
-H "$AUTH" -H "Content-Type: application/json" \
-d '<request_body>'
```
请求体结构:
```json
{
"lab_uuid": "<lab_uuid>",
"project_uuid": "<project_uuid>",
"workflow_uuid": "<workflow_uuid>",
"name": "<实验名称>",
"node_params": [
{
"sample_uuids": ["<样品UUID1>", "<样品UUID2>"],
"datas": [
{
"node_uuid": "<workflow中的节点UUID>",
"param": {},
"sample_params": [
{
"container_uuid": "<容器UUID>",
"sample_value": {
"liquid_names": "<液体名称>",
"volumes": 1000
}
}
]
}
]
}
]
}
```
> **注意**`sample_uuids` 必须是 **UUID 数组**`[]uuid.UUID`),不是字符串。无样品时传空数组 `[]`。
### 6. 查询 notebook 状态
提交成功后,使用返回的 notebook UUID 查询执行状态:
```bash
curl -s -X GET "$BASE/api/v1/lab/notebook/status?uuid=$notebook_uuid" -H "$AUTH"
```
提交后应**立即查询一次**状态,确认 notebook 已被正确接收并开始调度。
---
## Notebook 请求体详解
### node_params 结构
`node_params` 是一个数组,**每个元素代表一轮实验**
- 要跑 2 轮 → `node_params` 有 2 个元素
- 要跑 N 轮 → `node_params` 有 N 个元素
### 每轮的字段
| 字段 | 类型 | 说明 |
|------|------|------|
| `sample_uuids` | array\<uuid\> | 该轮实验的样品 UUID 数组,无样品时传 `[]` |
| `datas` | array | 该轮中每个 workflow 节点的参数配置 |
### datas 中每个节点
| 字段 | 类型 | 说明 |
|------|------|------|
| `node_uuid` | string | workflow 模板中的节点 UUID从 API #4 获取) |
| `param` | object | 动作参数(根据本地注册表 schema 填写) |
| `sample_params` | array | 样品相关参数(液体名、体积等) |
### sample_params 中每条
| 字段 | 类型 | 说明 |
|------|------|------|
| `container_uuid` | string | 容器 UUID |
| `sample_value` | object | 样品值,如 `{"liquid_names": "水", "volumes": 1000}` |
---
## 从本地注册表生成 param 模板
### 自动方式 — 运行脚本
```bash
python scripts/gen_notebook_params.py \
--auth <token> \
--base <BASE_URL> \
--workflow-uuid <workflow_uuid> \
[--registry <path/to/req_device_registry_upload.json>] \
[--rounds <轮次数>] \
[--output <输出文件路径>]
```
> 脚本位于本文档同级目录下的 `scripts/gen_notebook_params.py`。
脚本会:
1. 调用 workflow detail API 获取所有 action 节点
2. 读取本地注册表,为每个节点查找对应的 action schema
3. 生成 `notebook_template.json`,包含:
- 完整 `node_params` 骨架
- 每个节点的 param 字段及类型说明
- `_schema_info` 辅助信息(不提交,仅供参考)
### 手动方式
如果脚本不可用或注册表不存在:
1. 调用 API #4 获取 workflow 详情
2. 找到每个 action 节点的 `node_uuid`
3. 在本地注册表中查找对应设备的 `action_value_mappings`
```
resources[].id == <device_id>
→ resources[].class.action_value_mappings.<action_name>.schema.properties.goal.properties
```
4. 将 schema 中的 properties 作为 `param` 的字段模板
5. 按轮次复制 `node_params` 元素,让用户填写每轮的具体值
### 注册表结构参考
```json
{
"resources": [
{
"id": "liquid_handler.prcxi",
"class": {
"module": "unilabos.devices.xxx:ClassName",
"action_value_mappings": {
"transfer_liquid": {
"type": "LiquidHandlerTransfer",
"schema": {
"properties": {
"goal": {
"properties": {
"asp_vols": {"type": "array", "items": {"type": "number"}},
"sources": {"type": "array"}
},
"required": ["asp_vols", "sources"]
}
}
},
"goal_default": {}
}
}
}
}
]
}
```
`param` 填写时,使用 `goal.properties` 中的字段名和类型。
---
## 完整工作流 Checklist
```
Task Progress:
- [ ] Step 1: 确认 ak/sk → 生成 AUTH token
- [ ] Step 2: 确认 --addr → 设置 BASE URL
- [ ] Step 3: GET /edge/lab/info → 获取 lab_uuid
- [ ] Step 4: GET /lab/project/list → 列出项目,让用户选择 → 获取 project_uuid
- [ ] Step 5: 确认 workflow_uuid用户提供或从 GET #3 列表选择)
- [ ] Step 6: GET workflow detail (#4) → 提取各节点 uuid、设备ID、动作名
- [ ] Step 7: 定位本地注册表 req_device_registry_upload.json
- [ ] Step 8: 运行 gen_notebook_params.py 或手动匹配 → 生成 node_params 模板
- [ ] Step 9: 引导用户填写每轮的参数sample_uuids、param、sample_params
- [ ] Step 10: 构建完整请求体(含 project_uuid→ POST /lab/notebook 提交
- [ ] Step 11: 检查返回结果,记录 notebook UUID
- [ ] Step 12: GET /lab/notebook/status → 查询 notebook 状态,确认已调度
```
---
## 常见问题
### Q: workflow 中有多个节点,每轮都要填所有节点的参数吗?
是的。`datas` 数组中需要包含该轮实验涉及的每个 workflow 节点的参数。通常每个 action 节点都需要一条 `datas` 记录。
### Q: 多轮实验的参数完全不同吗?
通常每轮的 `param`(设备动作参数)可能相同或相似,但 `sample_uuids` 和 `sample_params`(样品信息)每轮不同。脚本生成模板时会按轮次复制骨架,用户只需修改差异部分。
### Q: 如何获取 sample_uuids 和 container_uuid
这些 UUID 通常来自实验室的样品管理系统。向用户询问或从资源树API `GET /lab/material/download/$lab_uuid`)中查找。

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@@ -0,0 +1,395 @@
#!/usr/bin/env python3
"""
从 workflow 模板详情 + 本地设备注册表生成 notebook 提交用的 node_params 模板。
用法:
python gen_notebook_params.py --auth <token> --base <url> --workflow-uuid <uuid> [选项]
选项:
--auth <token> Lab tokenbase64(ak:sk) 的结果,不含 "Lab " 前缀)
--base <url> API 基础 URL如 https://uni-lab.test.bohrium.com
--workflow-uuid <uuid> 目标 workflow 的 UUID
--registry <path> 本地注册表文件路径(默认自动搜索)
--rounds <n> 实验轮次数(默认 1
--output <path> 输出模板文件路径(默认 notebook_template.json
--dump-response 打印 workflow detail API 的原始响应(调试用)
示例:
python gen_notebook_params.py \\
--auth YTFmZDlkNGUtxxxx \\
--base https://uni-lab.test.bohrium.com \\
--workflow-uuid abc-123-def \\
--rounds 2
"""
import copy
import json
import os
import sys
from datetime import datetime
from urllib.request import Request, urlopen
from urllib.error import HTTPError, URLError
REGISTRY_FILENAME = "req_device_registry_upload.json"
def find_registry(explicit_path=None):
"""查找本地注册表文件,逻辑同 extract_device_actions.py"""
if explicit_path:
if os.path.isfile(explicit_path):
return explicit_path
if os.path.isdir(explicit_path):
fp = os.path.join(explicit_path, REGISTRY_FILENAME)
if os.path.isfile(fp):
return fp
print(f"警告: 指定的注册表路径不存在: {explicit_path}")
return None
candidates = [
os.path.join("unilabos_data", REGISTRY_FILENAME),
REGISTRY_FILENAME,
]
for c in candidates:
if os.path.isfile(c):
return c
script_dir = os.path.dirname(os.path.abspath(__file__))
workspace_root = os.path.normpath(os.path.join(script_dir, "..", "..", ".."))
for c in candidates:
path = os.path.join(workspace_root, c)
if os.path.isfile(path):
return path
cwd = os.getcwd()
for _ in range(5):
parent = os.path.dirname(cwd)
if parent == cwd:
break
cwd = parent
for c in candidates:
path = os.path.join(cwd, c)
if os.path.isfile(path):
return path
return None
def load_registry(path):
with open(path, "r", encoding="utf-8") as f:
return json.load(f)
def build_registry_index(registry_data):
"""构建 device_id → action_value_mappings 的索引"""
index = {}
for res in registry_data.get("resources", []):
rid = res.get("id", "")
avm = res.get("class", {}).get("action_value_mappings", {})
if rid and avm:
index[rid] = avm
return index
def flatten_goal_schema(action_data):
"""从 action_value_mappings 条目中提取 goal 层的 schema"""
schema = action_data.get("schema", {})
goal_schema = schema.get("properties", {}).get("goal", {})
return goal_schema if goal_schema else schema
def build_param_template(goal_schema):
"""根据 goal schema 生成 param 模板,含类型标注"""
properties = goal_schema.get("properties", {})
required = set(goal_schema.get("required", []))
template = {}
for field_name, field_def in properties.items():
if field_name == "unilabos_device_id":
continue
ftype = field_def.get("type", "any")
default = field_def.get("default")
if default is not None:
template[field_name] = default
elif ftype == "string":
template[field_name] = f"$TODO ({ftype}, {'required' if field_name in required else 'optional'})"
elif ftype == "number" or ftype == "integer":
template[field_name] = 0
elif ftype == "boolean":
template[field_name] = False
elif ftype == "array":
template[field_name] = []
elif ftype == "object":
template[field_name] = {}
else:
template[field_name] = f"$TODO ({ftype})"
return template
def fetch_workflow_detail(base_url, auth_token, workflow_uuid):
"""调用 workflow detail API"""
url = f"{base_url}/api/v1/lab/workflow/template/detail/{workflow_uuid}"
req = Request(url, method="GET")
req.add_header("Authorization", f"Lab {auth_token}")
try:
with urlopen(req, timeout=30) as resp:
return json.loads(resp.read().decode("utf-8"))
except HTTPError as e:
body = e.read().decode("utf-8", errors="replace")
print(f"API 错误 {e.code}: {body}")
return None
except URLError as e:
print(f"网络错误: {e.reason}")
return None
def extract_nodes_from_response(response):
"""
从 workflow detail 响应中提取 action 节点列表。
适配多种可能的响应格式。
返回: [(node_uuid, resource_template_name, node_template_name, existing_param), ...]
"""
data = response.get("data", response)
search_keys = ["nodes", "workflow_nodes", "node_list", "steps"]
nodes_raw = None
for key in search_keys:
if key in data and isinstance(data[key], list):
nodes_raw = data[key]
break
if nodes_raw is None:
if isinstance(data, list):
nodes_raw = data
else:
for v in data.values():
if isinstance(v, list) and len(v) > 0 and isinstance(v[0], dict):
nodes_raw = v
break
if not nodes_raw:
print("警告: 未能从响应中提取节点列表")
print("响应顶层 keys:", list(data.keys()) if isinstance(data, dict) else type(data).__name__)
return []
result = []
for node in nodes_raw:
if not isinstance(node, dict):
continue
node_uuid = (
node.get("uuid")
or node.get("node_uuid")
or node.get("id")
or ""
)
resource_name = (
node.get("resource_template_name")
or node.get("device_id")
or node.get("resource_name")
or node.get("device_name")
or ""
)
template_name = (
node.get("node_template_name")
or node.get("action_name")
or node.get("template_name")
or node.get("action")
or node.get("name")
or ""
)
existing_param = node.get("param", {}) or {}
if node_uuid:
result.append((node_uuid, resource_name, template_name, existing_param))
return result
def generate_template(nodes, registry_index, rounds):
"""生成 notebook 提交模板"""
node_params = []
schema_info = {}
datas_template = []
for node_uuid, resource_name, template_name, existing_param in nodes:
param_template = {}
matched = False
if resource_name and template_name and resource_name in registry_index:
avm = registry_index[resource_name]
if template_name in avm:
goal_schema = flatten_goal_schema(avm[template_name])
param_template = build_param_template(goal_schema)
goal_default = avm[template_name].get("goal_default", {})
if goal_default:
for k, v in goal_default.items():
if k in param_template and v is not None:
param_template[k] = v
matched = True
schema_info[node_uuid] = {
"device_id": resource_name,
"action_name": template_name,
"action_type": avm[template_name].get("type", ""),
"schema_properties": list(goal_schema.get("properties", {}).keys()),
"required": goal_schema.get("required", []),
}
if not matched and existing_param:
param_template = existing_param
if not matched and not existing_param:
schema_info[node_uuid] = {
"device_id": resource_name,
"action_name": template_name,
"warning": "未在本地注册表中找到匹配的 action schema",
}
datas_template.append({
"node_uuid": node_uuid,
"param": param_template,
"sample_params": [
{
"container_uuid": "$TODO_CONTAINER_UUID",
"sample_value": {
"liquid_names": "$TODO_LIQUID_NAME",
"volumes": 0,
},
}
],
})
for i in range(rounds):
node_params.append({
"sample_uuids": f"$TODO_SAMPLE_UUID_ROUND_{i + 1}",
"datas": copy.deepcopy(datas_template),
})
return {
"lab_uuid": "$TODO_LAB_UUID",
"project_uuid": "$TODO_PROJECT_UUID",
"workflow_uuid": "$TODO_WORKFLOW_UUID",
"name": "$TODO_EXPERIMENT_NAME",
"node_params": node_params,
"_schema_info仅参考提交时删除": schema_info,
}
def parse_args(argv):
"""简单的参数解析"""
opts = {
"auth": None,
"base": None,
"workflow_uuid": None,
"registry": None,
"rounds": 1,
"output": "notebook_template.json",
"dump_response": False,
}
i = 0
while i < len(argv):
arg = argv[i]
if arg == "--auth" and i + 1 < len(argv):
opts["auth"] = argv[i + 1]
i += 2
elif arg == "--base" and i + 1 < len(argv):
opts["base"] = argv[i + 1].rstrip("/")
i += 2
elif arg == "--workflow-uuid" and i + 1 < len(argv):
opts["workflow_uuid"] = argv[i + 1]
i += 2
elif arg == "--registry" and i + 1 < len(argv):
opts["registry"] = argv[i + 1]
i += 2
elif arg == "--rounds" and i + 1 < len(argv):
opts["rounds"] = int(argv[i + 1])
i += 2
elif arg == "--output" and i + 1 < len(argv):
opts["output"] = argv[i + 1]
i += 2
elif arg == "--dump-response":
opts["dump_response"] = True
i += 1
else:
print(f"未知参数: {arg}")
i += 1
return opts
def main():
opts = parse_args(sys.argv[1:])
if not opts["auth"] or not opts["base"] or not opts["workflow_uuid"]:
print("用法:")
print(" python gen_notebook_params.py --auth <token> --base <url> --workflow-uuid <uuid> [选项]")
print()
print("必需参数:")
print(" --auth <token> Lab tokenbase64(ak:sk)")
print(" --base <url> API 基础 URL")
print(" --workflow-uuid <uuid> 目标 workflow UUID")
print()
print("可选参数:")
print(" --registry <path> 注册表文件路径(默认自动搜索)")
print(" --rounds <n> 实验轮次数(默认 1")
print(" --output <path> 输出文件路径(默认 notebook_template.json")
print(" --dump-response 打印 API 原始响应")
sys.exit(1)
# 1. 查找并加载本地注册表
registry_path = find_registry(opts["registry"])
registry_index = {}
if registry_path:
mtime = os.path.getmtime(registry_path)
gen_time = datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
print(f"注册表: {registry_path} (生成时间: {gen_time})")
registry_data = load_registry(registry_path)
registry_index = build_registry_index(registry_data)
print(f"已索引 {len(registry_index)} 个设备的 action schemas")
else:
print("警告: 未找到本地注册表,将跳过 param 模板生成")
print(" 提交时需要手动填写各节点的 param 字段")
# 2. 获取 workflow 详情
print(f"\n正在获取 workflow 详情: {opts['workflow_uuid']}")
response = fetch_workflow_detail(opts["base"], opts["auth"], opts["workflow_uuid"])
if not response:
print("错误: 无法获取 workflow 详情")
sys.exit(1)
if opts["dump_response"]:
print("\n=== API 原始响应 ===")
print(json.dumps(response, indent=2, ensure_ascii=False)[:5000])
print("=== 响应结束(截断至 5000 字符) ===\n")
# 3. 提取节点
nodes = extract_nodes_from_response(response)
if not nodes:
print("错误: 未能从 workflow 中提取任何 action 节点")
print("请使用 --dump-response 查看原始响应结构")
sys.exit(1)
print(f"\n找到 {len(nodes)} 个 action 节点:")
print(f" {'节点 UUID':<40} {'设备 ID':<30} {'动作名':<25} {'Schema'}")
print(" " + "-" * 110)
for node_uuid, resource_name, template_name, _ in nodes:
matched = "" if (resource_name in registry_index and
template_name in registry_index.get(resource_name, {})) else ""
print(f" {node_uuid:<40} {resource_name:<30} {template_name:<25} {matched}")
# 4. 生成模板
template = generate_template(nodes, registry_index, opts["rounds"])
template["workflow_uuid"] = opts["workflow_uuid"]
output_path = opts["output"]
with open(output_path, "w", encoding="utf-8") as f:
json.dump(template, f, indent=2, ensure_ascii=False)
print(f"\n模板已写入: {output_path}")
print(f" 轮次数: {opts['rounds']}")
print(f" 节点数/轮: {len(nodes)}")
print()
print("下一步:")
print(" 1. 打开模板文件,将 $TODO 占位符替换为实际值")
print(" 2. 删除 _schema_info 字段(仅供参考)")
print(" 3. 使用 POST /api/v1/lab/notebook 提交")
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,380 @@
---
name: create-device-skill
description: Create a skill for any Uni-Lab device by extracting action schemas from the device registry. Use when the user wants to create a new device skill, add device API documentation, or set up action schemas for a device.
---
# 创建设备 Skill 指南
本 meta-skill 教你如何为任意 Uni-Lab-OS 设备创建完整的 API 操作技能(参考 `unilab-device-api` 的成功案例)。
## 数据源
- **设备注册表**: `unilabos_data/req_device_registry_upload.json`
- **结构**: `{ "resources": [{ "id": "<device_id>", "class": { "module": "<python_module:ClassName>", "action_value_mappings": { ... } } }] }`
- **生成时机**: `unilab` 启动并完成注册表上传后自动生成
- **module 字段**: 格式 `unilabos.devices.xxx.yyy:ClassName`,可转为源码路径 `unilabos/devices/xxx/yyy.py`,阅读源码可了解参数含义和设备行为
## 创建流程
### Step 0 — 收集必备信息(缺一不可,否则询问后终止)
开始前**必须**确认以下 4 项信息全部就绪。如果用户未提供任何一项,**立即询问并终止当前流程**,等用户补齐后再继续。
向用户提问:「请提供你的 unilab 启动参数,我需要以下信息:」
#### 必备项 ①ak / sk认证凭据
来源:启动命令的 `--ak` `--sk` 参数,或 config.py 中的 `ak = "..."` `sk = "..."`
获取后立即生成 AUTH token
```bash
python ./scripts/gen_auth.py <ak> <sk>
# 或从 config.py 提取
python ./scripts/gen_auth.py --config <config.py>
```
认证算法:`base64(ak:sk)``Authorization: Lab <token>`
#### 必备项 ②:--addr目标环境
决定 API 请求发往哪个服务器。从启动命令的 `--addr` 参数获取:
| `--addr` 值 | BASE URL |
|-------------|----------|
| `test` | `https://uni-lab.test.bohrium.com` |
| `uat` | `https://uni-lab.uat.bohrium.com` |
| `local` | `http://127.0.0.1:48197` |
| 不传(默认) | `https://uni-lab.bohrium.com` |
| 其他自定义 URL | 直接使用该 URL |
#### 必备项 ③req_device_registry_upload.json设备注册表
数据文件由 `unilab` 启动时自动生成,需要定位它:
**推断 working_dir**(即 `unilabos_data` 所在目录):
| 条件 | working_dir 取值 |
|------|------------------|
| 传了 `--working_dir` | `<working_dir>/unilabos_data/`(若子目录已存在则直接用) |
| 仅传了 `--config` | `<config 文件所在目录>/unilabos_data/` |
| 都没传 | `<当前工作目录>/unilabos_data/` |
**按优先级搜索文件**
```
<推断的 working_dir>/unilabos_data/req_device_registry_upload.json
<推断的 working_dir>/req_device_registry_upload.json
<workspace 根目录>/unilabos_data/req_device_registry_upload.json
```
也可以直接 Glob 搜索:`**/req_device_registry_upload.json`
找到后**必须检查文件修改时间**并告知用户:「找到注册表文件 `<路径>`,生成于 `<时间>`。请确认这是最近一次启动生成的。」超过 1 天提醒用户是否需要重新启动 `unilab`
**如果文件不存在** → 告知用户先运行 `unilab` 启动命令,等日志出现 `注册表响应数据已保存` 后再执行本流程。**终止。**
#### 必备项 ④:目标设备
用户需要明确要为哪个设备创建 skill。可以是设备名称如「PRCXI 移液站」)或 device_id`liquid_handler.prcxi`)。
如果用户不确定,运行提取脚本列出所有设备供选择:
```bash
python ./scripts/extract_device_actions.py --registry <找到的文件路径>
```
#### 完整示例
用户提供:
```
--ak a1fd9d4e-xxxx-xxxx-xxxx-d9a69c09f0fd
--sk 136ff5c6-xxxx-xxxx-xxxx-a03e301f827b
--addr test
--port 8003
--disable_browser
```
从中提取:
- ✅ ak/sk → 运行 `gen_auth.py` 得到 `AUTH="Authorization: Lab YTFmZDlk..."`
- ✅ addr=test → `BASE=https://uni-lab.test.bohrium.com`
- ✅ 搜索 `unilabos_data/req_device_registry_upload.json` → 找到并确认时间
- ✅ 用户指明目标设备 → 如 `liquid_handler.prcxi`
**四项全部就绪后才进入 Step 1。**
### Step 1 — 列出可用设备
运行提取脚本,列出所有设备及 action 数量和 Python 源码路径,让用户选择:
```bash
# 自动搜索(默认在 unilabos_data/ 和当前目录查找)
python ./scripts/extract_device_actions.py
# 指定注册表文件路径
python ./scripts/extract_device_actions.py --registry <path/to/req_device_registry_upload.json>
```
脚本输出包含每个设备的 **Python 源码路径**(从 `class.module` 转换),可用于后续阅读源码理解参数含义。
### Step 2 — 提取 Action Schema
用户选择设备后,运行提取脚本:
```bash
python ./scripts/extract_device_actions.py [--registry <path>] <device_id> ./skills/<skill-name>/actions/
```
脚本会显示设备的 Python 源码路径和类名,方便阅读源码了解参数含义。
每个 action 生成一个 JSON 文件,包含:
- `type` — 作为 API 调用的 `action_type`
- `schema` — 完整 JSON Schema`properties.goal.properties` 参数定义)
- `goal` — goal 字段映射(含占位符 `$placeholder`
- `goal_default` — 默认值
### Step 3 — 写 action-index.md
按模板为每个 action 写条目:
```markdown
### `<action_name>`
<用途描述(一句话)>
- **Schema**: [`actions/<filename>.json`](actions/<filename>.json)
- **核心参数**: `param1`, `param2`(从 schema.required 获取)
- **可选参数**: `param3`, `param4`
- **占位符字段**: `field`(需填入物料信息,值以 `$` 开头)
```
描述规则:
-`schema.properties` 读参数列表schema 已提升为 goal 内容)
-`schema.required` 区分核心/可选参数
- 按功能分类(移液、枪头、外设等)
- 标注 `placeholder_keys` 中的字段类型:
- `unilabos_resources`**ResourceSlot**,填入 `{id, name, uuid}`id 是路径格式,从资源树取物料节点)
- `unilabos_devices`**DeviceSlot**,填入路径字符串如 `"/host_node"`(从资源树筛选 type=device
- `unilabos_nodes`**NodeSlot**,填入路径字符串如 `"/PRCXI/PRCXI_Deck"`(资源树中任意节点)
- `unilabos_class`**ClassSlot**,填入类名字符串如 `"container"`(从注册表查找)
- `unilabos_formulation`**FormulationSlot**,填入配方数组 `[{well_name, liquids: [{name, volume}]}]`well_name 为目标物料的 name
- array 类型字段 → `[{id, name, uuid}, ...]`
- 特殊:`create_resource``res_id`ResourceSlot可填不存在的路径
### Step 4 — 写 SKILL.md
直接复用 `unilab-device-api` 的 API 模板,修改:
- 设备名称
- Action 数量
- 目录列表
- Session state 中的 `device_name`
- **AUTH 头** — 使用 Step 0 中 `gen_auth.py` 生成的 `Authorization: Lab <token>`(不要硬编码 `Api` 类型的 key
- **Python 源码路径** — 在 SKILL.md 开头注明设备对应的源码文件,方便参考参数含义
- **Slot 字段表** — 列出本设备哪些 action 的哪些字段需要填入 Slot物料/设备/节点/类名)
API 模板结构:
```markdown
## 设备信息
- device_id, Python 源码路径, 设备类名
## 前置条件(缺一不可)
- ak/sk → AUTH, --addr → BASE URL
## 请求约定
- Windows 平台必须用 curl.exe非 PowerShell 的 curl 别名)
## Session State
- lab_uuid通过 GET /edge/lab/info 直接获取,不要问用户), device_name
## API Endpoints
# - #1 GET /edge/lab/info → 直接拿到 lab_uuid
# - #2 创建工作流 POST /lab/workflow/owner → 拼 URL 告知用户
# - #3 创建节点 POST /edge/workflow/node
# body: {workflow_uuid, resource_template_name: "<device_id>", node_template_name: "<action_name>"}
# - #4 删除节点 DELETE /lab/workflow/nodes
# - #5 更新节点参数 PATCH /lab/workflow/node
# - #6 查询节点 handles POST /lab/workflow/node-handles
# body: {node_uuids: ["uuid1","uuid2"]} → 返回各节点的 handle_uuid
# - #7 批量创建边 POST /lab/workflow/edges
# body: {edges: [{source_node_uuid, target_node_uuid, source_handle_uuid, target_handle_uuid}]}
# - #8 启动工作流 POST /lab/workflow/{uuid}/run
# - #9 运行设备单动作 POST /lab/mcp/run/action
# - #10 查询任务状态 GET /lab/mcp/task/{task_uuid}
# - #11 运行工作流单节点 POST /lab/mcp/run/workflow/action
# - #12 获取资源树 GET /lab/material/download/{lab_uuid}
# - #13 获取工作流模板详情 GET /lab/workflow/template/detail/{workflow_uuid}
# 返回 workflow 完整结构data.nodes[] 含每个节点的 uuid、name、param、device_name、handles
## Placeholder Slot 填写规则
- unilabos_resources → ResourceSlot → {"id":"/path/name","name":"name","uuid":"xxx"}
- unilabos_devices → DeviceSlot → "/parent/device" 路径字符串
- unilabos_nodes → NodeSlot → "/parent/node" 路径字符串
- unilabos_class → ClassSlot → "class_name" 字符串
- unilabos_formulation → FormulationSlot → [{well_name, liquids: [{name, volume}]}] 配方数组
- 特例create_resource 的 res_id 允许填不存在的路径
- 列出本设备所有 Slot 字段、类型及含义
## 渐进加载策略
## 完整工作流 Checklist
```
### Step 5 — 验证
检查文件完整性:
- [ ] `SKILL.md` 包含 API endpoint#1 获取 lab_uuid、#2-#7 工作流/节点/边、#8-#11 运行/查询、#12 资源树、#13 工作流模板详情)
- [ ] `SKILL.md` 包含 Placeholder Slot 填写规则ResourceSlot / DeviceSlot / NodeSlot / ClassSlot / FormulationSlot + create_resource 特例)和本设备的 Slot 字段表
- [ ] `action-index.md` 列出所有 action 并有描述
- [ ] `actions/` 目录中每个 action 有对应 JSON 文件
- [ ] JSON 文件包含 `type`, `schema`(已提升为 goal 内容), `goal`, `goal_default`, `placeholder_keys` 字段
- [ ] 描述能让 agent 判断该用哪个 action
## Action JSON 文件结构
```json
{
"type": "LiquidHandlerTransfer", // → API 的 action_type
"goal": { // goal 字段映射
"sources": "sources",
"targets": "targets",
"tip_racks": "tip_racks",
"asp_vols": "asp_vols"
},
"schema": { // ← 直接是 goal 的 schema已提升
"type": "object",
"properties": { // 参数定义(即请求中 goal 的字段)
"sources": { "type": "array", "items": { "type": "object" } },
"targets": { "type": "array", "items": { "type": "object" } },
"asp_vols": { "type": "array", "items": { "type": "number" } }
},
"required": [...],
"_unilabos_placeholder_info": { // ← Slot 类型标记
"sources": "unilabos_resources",
"targets": "unilabos_resources",
"tip_racks": "unilabos_resources"
}
},
"goal_default": { ... }, // 默认值
"placeholder_keys": { // ← 汇总所有 Slot 字段
"sources": "unilabos_resources", // ResourceSlot
"targets": "unilabos_resources",
"tip_racks": "unilabos_resources",
"target_device_id": "unilabos_devices" // DeviceSlot
}
}
```
> **注意**`schema` 已由脚本从原始 `schema.properties.goal` 提升为顶层,直接包含参数定义。
> `schema.properties` 中的字段即为 API 创建节点返回的 `data.param` 中的字段PATCH 更新时直接修改 `param` 即可。
## Placeholder Slot 类型体系
`placeholder_keys` / `_unilabos_placeholder_info` 中有 5 种值,对应不同的填写方式:
| placeholder 值 | Slot 类型 | 填写格式 | 选取范围 |
|---------------|-----------|---------|---------|
| `unilabos_resources` | ResourceSlot | `{"id": "/path/name", "name": "name", "uuid": "xxx"}` | 仅**物料**节点(不含设备) |
| `unilabos_devices` | DeviceSlot | `"/parent/device_name"` | 仅**设备**节点type=device路径字符串 |
| `unilabos_nodes` | NodeSlot | `"/parent/node_name"` | **设备 + 物料**,即所有节点,路径字符串 |
| `unilabos_class` | ClassSlot | `"class_name"` | 注册表中已上报的资源类 name |
| `unilabos_formulation` | FormulationSlot | `[{well_name, liquids: [{name, volume}]}]` | 资源树中物料节点的 **name**,配合液体配方 |
### ResourceSlot`unilabos_resources`
最常见的类型。从资源树中选取**物料**节点(孔板、枪头盒、试剂槽等):
```json
{"id": "/workstation/container1", "name": "container1", "uuid": "ff149a9a-2cb8-419d-8db5-d3ba056fb3c2"}
```
- 单个schema type=object`{"id": "/path/name", "name": "name", "uuid": "xxx"}`
- 数组schema type=array`[{"id": "/path/a", "name": "a", "uuid": "xxx"}, ...]`
- `id` 本身是从 parent 计算的路径格式
- 根据 action 语义选择正确的物料(如 `sources` = 液体来源,`targets` = 目标位置)
> **特例**`create_resource` 的 `res_id` 字段,目标物料可能**尚不存在**,此时直接填写期望的路径(如 `"/workstation/container1"`),不需要 uuid。
### DeviceSlot`unilabos_devices`
填写**设备路径字符串**。从资源树中筛选 type=device 的节点,从 parent 计算路径:
```
"/host_node"
"/bioyond_cell/reaction_station"
```
- 只填路径字符串,不需要 `{id, uuid}` 对象
- 根据 action 语义选择正确的设备(如 `target_device_id` = 目标设备)
### NodeSlot`unilabos_nodes`
范围 = 设备 + 物料。即资源树中**所有节点**都可以选,填写**路径字符串**
```
"/PRCXI/PRCXI_Deck"
```
- 使用场景:当参数既可能指向物料也可能指向设备时(如 `PumpTransferProtocol``from_vessel`/`to_vessel``create_resource``parent`
### ClassSlot`unilabos_class`
填写注册表中已上报的**资源类 name**。从本地 `req_resource_registry_upload.json` 中查找:
```
"container"
```
### FormulationSlot`unilabos_formulation`
描述**液体配方**:向哪些物料容器中加入哪些液体及体积。填写为**对象数组**
```json
[
{
"sample_uuid": "",
"well_name": "YB_PrepBottle_15mL_Carrier_bottle_A1",
"liquids": [
{ "name": "LiPF6", "volume": 0.6 },
{ "name": "DMC", "volume": 1.2 }
]
}
]
```
#### 字段说明
| 字段 | 类型 | 说明 |
|------|------|------|
| `sample_uuid` | string | 样品 UUID无样品时传空字符串 `""` |
| `well_name` | string | 目标物料容器的 **name**(从资源树中取物料节点的 `name` 字段,如瓶子、孔位名称) |
| `liquids` | array | 要加入的液体列表 |
| `liquids[].name` | string | 液体名称(如试剂名、溶剂名) |
| `liquids[].volume` | number | 液体体积(单位由设备决定,通常为 mL |
#### 填写规则
- `well_name` 必须是资源树中已存在的物料节点 `name`(不是 `id` 路径),通过 API #12 获取资源树后筛选
- 每个数组元素代表一个目标容器的配方
- 一个容器可以加入多种液体(`liquids` 数组多条记录)
- 与 ResourceSlot 的区别ResourceSlot 填 `{id, name, uuid}` 指向物料本身FormulationSlot 用 `well_name` 引用物料,并附带液体配方信息
### 通过 API #12 获取资源树
```bash
curl -s -X GET "$BASE/api/v1/lab/material/download/$lab_uuid" -H "$AUTH"
```
注意 `lab_uuid` 在路径中(不是查询参数)。资源树返回所有节点,每个节点包含 `id`(路径格式)、`name``uuid``type``parent` 等字段。填写 Slot 时需根据 placeholder 类型筛选正确的节点。
## 最终目录结构
```
./<skill-name>/
├── SKILL.md # API 端点 + 渐进加载指引
├── action-index.md # 动作索引:描述/用途/核心参数
└── actions/ # 每个 action 的完整 JSON Schema
├── action1.json
├── action2.json
└── ...
```

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@@ -0,0 +1,200 @@
#!/usr/bin/env python3
"""
从 req_device_registry_upload.json 中提取指定设备的 action schema。
用法:
# 列出所有设备及 action 数量(自动搜索注册表文件)
python extract_device_actions.py
# 指定注册表文件路径
python extract_device_actions.py --registry <path/to/req_device_registry_upload.json>
# 提取指定设备的 action 到目录
python extract_device_actions.py <device_id> <output_dir>
python extract_device_actions.py --registry <path> <device_id> <output_dir>
示例:
python extract_device_actions.py --registry unilabos_data/req_device_registry_upload.json
python extract_device_actions.py liquid_handler.prcxi .cursor/skills/unilab-device-api/actions/
"""
import json
import os
import sys
from datetime import datetime
REGISTRY_FILENAME = "req_device_registry_upload.json"
def find_registry(explicit_path=None):
"""
查找 req_device_registry_upload.json 文件。
搜索优先级:
1. 用户通过 --registry 显式指定的路径
2. <cwd>/unilabos_data/req_device_registry_upload.json
3. <cwd>/req_device_registry_upload.json
4. <script所在目录>/../../.. (workspace根) 下的 unilabos_data/
5. 向上逐级搜索父目录(最多 5 层)
"""
if explicit_path:
if os.path.isfile(explicit_path):
return explicit_path
if os.path.isdir(explicit_path):
fp = os.path.join(explicit_path, REGISTRY_FILENAME)
if os.path.isfile(fp):
return fp
print(f"警告: 指定的路径不存在: {explicit_path}")
return None
candidates = [
os.path.join("unilabos_data", REGISTRY_FILENAME),
REGISTRY_FILENAME,
]
for c in candidates:
if os.path.isfile(c):
return c
script_dir = os.path.dirname(os.path.abspath(__file__))
workspace_root = os.path.normpath(os.path.join(script_dir, "..", "..", ".."))
for c in candidates:
path = os.path.join(workspace_root, c)
if os.path.isfile(path):
return path
cwd = os.getcwd()
for _ in range(5):
parent = os.path.dirname(cwd)
if parent == cwd:
break
cwd = parent
for c in candidates:
path = os.path.join(cwd, c)
if os.path.isfile(path):
return path
return None
def load_registry(path):
with open(path, 'r', encoding='utf-8') as f:
return json.load(f)
def list_devices(data):
"""列出所有包含 action_value_mappings 的设备,同时返回 module 路径"""
resources = data.get('resources', [])
devices = []
for res in resources:
rid = res.get('id', '')
cls = res.get('class', {})
avm = cls.get('action_value_mappings', {})
module = cls.get('module', '')
if avm:
devices.append((rid, len(avm), module))
return devices
def flatten_schema_to_goal(action_data):
"""将 schema 中嵌套的 goal 内容提升为顶层 schema去掉 feedback/result 包装"""
schema = action_data.get('schema', {})
goal_schema = schema.get('properties', {}).get('goal', {})
if goal_schema:
action_data = dict(action_data)
action_data['schema'] = goal_schema
return action_data
def extract_actions(data, device_id, output_dir):
"""提取指定设备的 action schema 到独立 JSON 文件"""
resources = data.get('resources', [])
for res in resources:
if res.get('id') == device_id:
cls = res.get('class', {})
module = cls.get('module', '')
avm = cls.get('action_value_mappings', {})
if not avm:
print(f"设备 {device_id} 没有 action_value_mappings")
return []
if module:
py_path = module.split(":")[0].replace(".", "/") + ".py"
class_name = module.split(":")[-1] if ":" in module else ""
print(f"Python 源码: {py_path}")
if class_name:
print(f"设备类: {class_name}")
os.makedirs(output_dir, exist_ok=True)
written = []
for action_name in sorted(avm.keys()):
action_data = flatten_schema_to_goal(avm[action_name])
filename = action_name.replace('-', '_') + '.json'
filepath = os.path.join(output_dir, filename)
with open(filepath, 'w', encoding='utf-8') as f:
json.dump(action_data, f, indent=2, ensure_ascii=False)
written.append(filename)
print(f" {filepath}")
return written
print(f"设备 {device_id} 未找到")
return []
def main():
args = sys.argv[1:]
explicit_registry = None
if "--registry" in args:
idx = args.index("--registry")
if idx + 1 < len(args):
explicit_registry = args[idx + 1]
args = args[:idx] + args[idx + 2:]
else:
print("错误: --registry 需要指定路径")
sys.exit(1)
registry_path = find_registry(explicit_registry)
if not registry_path:
print(f"错误: 找不到 {REGISTRY_FILENAME}")
print()
print("解决方法:")
print(" 1. 先运行 unilab 启动命令,等待注册表生成")
print(" 2. 用 --registry 指定文件路径:")
print(f" python {sys.argv[0]} --registry <path/to/{REGISTRY_FILENAME}>")
print()
print("搜索过的路径:")
for p in [
os.path.join("unilabos_data", REGISTRY_FILENAME),
REGISTRY_FILENAME,
os.path.join("<workspace_root>", "unilabos_data", REGISTRY_FILENAME),
]:
print(f" - {p}")
sys.exit(1)
print(f"注册表: {registry_path}")
mtime = os.path.getmtime(registry_path)
gen_time = datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
size_mb = os.path.getsize(registry_path) / (1024 * 1024)
print(f"生成时间: {gen_time} (文件大小: {size_mb:.1f} MB)")
data = load_registry(registry_path)
if len(args) == 0:
devices = list_devices(data)
print(f"\n找到 {len(devices)} 个设备:")
print(f"{'设备 ID':<50} {'Actions':>7} {'Python 模块'}")
print("-" * 120)
for did, count, module in sorted(devices, key=lambda x: x[0]):
py_path = module.split(":")[0].replace(".", "/") + ".py" if module else ""
print(f"{did:<50} {count:>7} {py_path}")
elif len(args) == 2:
device_id = args[0]
output_dir = args[1]
print(f"\n提取 {device_id} 的 actions 到 {output_dir}/")
written = extract_actions(data, device_id, output_dir)
if written:
print(f"\n共写入 {len(written)} 个 action 文件")
else:
print("用法:")
print(" python extract_device_actions.py [--registry <path>] # 列出设备")
print(" python extract_device_actions.py [--registry <path>] <device_id> <dir> # 提取 actions")
sys.exit(1)
if __name__ == '__main__':
main()

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@@ -0,0 +1,69 @@
#!/usr/bin/env python3
"""
从 ak/sk 生成 UniLab API Authorization header。
算法: base64(ak:sk) → "Authorization: Lab <token>"
用法:
python gen_auth.py <ak> <sk>
python gen_auth.py --config <config.py>
示例:
python gen_auth.py myak mysk
python gen_auth.py --config experiments/config.py
"""
import base64
import re
import sys
def gen_auth(ak: str, sk: str) -> str:
token = base64.b64encode(f"{ak}:{sk}".encode("utf-8")).decode("utf-8")
return token
def extract_from_config(config_path: str) -> tuple:
"""从 config.py 中提取 ak 和 sk"""
with open(config_path, "r", encoding="utf-8") as f:
content = f.read()
ak_match = re.search(r'''ak\s*=\s*["']([^"']+)["']''', content)
sk_match = re.search(r'''sk\s*=\s*["']([^"']+)["']''', content)
if not ak_match or not sk_match:
return None, None
return ak_match.group(1), sk_match.group(1)
def main():
args = sys.argv[1:]
if len(args) == 2 and args[0] == "--config":
ak, sk = extract_from_config(args[1])
if not ak or not sk:
print(f"错误: 在 {args[1]} 中未找到 ak/sk 配置")
print("期望格式: ak = \"xxx\" sk = \"xxx\"")
sys.exit(1)
print(f"配置文件: {args[1]}")
elif len(args) == 2:
ak, sk = args
else:
print("用法:")
print(" python gen_auth.py <ak> <sk>")
print(" python gen_auth.py --config <config.py>")
sys.exit(1)
token = gen_auth(ak, sk)
print(f"ak: {ak}")
print(f"sk: {sk}")
print()
print(f"Authorization header:")
print(f" Authorization: Lab {token}")
print()
print(f"curl 用法:")
print(f' curl -H "Authorization: Lab {token}" ...')
print()
print(f"Shell 变量:")
print(f' AUTH="Authorization: Lab {token}"')
if __name__ == "__main__":
main()

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---
name: submit-agent-result
description: Submit historical experiment results (agent_result) to Uni-Lab notebook — read data files, assemble JSON payload, PUT to cloud API. Use when the user wants to submit experiment results, upload agent results, report experiment data, or mentions agent_result/实验结果/历史记录/notebook结果.
---
# 提交历史实验记录指南
通过云端 API 向已创建的 notebook 提交实验结果数据agent_result。支持从 JSON / CSV 文件读取数据,整合后提交。
## 前置条件(缺一不可)
使用本指南前,**必须**先确认以下信息。如果缺少任何一项,**立即向用户询问并终止**,等补齐后再继续。
### 1. ak / sk → AUTH
询问用户的启动参数,从 `--ak` `--sk` 或 config.py 中获取。
生成 AUTH token
```bash
python -c "import base64,sys; print(base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
```
输出即为 token 值,拼接为 `Authorization: Lab <token>`
### 2. --addr → BASE URL
| `--addr` 值 | BASE |
|-------------|------|
| `test` | `https://uni-lab.test.bohrium.com` |
| `uat` | `https://uni-lab.uat.bohrium.com` |
| `local` | `http://127.0.0.1:48197` |
| 不传(默认) | `https://uni-lab.bohrium.com` |
确认后设置:
```bash
BASE="<根据 addr 确定的 URL>"
AUTH="Authorization: Lab <上面命令输出的 token>"
```
### 3. notebook_uuid**必须询问用户**
**必须主动询问用户**:「请提供要提交结果的 notebook UUID。」
notebook_uuid 来自之前通过「批量提交实验」创建的实验批次,即 `POST /api/v1/lab/notebook` 返回的 `data.uuid`
如果用户不记得,可提示:
- 查看之前的对话记录中创建 notebook 时返回的 UUID
- 或通过平台页面查找对应的 notebook
**绝不能跳过此步骤,没有 notebook_uuid 无法提交。**
### 4. 实验结果数据
用户需要提供实验结果数据,支持以下方式:
| 方式 | 说明 |
|------|------|
| JSON 文件 | 直接作为 `agent_result` 的内容合并 |
| CSV 文件 | 转为 `{"文件名": [行数据...]}` 格式 |
| 手动指定 | 用户直接告知 key-value 数据,由 agent 构建 JSON |
**四项全部就绪后才可开始。**
## Session State
在整个对话过程中agent 需要记住以下状态:
- `lab_uuid` — 实验室 UUID通过 API #1 自动获取,**不需要问用户**
- `notebook_uuid` — 目标 notebook UUID**必须询问用户**
## 请求约定
所有请求使用 `curl -s`PUT 需加 `Content-Type: application/json`
> **Windows 平台**必须使用 `curl.exe`(而非 PowerShell 的 `curl` 别名),示例中的 `curl` 均指 `curl.exe`。
>
> **PowerShell JSON 传参**PowerShell 中 `-d '{"key":"value"}'` 会因引号转义失败。请将 JSON 写入临时文件,用 `-d '@tmp_body.json'`(单引号包裹 `@`,否则 `@` 会被 PowerShell 解析为 splatting 运算符导致报错)。
---
## API Endpoints
### 1. 获取实验室信息(自动获取 lab_uuid
```bash
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"
```
返回:
```json
{"code": 0, "data": {"uuid": "xxx", "name": "实验室名称"}}
```
记住 `data.uuid``lab_uuid`
### 2. 提交实验结果agent_result
```bash
curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
-H "$AUTH" -H "Content-Type: application/json" \
-d '<request_body>'
```
请求体结构:
```json
{
"notebook_uuid": "<notebook_uuid>",
"agent_result": {
"<key1>": "<value1>",
"<key2>": 123,
"<nested_key>": {"a": 1, "b": 2},
"<array_key>": [{"col1": "v1", "col2": "v2"}, ...]
}
}
```
> **注意**HTTP 方法是 **PUT**(不是 POST
#### 必要字段
| 字段 | 类型 | 说明 |
|------|------|------|
| `notebook_uuid` | string (UUID) | 目标 notebook 的 UUID从批量提交实验时获取 |
| `agent_result` | object | 实验结果数据,任意 JSON 对象 |
#### agent_result 内容格式
`agent_result` 接受**任意 JSON 对象**,常见格式:
**简单键值对**
```json
{
"avg_rtt_ms": 12.5,
"status": "success",
"test_count": 5
}
```
**包含嵌套结构**
```json
{
"summary": {"total": 100, "passed": 98, "failed": 2},
"measurements": [
{"sample_id": "S001", "value": 3.14, "unit": "mg/mL"},
{"sample_id": "S002", "value": 2.71, "unit": "mg/mL"}
]
}
```
**从 CSV 文件导入**(脚本自动转换):
```json
{
"experiment_data": [
{"温度": 25, "压力": 101.3, "产率": 0.85},
{"温度": 30, "压力": 101.3, "产率": 0.91}
]
}
```
---
## 整合脚本
本文档同级目录下的 `scripts/prepare_agent_result.py` 可自动读取文件并构建请求体。
### 用法
```bash
python scripts/prepare_agent_result.py \
--notebook-uuid <uuid> \
--files data1.json data2.csv \
[--auth <token>] \
[--base <BASE_URL>] \
[--submit] \
[--output <output.json>]
```
| 参数 | 必选 | 说明 |
|------|------|------|
| `--notebook-uuid` | 是 | 目标 notebook UUID |
| `--files` | 是 | 输入文件路径支持多个JSON / CSV |
| `--auth` | 提交时必选 | Lab tokenbase64(ak:sk) |
| `--base` | 提交时必选 | API base URL |
| `--submit` | 否 | 加上此标志则直接提交到云端 |
| `--output` | 否 | 输出 JSON 路径(默认 `agent_result_body.json` |
### 文件合并规则
| 文件类型 | 合并方式 |
|----------|----------|
| `.json`dict | 字段直接合并到 `agent_result` 顶层 |
| `.json`list/other | 以文件名为 key 放入 `agent_result` |
| `.csv` | 以文件名(不含扩展名)为 key值为行对象数组 |
多个文件的字段会合并。JSON dict 中的重复 key 后者覆盖前者。
### 示例
```bash
# 仅生成请求体文件(不提交)
python scripts/prepare_agent_result.py \
--notebook-uuid 73c67dca-c8cc-4936-85a0-329106aa7cca \
--files results.json measurements.csv
# 生成并直接提交
python scripts/prepare_agent_result.py \
--notebook-uuid 73c67dca-c8cc-4936-85a0-329106aa7cca \
--files results.json \
--auth YTFmZDlkNGUt... \
--base https://uni-lab.test.bohrium.com \
--submit
```
---
## 手动构建方式
如果不使用脚本,也可手动构建请求体:
1. 将实验结果数据组装为 JSON 对象
2. 写入临时文件:
```json
{
"notebook_uuid": "<uuid>",
"agent_result": { ... }
}
```
3. 用 curl 提交:
```bash
curl -s -X PUT "$BASE/api/v1/lab/notebook/agent-result" \
-H "$AUTH" -H "Content-Type: application/json" \
-d '@tmp_body.json'
```
---
## 完整工作流 Checklist
```
Task Progress:
- [ ] Step 1: 确认 ak/sk → 生成 AUTH token
- [ ] Step 2: 确认 --addr → 设置 BASE URL
- [ ] Step 3: GET /edge/lab/info → 获取 lab_uuid
- [ ] Step 4: **询问用户** notebook_uuid必须不可跳过
- [ ] Step 5: 确认实验结果数据来源(文件路径或手动数据)
- [ ] Step 6: 运行 prepare_agent_result.py 或手动构建请求体
- [ ] Step 7: PUT /lab/notebook/agent-result 提交
- [ ] Step 8: 检查返回结果,确认提交成功
```
---
## 常见问题
### Q: notebook_uuid 从哪里获取?
从之前「批量提交实验」时 `POST /api/v1/lab/notebook` 的返回值 `data.uuid` 获取。也可以在平台 UI 中查找对应的 notebook。
### Q: agent_result 有固定的 schema 吗?
没有严格 schema接受任意 JSON 对象。但建议包含有意义的字段名和结构化数据,方便后续分析。
### Q: 可以多次提交同一个 notebook 的结果吗?
可以,后续提交会覆盖之前的 agent_result。
### Q: 认证方式是 Lab 还是 Api
本指南统一使用 `Authorization: Lab <base64(ak:sk)>` 方式。如果用户有独立的 API Key也可用 `Authorization: Api <key>` 替代。

View File

@@ -0,0 +1,133 @@
"""
读取实验结果文件JSON / CSV整合为 agent_result 请求体并可选提交。
用法:
python prepare_agent_result.py \
--notebook-uuid <uuid> \
--files data1.json data2.csv \
[--auth <Lab token>] \
[--base <BASE_URL>] \
[--submit] \
[--output <output.json>]
支持的输入文件格式:
- .json → 直接作为 dict 合并
- .csv → 转为 {"filename": [row_dict, ...]} 格式
"""
import argparse
import base64
import csv
import json
import os
import sys
from pathlib import Path
from typing import Any, Dict, List
def read_json_file(filepath: str) -> Dict[str, Any]:
with open(filepath, "r", encoding="utf-8") as f:
return json.load(f)
def read_csv_file(filepath: str) -> List[Dict[str, Any]]:
rows = []
with open(filepath, "r", encoding="utf-8-sig") as f:
reader = csv.DictReader(f)
for row in reader:
converted = {}
for k, v in row.items():
try:
converted[k] = int(v)
except (ValueError, TypeError):
try:
converted[k] = float(v)
except (ValueError, TypeError):
converted[k] = v
rows.append(converted)
return rows
def merge_files(filepaths: List[str]) -> Dict[str, Any]:
"""将多个文件合并为一个 agent_result dict"""
merged: Dict[str, Any] = {}
for fp in filepaths:
path = Path(fp)
ext = path.suffix.lower()
key = path.stem
if ext == ".json":
data = read_json_file(fp)
if isinstance(data, dict):
merged.update(data)
else:
merged[key] = data
elif ext == ".csv":
merged[key] = read_csv_file(fp)
else:
print(f"[警告] 不支持的文件格式: {fp},跳过", file=sys.stderr)
return merged
def build_request_body(notebook_uuid: str, agent_result: Dict[str, Any]) -> Dict[str, Any]:
return {
"notebook_uuid": notebook_uuid,
"agent_result": agent_result,
}
def submit(base: str, auth: str, body: Dict[str, Any]) -> Dict[str, Any]:
try:
import requests
except ImportError:
print("[错误] 提交需要 requests 库: pip install requests", file=sys.stderr)
sys.exit(1)
url = f"{base}/api/v1/lab/notebook/agent-result"
headers = {
"Content-Type": "application/json",
"Authorization": f"Lab {auth}",
}
resp = requests.put(url, json=body, headers=headers, timeout=30)
return {"status_code": resp.status_code, "body": resp.json() if resp.headers.get("content-type", "").startswith("application/json") else resp.text}
def main():
parser = argparse.ArgumentParser(description="整合实验结果文件并构建 agent_result 请求体")
parser.add_argument("--notebook-uuid", required=True, help="目标 notebook UUID")
parser.add_argument("--files", nargs="+", required=True, help="输入文件路径JSON / CSV")
parser.add_argument("--auth", help="Lab tokenbase64(ak:sk)")
parser.add_argument("--base", help="API base URL")
parser.add_argument("--submit", action="store_true", help="直接提交到云端")
parser.add_argument("--output", default="agent_result_body.json", help="输出 JSON 文件路径")
args = parser.parse_args()
for fp in args.files:
if not os.path.exists(fp):
print(f"[错误] 文件不存在: {fp}", file=sys.stderr)
sys.exit(1)
agent_result = merge_files(args.files)
body = build_request_body(args.notebook_uuid, agent_result)
with open(args.output, "w", encoding="utf-8") as f:
json.dump(body, f, ensure_ascii=False, indent=2)
print(f"[完成] 请求体已保存: {args.output}")
print(f" notebook_uuid: {args.notebook_uuid}")
print(f" agent_result 字段数: {len(agent_result)}")
print(f" 合并文件数: {len(args.files)}")
if args.submit:
if not args.auth or not args.base:
print("[错误] 提交需要 --auth 和 --base 参数", file=sys.stderr)
sys.exit(1)
print(f"\n[提交] PUT {args.base}/api/v1/lab/notebook/agent-result ...")
result = submit(args.base, args.auth, body)
print(f" HTTP {result['status_code']}")
print(f" 响应: {json.dumps(result['body'], ensure_ascii=False)}")
if __name__ == "__main__":
main()

View File

@@ -1,26 +0,0 @@
.conda
# .github
.idea
# .vscode
output
pylabrobot_repo
recipes
scripts
service
temp
# unilabos/test
# unilabos/app/web
unilabos/device_mesh
unilabos_data
unilabos_msgs
unilabos.egg-info
CONTRIBUTORS
# LICENSE
MANIFEST.in
pyrightconfig.json
# README.md
# README_zh.md
setup.py
setup.cfg
.gitattrubutes
**/__pycache__

19
.github/dependabot.yml vendored Normal file
View File

@@ -0,0 +1,19 @@
version: 2
updates:
# GitHub Actions
- package-ecosystem: "github-actions"
directory: "/"
target-branch: "dev"
schedule:
interval: "weekly"
day: "monday"
time: "06:00"
open-pull-requests-limit: 5
reviewers:
- "msgcenterpy-team"
labels:
- "dependencies"
- "github-actions"
commit-message:
prefix: "ci"
include: "scope"

67
.github/workflows/ci-check.yml vendored Normal file
View File

@@ -0,0 +1,67 @@
name: CI Check
on:
push:
branches: [main, dev]
pull_request:
branches: [main, dev]
jobs:
registry-check:
runs-on: windows-latest
env:
# Fix Unicode encoding issue on Windows runner (cp1252 -> utf-8)
PYTHONIOENCODING: utf-8
PYTHONUTF8: 1
defaults:
run:
shell: cmd
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Setup Miniforge
uses: conda-incubator/setup-miniconda@v3
with:
miniforge-version: latest
use-mamba: true
channels: robostack-staging,conda-forge,uni-lab
channel-priority: flexible
activate-environment: check-env
auto-update-conda: false
show-channel-urls: true
- name: Install ROS dependencies, uv and unilabos-msgs
run: |
echo Installing ROS dependencies...
mamba install -n check-env conda-forge::uv conda-forge::opencv robostack-staging::ros-humble-ros-core robostack-staging::ros-humble-action-msgs robostack-staging::ros-humble-std-msgs robostack-staging::ros-humble-geometry-msgs robostack-staging::ros-humble-control-msgs robostack-staging::ros-humble-nav2-msgs uni-lab::ros-humble-unilabos-msgs robostack-staging::ros-humble-cv-bridge robostack-staging::ros-humble-vision-opencv robostack-staging::ros-humble-tf-transformations robostack-staging::ros-humble-moveit-msgs robostack-staging::ros-humble-tf2-ros robostack-staging::ros-humble-tf2-ros-py conda-forge::transforms3d -c robostack-staging -c conda-forge -c uni-lab -y
- name: Install pip dependencies and unilabos
run: |
call conda activate check-env
echo Installing pip dependencies...
uv pip install -r unilabos/utils/requirements.txt
uv pip install pywinauto git+https://github.com/Xuwznln/pylabrobot.git
uv pip uninstall enum34 || echo enum34 not installed, skipping
uv pip install .
- name: Run check mode (AST registry validation)
run: |
call conda activate check-env
echo Running check mode...
python -m unilabos --check_mode --skip_env_check
- name: Check for uncommitted changes
shell: bash
run: |
if ! git diff --exit-code; then
echo "::error::检测到文件变化!请先在本地运行 'python -m unilabos --complete_registry' 并提交变更"
echo "变化的文件:"
git diff --name-only
exit 1
fi
echo "检查通过:无文件变化"

View File

@@ -13,6 +13,11 @@ on:
required: false
default: 'win-64'
type: string
build_full:
description: '是否构建完整版 unilabos-full (默认构建轻量版 unilabos)'
required: false
default: false
type: boolean
jobs:
build-conda-pack:
@@ -57,7 +62,7 @@ jobs:
echo "should_build=false" >> $GITHUB_OUTPUT
fi
- uses: actions/checkout@v4
- uses: actions/checkout@v6
if: steps.should_build.outputs.should_build == 'true'
with:
ref: ${{ github.event.inputs.branch }}
@@ -69,7 +74,7 @@ jobs:
with:
miniforge-version: latest
use-mamba: true
python-version: '3.11.11'
python-version: '3.11.14'
channels: conda-forge,robostack-staging,uni-lab,defaults
channel-priority: flexible
activate-environment: unilab
@@ -81,7 +86,14 @@ jobs:
run: |
echo Installing unilabos and dependencies to unilab environment...
echo Using mamba for faster and more reliable dependency resolution...
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
echo Build full: ${{ github.event.inputs.build_full }}
if "${{ github.event.inputs.build_full }}"=="true" (
echo Installing unilabos-full ^(complete package^)...
mamba install -n unilab uni-lab::unilabos-full conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
) else (
echo Installing unilabos ^(minimal package^)...
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
)
- name: Install conda-pack, unilabos and dependencies (Unix)
if: steps.should_build.outputs.should_build == 'true' && matrix.platform != 'win-64'
@@ -89,7 +101,14 @@ jobs:
run: |
echo "Installing unilabos and dependencies to unilab environment..."
echo "Using mamba for faster and more reliable dependency resolution..."
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
echo "Build full: ${{ github.event.inputs.build_full }}"
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
echo "Installing unilabos-full (complete package)..."
mamba install -n unilab uni-lab::unilabos-full conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
else
echo "Installing unilabos (minimal package)..."
mamba install -n unilab uni-lab::unilabos conda-pack -c uni-lab -c robostack-staging -c conda-forge -y
fi
- name: Get latest ros-humble-unilabos-msgs version (Windows)
if: steps.should_build.outputs.should_build == 'true' && matrix.platform == 'win-64'
@@ -293,7 +312,7 @@ jobs:
- name: Upload distribution package
if: steps.should_build.outputs.should_build == 'true'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v6
with:
name: unilab-pack-${{ matrix.platform }}-${{ github.event.inputs.branch }}
path: dist-package/
@@ -308,7 +327,12 @@ jobs:
echo ==========================================
echo Platform: ${{ matrix.platform }}
echo Branch: ${{ github.event.inputs.branch }}
echo Python version: 3.11.11
echo Python version: 3.11.14
if "${{ github.event.inputs.build_full }}"=="true" (
echo Package: unilabos-full ^(complete^)
) else (
echo Package: unilabos ^(minimal^)
)
echo.
echo Distribution package contents:
dir dist-package
@@ -328,7 +352,12 @@ jobs:
echo "=========================================="
echo "Platform: ${{ matrix.platform }}"
echo "Branch: ${{ github.event.inputs.branch }}"
echo "Python version: 3.11.11"
echo "Python version: 3.11.14"
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
echo "Package: unilabos-full (complete)"
else
echo "Package: unilabos (minimal)"
fi
echo ""
echo "Distribution package contents:"
ls -lh dist-package/

View File

@@ -1,10 +1,12 @@
name: Deploy Docs
on:
push:
branches: [main]
pull_request:
# 在 CI Check 成功后自动触发(仅 main 分支)
workflow_run:
workflows: ["CI Check"]
types: [completed]
branches: [main]
# 手动触发
workflow_dispatch:
inputs:
branch:
@@ -33,12 +35,19 @@ concurrency:
jobs:
# Build documentation
build:
# 只在以下情况运行:
# 1. workflow_run 触发且 CI Check 成功
# 2. 手动触发
if: |
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'workflow_run' && github.event.workflow_run.conclusion == 'success')
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
uses: actions/checkout@v6
with:
ref: ${{ github.event.inputs.branch || github.ref }}
# workflow_run 时使用触发工作流的分支,手动触发时使用输入的分支
ref: ${{ github.event.workflow_run.head_branch || github.event.inputs.branch || github.ref }}
fetch-depth: 0
- name: Setup Miniforge (with mamba)
@@ -46,7 +55,7 @@ jobs:
with:
miniforge-version: latest
use-mamba: true
python-version: '3.11.11'
python-version: '3.11.14'
channels: conda-forge,robostack-staging,uni-lab,defaults
channel-priority: flexible
activate-environment: unilab
@@ -75,8 +84,10 @@ jobs:
- name: Setup Pages
id: pages
uses: actions/configure-pages@v4
if: github.ref == 'refs/heads/main' || (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
uses: actions/configure-pages@v5
if: |
github.event.workflow_run.head_branch == 'main' ||
(github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
- name: Build Sphinx documentation
run: |
@@ -94,14 +105,18 @@ jobs:
test -f docs/_build/html/index.html && echo "✓ index.html exists" || echo "✗ index.html missing"
- name: Upload build artifacts
uses: actions/upload-pages-artifact@v3
if: github.ref == 'refs/heads/main' || (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
uses: actions/upload-pages-artifact@v4
if: |
github.event.workflow_run.head_branch == 'main' ||
(github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
with:
path: docs/_build/html
# Deploy to GitHub Pages
deploy:
if: github.ref == 'refs/heads/main' || (github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
if: |
github.event.workflow_run.head_branch == 'main' ||
(github.event_name == 'workflow_dispatch' && github.event.inputs.deploy_to_pages == 'true')
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}

View File

@@ -1,11 +1,16 @@
name: Multi-Platform Conda Build
on:
# 在 CI Check 工作流完成后触发(仅限 main/dev 分支)
workflow_run:
workflows: ["CI Check"]
types:
- completed
branches: [main, dev]
# 支持 tag 推送(不依赖 CI Check
push:
branches: [main, dev]
tags: ['v*']
pull_request:
branches: [main, dev]
# 手动触发
workflow_dispatch:
inputs:
platforms:
@@ -17,9 +22,37 @@ on:
required: false
default: false
type: boolean
skip_ci_check:
description: '跳过等待 CI Check (手动触发时可选)'
required: false
default: false
type: boolean
jobs:
# 等待 CI Check 完成的 job (仅用于 workflow_run 触发)
wait-for-ci:
runs-on: ubuntu-latest
if: github.event_name == 'workflow_run'
outputs:
should_continue: ${{ steps.check.outputs.should_continue }}
steps:
- name: Check CI status
id: check
run: |
if [[ "${{ github.event.workflow_run.conclusion }}" == "success" ]]; then
echo "should_continue=true" >> $GITHUB_OUTPUT
echo "CI Check passed, proceeding with build"
else
echo "should_continue=false" >> $GITHUB_OUTPUT
echo "CI Check did not succeed (status: ${{ github.event.workflow_run.conclusion }}), skipping build"
fi
build:
needs: [wait-for-ci]
# 运行条件workflow_run 触发且 CI 成功,或者其他触发方式
if: |
always() &&
(needs.wait-for-ci.result == 'skipped' || needs.wait-for-ci.outputs.should_continue == 'true')
strategy:
fail-fast: false
matrix:
@@ -44,8 +77,10 @@ jobs:
shell: bash -l {0}
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
with:
# 如果是 workflow_run 触发,使用触发 CI Check 的 commit
ref: ${{ github.event.workflow_run.head_sha || github.ref }}
fetch-depth: 0
- name: Check if platform should be built
@@ -69,7 +104,6 @@ jobs:
channels: conda-forge,robostack-staging,defaults
channel-priority: strict
activate-environment: build-env
auto-activate-base: false
auto-update-conda: false
show-channel-urls: true
@@ -115,7 +149,7 @@ jobs:
- name: Upload conda package artifacts
if: steps.should_build.outputs.should_build == 'true'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v6
with:
name: conda-package-${{ matrix.platform }}
path: conda-packages-temp

View File

@@ -1,25 +1,62 @@
name: UniLabOS Conda Build
on:
# 在 CI Check 成功后自动触发
workflow_run:
workflows: ["CI Check"]
types: [completed]
branches: [main, dev]
# 标签推送时直接触发(发布版本)
push:
branches: [main, dev]
tags: ['v*']
pull_request:
branches: [main, dev]
# 手动触发
workflow_dispatch:
inputs:
platforms:
description: '选择构建平台 (逗号分隔): linux-64, osx-64, osx-arm64, win-64'
required: false
default: 'linux-64'
build_full:
description: '是否构建 unilabos-full 完整包 (默认只构建 unilabos 基础包)'
required: false
default: false
type: boolean
upload_to_anaconda:
description: '是否上传到Anaconda.org'
required: false
default: false
type: boolean
skip_ci_check:
description: '跳过等待 CI Check (手动触发时可选)'
required: false
default: false
type: boolean
jobs:
# 等待 CI Check 完成的 job (仅用于 workflow_run 触发)
wait-for-ci:
runs-on: ubuntu-latest
if: github.event_name == 'workflow_run'
outputs:
should_continue: ${{ steps.check.outputs.should_continue }}
steps:
- name: Check CI status
id: check
run: |
if [[ "${{ github.event.workflow_run.conclusion }}" == "success" ]]; then
echo "should_continue=true" >> $GITHUB_OUTPUT
echo "CI Check passed, proceeding with build"
else
echo "should_continue=false" >> $GITHUB_OUTPUT
echo "CI Check did not succeed (status: ${{ github.event.workflow_run.conclusion }}), skipping build"
fi
build:
needs: [wait-for-ci]
# 运行条件workflow_run 触发且 CI 成功,或者其他触发方式
if: |
always() &&
(needs.wait-for-ci.result == 'skipped' || needs.wait-for-ci.outputs.should_continue == 'true')
strategy:
fail-fast: false
matrix:
@@ -40,8 +77,10 @@ jobs:
shell: bash -l {0}
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
with:
# 如果是 workflow_run 触发,使用触发 CI Check 的 commit
ref: ${{ github.event.workflow_run.head_sha || github.ref }}
fetch-depth: 0
- name: Check if platform should be built
@@ -65,7 +104,6 @@ jobs:
channels: conda-forge,robostack-staging,uni-lab,defaults
channel-priority: strict
activate-environment: build-env
auto-activate-base: false
auto-update-conda: false
show-channel-urls: true
@@ -81,12 +119,61 @@ jobs:
conda list | grep -E "(rattler-build|anaconda-client)"
echo "Platform: ${{ matrix.platform }}"
echo "OS: ${{ matrix.os }}"
echo "Building UniLabOS package"
echo "Build full package: ${{ github.event.inputs.build_full || 'false' }}"
echo "Building packages:"
echo " - unilabos-env (environment dependencies)"
echo " - unilabos (with pip package)"
if [[ "${{ github.event.inputs.build_full }}" == "true" ]]; then
echo " - unilabos-full (complete package)"
fi
- name: Build conda package
- name: Build unilabos-env (conda environment only, noarch)
if: steps.should_build.outputs.should_build == 'true'
run: |
rattler-build build -r .conda/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge
echo "Building unilabos-env (conda environment dependencies)..."
rattler-build build -r .conda/environment/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge
- name: Upload unilabos-env to Anaconda.org (if enabled)
if: steps.should_build.outputs.should_build == 'true' && github.event.inputs.upload_to_anaconda == 'true'
run: |
echo "Uploading unilabos-env to uni-lab organization..."
for package in $(find ./output -name "unilabos-env*.conda"); do
anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
done
- name: Build unilabos (with pip package)
if: steps.should_build.outputs.should_build == 'true'
run: |
echo "Building unilabos package..."
# 如果已上传到 Anaconda从 uni-lab channel 获取 unilabos-env否则从本地 output 获取
rattler-build build -r .conda/base/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output
- name: Upload unilabos to Anaconda.org (if enabled)
if: steps.should_build.outputs.should_build == 'true' && github.event.inputs.upload_to_anaconda == 'true'
run: |
echo "Uploading unilabos to uni-lab organization..."
for package in $(find ./output -name "unilabos-0*.conda" -o -name "unilabos-[0-9]*.conda"); do
anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
done
- name: Build unilabos-full - Only when explicitly requested
if: |
steps.should_build.outputs.should_build == 'true' &&
github.event.inputs.build_full == 'true'
run: |
echo "Building unilabos-full package on ${{ matrix.platform }}..."
rattler-build build -r .conda/full/recipe.yaml -c uni-lab -c robostack-staging -c conda-forge --channel ./output
- name: Upload unilabos-full to Anaconda.org (if enabled)
if: |
steps.should_build.outputs.should_build == 'true' &&
github.event.inputs.build_full == 'true' &&
github.event.inputs.upload_to_anaconda == 'true'
run: |
echo "Uploading unilabos-full to uni-lab organization..."
for package in $(find ./output -name "unilabos-full*.conda"); do
anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
done
- name: List built packages
if: steps.should_build.outputs.should_build == 'true'
@@ -108,17 +195,9 @@ jobs:
- name: Upload conda package artifacts
if: steps.should_build.outputs.should_build == 'true'
uses: actions/upload-artifact@v4
uses: actions/upload-artifact@v6
with:
name: conda-package-unilabos-${{ matrix.platform }}
path: conda-packages-temp
if-no-files-found: warn
retention-days: 30
- name: Upload to Anaconda.org (uni-lab organization)
if: github.event.inputs.upload_to_anaconda == 'true'
run: |
for package in $(find ./output -name "*.conda"); do
echo "Uploading $package to uni-lab organization..."
anaconda -t ${{ secrets.ANACONDA_API_TOKEN }} upload --user uni-lab --force "$package"
done

2
.gitignore vendored
View File

@@ -4,6 +4,8 @@ temp/
output/
unilabos_data/
pyrightconfig.json
.cursorignore
device_package*/
## Python
# Byte-compiled / optimized / DLL files

87
AGENTS.md Normal file
View File

@@ -0,0 +1,87 @@
# AGENTS.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Also follow the monorepo-level rules in `../AGENTS.md`.
## Build & Development
```bash
# Install in editable mode (requires mamba env with python 3.11)
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# Run with a device graph
unilab --graph <graph.json> --config <config.py> --backend ros
unilab --graph <graph.json> --config <config.py> --backend simple # no ROS2 needed
# Common CLI flags
unilab --app_bridges websocket fastapi # communication bridges
unilab --test_mode # simulate hardware, no real execution
unilab --check_mode # CI validation of registry imports
unilab --skip_env_check # skip auto-install of dependencies
unilab --visual rviz|web|disable # visualization mode
unilab --is_slave # run as slave node
# Workflow upload subcommand
unilab workflow_upload -f <workflow.json> -n <name> --tags tag1 tag2
# Tests
pytest tests/ # all tests
pytest tests/resources/test_resourcetreeset.py # single test file
pytest tests/resources/test_resourcetreeset.py::TestClassName::test_method # single test
```
## Architecture
### Startup Flow
`unilab` CLI → `unilabos/app/main.py:main()` → loads config → builds registry → reads device graph (JSON/GraphML) → starts backend thread (ROS2/simple) → starts FastAPI web server + WebSocket client.
### Core Layers
**Registry** (`unilabos/registry/`): Singleton `Registry` class discovers and catalogs all device types, resource types, and communication devices from YAML definitions. Device types live in `registry/devices/*.yaml`, resources in `registry/resources/`, comms in `registry/device_comms/`. The registry resolves class paths to actual Python classes via `utils/import_manager.py`.
**Resource Tracking** (`unilabos/resources/resource_tracker.py`): Pydantic-based `ResourceDict``ResourceDictInstance``ResourceTreeSet` hierarchy. `ResourceTreeSet` is the canonical in-memory representation of all devices and resources, used throughout the system. Graph I/O is in `resources/graphio.py` (reads JSON/GraphML device topology files into `nx.Graph` + `ResourceTreeSet`).
**Device Drivers** (`unilabos/devices/`): 30+ hardware drivers organized by device type (liquid_handling, hplc, balance, arm, etc.). Each driver is a Python class that gets wrapped by `ros/device_node_wrapper.py:ros2_device_node()` to become a ROS2 node with publishers, subscribers, and action servers.
**ROS2 Layer** (`unilabos/ros/`): `device_node_wrapper.py` dynamically wraps any device class into `ROS2DeviceNode` (defined in `ros/nodes/base_device_node.py`). Preset node types in `ros/nodes/presets/` include `host_node`, `controller_node`, `workstation`, `serial_node`, `camera`. Messages use custom `unilabos_msgs` (pre-built, distributed via releases).
**Protocol Compilation** (`unilabos/compile/`): 20+ protocol compilers (add, centrifuge, dissolve, filter, heatchill, stir, pump, etc.) that transform YAML protocol definitions into executable sequences.
**Communication** (`unilabos/device_comms/`): Hardware communication adapters — OPC-UA client, Modbus PLC, RPC, and a universal driver. `app/communication.py` provides a factory pattern for WebSocket client connections to the cloud.
**Web/API** (`unilabos/app/web/`): FastAPI server with REST API (`api.py`), Jinja2 template pages (`pages.py`), and HTTP client for cloud communication (`client.py`). Runs on port 8002 by default.
### Configuration System
- **Config classes** in `unilabos/config/config.py`: `BasicConfig`, `WSConfig`, `HTTPConfig`, `ROSConfig` — all class-level attributes, loaded from Python config files
- Config files are `.py` files with matching class names (see `config/example_config.py`)
- Environment variables override with prefix `UNILABOS_` (e.g., `UNILABOS_BASICCONFIG_PORT=9000`)
- Device topology defined in graph files (JSON with node-link format, or GraphML)
### Key Data Flow
1. Graph file → `graphio.read_node_link_json()``(nx.Graph, ResourceTreeSet, resource_links)`
2. `ResourceTreeSet` + `Registry``initialize_device.initialize_device_from_dict()``ROS2DeviceNode` instances
3. Device nodes communicate via ROS2 topics/actions or direct Python calls (simple backend)
4. Cloud sync via WebSocket (`app/ws_client.py`) and HTTP (`app/web/client.py`)
### Test Data
Example device graphs and experiment configs are in `unilabos/test/experiments/` (not `tests/`). Registry test fixtures in `unilabos/test/registry/`.
## Code Conventions
- Code comments and log messages in simplified Chinese
- Python 3.11+, type hints expected
- Pydantic models for data validation (`resource_tracker.py`)
- Singleton pattern via `@singleton` decorator (`utils/decorator.py`)
- Dynamic class loading via `utils/import_manager.py` — device classes resolved at runtime from registry YAML paths
- CLI argument dashes auto-converted to underscores for consistency
## Licensing
- Framework code: GPL-3.0
- Device drivers (`unilabos/devices/`): DP Technology Proprietary License — do not redistribute

4
CLAUDE.md Normal file
View File

@@ -0,0 +1,4 @@
Please follow the rules defined in:
@AGENTS.md

View File

@@ -1,4 +1,5 @@
recursive-include unilabos/test *
recursive-include unilabos/utils *
recursive-include unilabos/registry *.yaml
recursive-include unilabos/app/web/static *
recursive-include unilabos/app/web/templates *

View File

@@ -31,26 +31,46 @@ Detailed documentation can be found at:
## Quick Start
1. Setup Conda Environment
### 1. Setup Conda Environment
Uni-Lab-OS recommends using `mamba` for environment management:
Uni-Lab-OS recommends using `mamba` for environment management. Choose the package that fits your needs:
| Package | Use Case | Contents |
|---------|----------|----------|
| `unilabos` | **Recommended for most users** | Complete package, ready to use |
| `unilabos-env` | Developers (editable install) | Environment only, install unilabos via pip |
| `unilabos-full` | Simulation/Visualization | unilabos + ROS2 Desktop + Gazebo + MoveIt |
```bash
# Create new environment
mamba create -n unilab python=3.11.11
mamba create -n unilab python=3.11.14
mamba activate unilab
mamba install -n unilab uni-lab::unilabos -c robostack-staging -c conda-forge
# Option A: Standard installation (recommended for most users)
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# Option B: For developers (editable mode development)
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# Then install unilabos and dependencies:
git clone https://github.com/deepmodeling/Uni-Lab-OS.git && cd Uni-Lab-OS
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# Option C: Full installation (simulation/visualization)
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
```
2. Install Dev Uni-Lab-OS
**When to use which?**
- **unilabos**: Standard installation for production deployment and general usage (recommended)
- **unilabos-env**: For developers who need `pip install -e .` editable mode, modify source code
- **unilabos-full**: For simulation (Gazebo), visualization (rviz2), and Jupyter notebooks
### 2. Clone Repository (Optional, for developers)
```bash
# Clone the repository
# Clone the repository (only needed for development or examples)
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
# Install Uni-Lab-OS
pip install .
```
3. Start Uni-Lab System

View File

@@ -31,26 +31,46 @@ Uni-Lab-OS 是一个用于实验室自动化的综合平台,旨在连接和控
## 快速开始
1. 配置 Conda 环境
### 1. 配置 Conda 环境
Uni-Lab-OS 建议使用 `mamba` 管理环境。根据您的操作系统选择适当的环境文件:
Uni-Lab-OS 建议使用 `mamba` 管理环境。根据您的需求选择合适的安装包:
| 安装包 | 适用场景 | 包含内容 |
|--------|----------|----------|
| `unilabos` | **推荐大多数用户** | 完整安装包,开箱即用 |
| `unilabos-env` | 开发者(可编辑安装) | 仅环境依赖,通过 pip 安装 unilabos |
| `unilabos-full` | 仿真/可视化 | unilabos + ROS2 桌面版 + Gazebo + MoveIt |
```bash
# 创建新环境
mamba create -n unilab python=3.11.11
mamba create -n unilab python=3.11.14
mamba activate unilab
mamba install -n unilab uni-lab::unilabos -c robostack-staging -c conda-forge
# 方案 A标准安装推荐大多数用户
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# 方案 B开发者环境可编辑模式开发
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# 然后安装 unilabos 和依赖:
git clone https://github.com/deepmodeling/Uni-Lab-OS.git && cd Uni-Lab-OS
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# 方案 C完整安装仿真/可视化)
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
```
2. 安装开发版 Uni-Lab-OS:
**如何选择?**
- **unilabos**:标准安装,适用于生产部署和日常使用(推荐)
- **unilabos-env**:开发者使用,支持 `pip install -e .` 可编辑模式,可修改源代码
- **unilabos-full**需要仿真Gazebo、可视化rviz2或 Jupyter Notebook
### 2. 克隆仓库(可选,供开发者使用)
```bash
# 克隆仓库
# 克隆仓库(仅开发或查看示例时需要)
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
# 安装 Uni-Lab-OS
pip install .
```
3. 启动 Uni-Lab 系统

View File

@@ -15,6 +15,9 @@ Python 类设备驱动在完成注册表后可以直接在 Uni-Lab 中使用,
**示例:**
```python
from unilabos.registry.decorators import device, topic_config
@device(id="mock_gripper", category=["gripper"], description="Mock Gripper")
class MockGripper:
def __init__(self):
self._position: float = 0.0
@@ -23,19 +26,23 @@ class MockGripper:
self._status = "Idle"
@property
@topic_config() # 添加 @topic_config 才会定时广播
def position(self) -> float:
return self._position
@property
@topic_config()
def velocity(self) -> float:
return self._velocity
@property
@topic_config()
def torque(self) -> float:
return self._torque
# 会被自动识别的设备属性,接入 Uni-Lab 时会定时对外广播
# 使用 @topic_config 装饰的属性,接入 Uni-Lab 时会定时对外广播
@property
@topic_config(period=2.0) # 可自定义发布周期
def status(self) -> str:
return self._status
@@ -149,7 +156,7 @@ my_device: # 设备唯一标识符
系统会自动分析您的 Python 驱动类并生成:
- `status_types`:从 `@property` 装饰的方法自动识别状态属性
- `status_types`:从 `@topic_config` 装饰的 `@property` 方法自动识别状态属性
- `action_value_mappings`:从类方法自动生成动作映射
- `init_param_schema`:从 `__init__` 方法分析初始化参数
- `schema`:前端显示用的属性类型定义
@@ -179,7 +186,9 @@ Uni-Lab 设备驱动是一个 Python 类,需要遵循以下结构:
```python
from typing import Dict, Any
from unilabos.registry.decorators import device, topic_config
@device(id="my_device", category=["general"], description="My Device")
class MyDevice:
"""设备类文档字符串
@@ -198,8 +207,9 @@ class MyDevice:
# 初始化硬件连接
@property
@topic_config() # 必须添加 @topic_config 才会广播
def status(self) -> str:
"""设备状态(会自动广播)"""
"""设备状态(通过 @topic_config 广播)"""
return self._status
def my_action(self, param: float) -> Dict[str, Any]:
@@ -217,34 +227,61 @@ class MyDevice:
## 状态属性 vs 动作方法
### 状态属性(@property
### 状态属性(@property + @topic_config
状态属性会被自动识别并定期广播:
状态属性需要同时使用 `@property``@topic_config` 装饰器才会被识别并定期广播:
```python
from unilabos.registry.decorators import topic_config
@property
@topic_config() # 必须添加,否则不会广播
def temperature(self) -> float:
"""当前温度"""
return self._read_temperature()
@property
@topic_config(period=2.0) # 可自定义发布周期(秒)
def status(self) -> str:
"""设备状态: idle, running, error"""
return self._status
@property
@topic_config(name="ready") # 可自定义发布名称
def is_ready(self) -> bool:
"""设备是否就绪"""
return self._status == "idle"
```
也可以使用普通方法(非 @property)配合 `@topic_config`
```python
@topic_config(period=10.0)
def get_sensor_data(self) -> Dict[str, float]:
"""获取传感器数据get_ 前缀会自动去除,发布名为 sensor_data"""
return {"temp": self._temp, "humidity": self._humidity}
```
**`@topic_config` 参数**:
| 参数 | 类型 | 默认值 | 说明 |
|------|------|--------|------|
| `period` | float | 5.0 | 发布周期(秒) |
| `print_publish` | bool | 节点默认 | 是否打印发布日志 |
| `qos` | int | 10 | QoS 深度 |
| `name` | str | None | 自定义发布名称 |
**发布名称优先级**`@topic_config(name=...)` > `get_` 前缀去除 > 方法名
**特点**:
- 使用`@property`装饰器
- 只读,不能有参数
- 自动添加到注册表的`status_types`
- 必须使用 `@topic_config` 装饰器
- 支持 `@property` 和普通方法
- 添加到注册表的 `status_types`
- 定期发布到 ROS2 topic
> **⚠️ 重要:** 仅有 `@property` 装饰器而没有 `@topic_config` 的属性**不会**被广播。这是一个 Breaking Change。
### 动作方法
动作方法是设备可以执行的操作:
@@ -497,6 +534,7 @@ class LiquidHandler:
self._status = "idle"
@property
@topic_config()
def status(self) -> str:
return self._status
@@ -886,7 +924,52 @@ class MyDevice:
## 最佳实践
### 1. 类型注解
### 1. 使用 `@device` 装饰器标识设备
```python
from unilabos.registry.decorators import device
@device(id="my_device", category=["heating"], description="My Heating Device", icon="heater.webp")
class MyDevice:
...
```
- `id`:设备唯一标识符,用于注册表匹配
- `category`:分类列表,前端用于分组显示
- `description`:设备描述
- `icon`:图标文件名(可选)
### 2. 使用 `@topic_config` 声明需要广播的状态
```python
from unilabos.registry.decorators import topic_config
# ✓ @property + @topic_config → 会广播
@property
@topic_config(period=2.0)
def temperature(self) -> float:
return self._temp
# ✓ 普通方法 + @topic_config → 会广播get_ 前缀自动去除)
@topic_config(period=10.0)
def get_sensor_data(self) -> Dict[str, float]:
return {"temp": self._temp}
# ✓ 使用 name 参数自定义发布名称
@property
@topic_config(name="ready")
def is_ready(self) -> bool:
return self._status == "idle"
# ✗ 仅有 @property没有 @topic_config → 不会广播
@property
def internal_state(self) -> str:
return self._state
```
> **注意:** 与 `@property` 连用时,`@topic_config` 必须放在 `@property` 下面。
### 3. 类型注解
```python
from typing import Dict, Any, Optional, List
@@ -901,7 +984,7 @@ def method(
pass
```
### 2. 文档字符串
### 4. 文档字符串
```python
def method(self, param: float) -> Dict[str, Any]:
@@ -923,7 +1006,7 @@ def method(self, param: float) -> Dict[str, Any]:
pass
```
### 3. 配置验证
### 5. 配置验证
```python
def __init__(self, config: Dict[str, Any]):
@@ -937,7 +1020,7 @@ def __init__(self, config: Dict[str, Any]):
self.baudrate = config['baudrate']
```
### 4. 资源清理
### 6. 资源清理
```python
def __del__(self):
@@ -946,7 +1029,7 @@ def __del__(self):
self.connection.close()
```
### 5. 设计前端友好的返回值
### 7. 设计前端友好的返回值
**记住:返回值会直接显示在 Web 界面**

View File

@@ -422,18 +422,20 @@ placeholder_keys:
### status_types
系统会扫描你的 Python 类,从状态方法property 或 get\_方法自动生成这部分:
系统会扫描你的 Python 类,从带有 `@topic_config` 装饰器的 `@property`方法自动生成这部分:
```yaml
status_types:
current_temperature: float # 从 get_current_temperature() 或 @property current_temperature
is_heating: bool # 从 get_is_heating() 或 @property is_heating
status: str # 从 get_status() 或 @property status
current_temperature: float # 从 @topic_config 装饰的 @property 或方法
is_heating: bool
status: str
```
**注意事项**
- 系统会查找所有 `get_` 开头的方法和 `@property` 装饰的属性
- 仅有带 `@topic_config` 装饰器的 `@property` 或方法才会被识别为状态属性
- 没有 `@topic_config``@property` 不会生成 status_types也不会广播
- `get_` 前缀的方法名会自动去除前缀(如 `get_temperature``temperature`
- 类型会自动转成相应的类型(如 `str``float``bool`
- 如果类型是 `Any``None` 或未知的,默认使用 `String`
@@ -537,11 +539,13 @@ class AdvancedLiquidHandler:
self._temperature = 25.0
@property
@topic_config()
def status(self) -> str:
"""设备状态"""
return self._status
@property
@topic_config()
def temperature(self) -> float:
"""当前温度"""
return self._temperature
@@ -809,21 +813,23 @@ my_temperature_controller:
你的设备类需要符合以下要求:
```python
from unilabos.common.device_base import DeviceBase
from unilabos.registry.decorators import device, topic_config
class MyDevice(DeviceBase):
@device(id="my_device", category=["temperature"], description="My Device")
class MyDevice:
def __init__(self, config):
"""初始化,参数会自动分析到 init_param_schema.config"""
super().__init__(config)
self.port = config.get('port', '/dev/ttyUSB0')
# 状态方法(会自动生成到 status_types
# 状态方法(必须添加 @topic_config 才会生成到 status_types 并广播
@property
@topic_config()
def status(self):
"""返回设备状态"""
return "idle"
@property
@topic_config()
def temperature(self):
"""返回当前温度"""
return 25.0
@@ -1039,7 +1045,34 @@ resource.type # "resource"
### 代码规范
1. **始终使用类型注解**
1. **使用 `@device` 装饰器标识设备类**
```python
from unilabos.registry.decorators import device
@device(id="my_device", category=["heating"], description="My Device")
class MyDevice:
...
```
2. **使用 `@topic_config` 声明广播属性**
```python
from unilabos.registry.decorators import topic_config
# ✓ 需要广播的状态属性
@property
@topic_config(period=2.0)
def temperature(self) -> float:
return self._temp
# ✗ 仅有 @property 不会广播
@property
def internal_counter(self) -> int:
return self._counter
```
3. **始终使用类型注解**
```python
# ✓ 好
@@ -1051,7 +1084,7 @@ def method(self, resource, device):
pass
```
2. **提供有意义的参数名**
4. **提供有意义的参数名**
```python
# ✓ 好 - 清晰的参数名
@@ -1063,7 +1096,7 @@ def transfer(self, r1: ResourceSlot, r2: ResourceSlot):
pass
```
3. **使用 Optional 表示可选参数**
5. **使用 Optional 表示可选参数**
```python
from typing import Optional
@@ -1076,7 +1109,7 @@ def method(
pass
```
4. **添加详细的文档字符串**
6. **添加详细的文档字符串**
```python
def method(
@@ -1096,13 +1129,13 @@ def method(
pass
```
5. **方法命名规范**
7. **方法命名规范**
- 状态方法使用 `@property` 装饰器或 `get_` 前缀
- 状态方法使用 `@property` + `@topic_config` 装饰器,或普通方法 + `@topic_config`
- 动作方法使用动词开头
- 保持命名清晰、一致
6. **完善的错误处理**
8. **完善的错误处理**
- 实现完善的错误处理
- 添加日志记录
- 提供有意义的错误信息

View File

@@ -221,10 +221,10 @@ Laboratory A Laboratory B
```bash
# 实验室A
unilab --ak your_ak --sk your_sk --upload_registry --use_remote_resource
unilab --ak your_ak --sk your_sk --upload_registry
# 实验室B
unilab --ak your_ak --sk your_sk --upload_registry --use_remote_resource
unilab --ak your_ak --sk your_sk --upload_registry
```
---

View File

@@ -31,6 +31,14 @@
详细的安装步骤请参考 [安装指南](installation.md)。
**选择合适的安装包:**
| 安装包 | 适用场景 | 包含组件 |
|--------|----------|----------|
| `unilabos` | **推荐大多数用户**,生产部署 | 完整安装包,开箱即用 |
| `unilabos-env` | 开发者(可编辑安装) | 仅环境依赖,通过 pip 安装 unilabos |
| `unilabos-full` | 仿真/可视化 | unilabos + 完整 ROS2 桌面版 + Gazebo + MoveIt |
**关键步骤:**
```bash
@@ -38,15 +46,30 @@
# 下载 Miniforge: https://github.com/conda-forge/miniforge/releases
# 2. 创建 Conda 环境
mamba create -n unilab python=3.11.11
mamba create -n unilab python=3.11.14
# 3. 激活环境
mamba activate unilab
# 4. 安装 Uni-Lab-OS
# 4. 安装 Uni-Lab-OS(选择其一)
# 方案 A标准安装推荐大多数用户
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# 方案 B开发者环境可编辑模式开发
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
pip install -e /path/to/Uni-Lab-OS # 可编辑安装
uv pip install -r unilabos/utils/requirements.txt # 安装 pip 依赖
# 方案 C完整版仿真/可视化)
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
```
**选择建议:**
- **日常使用/生产部署**:使用 `unilabos`(推荐),完整功能,开箱即用
- **开发者**:使用 `unilabos-env` + `pip install -e .` + `uv pip install -r unilabos/utils/requirements.txt`,代码修改立即生效
- **仿真/可视化**:使用 `unilabos-full`,含 Gazebo、rviz2、MoveIt
#### 1.2 验证安装
```bash
@@ -416,6 +439,9 @@ unilab --ak your_ak --sk your_sk -g test/experiments/mock_devices/mock_all.json
1. 访问 Web 界面,进入"仪器耗材"模块
2. 在"仪器设备"区域找到并添加上述设备
3. 在"物料耗材"区域找到并添加容器
4. 在workstation中配置protocol_type包含PumpTransferProtocol
![添加Protocol类型](image/add_protocol.png)
![物料列表](image/material.png)
@@ -426,8 +452,9 @@ unilab --ak your_ak --sk your_sk -g test/experiments/mock_devices/mock_all.json
**操作步骤:**
1. 将两个 `container` 拖拽到 `workstation`
2.`virtual_transfer_pump` 拖拽到 `workstation`
3. 在画布上连接它们(建立父子关系)
2.`virtual_multiway_valve` 拖拽到 `workstation`
3. `virtual_transfer_pump` 拖拽到 `workstation`
4. 在画布上连接它们(建立父子关系)
![设备连接](image/links.png)
@@ -768,7 +795,43 @@ Waiting for host service...
详细的设备驱动编写指南请参考 [添加设备驱动](../developer_guide/add_device.md)。
#### 9.1 为什么需要自定义设备?
#### 9.1 开发环境准备
**推荐使用 `unilabos-env` + `pip install -e .` + `uv pip install`** 进行设备开发:
```bash
# 1. 创建环境并安装 unilabos-envROS2 + conda 依赖 + uv
mamba create -n unilab python=3.11.14
conda activate unilab
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# 2. 克隆代码
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
# 3. 以可编辑模式安装(推荐使用脚本,自动检测中文环境)
python scripts/dev_install.py
# 或手动安装:
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
```
**为什么使用这种方式?**
- `unilabos-env` 提供 ROS2 核心组件和 uv通过 conda 安装,避免编译)
- `unilabos/utils/requirements.txt` 包含所有运行时需要的 pip 依赖
- `dev_install.py` 自动检测中文环境,中文系统自动使用清华镜像
- 使用 `uv` 替代 `pip`,安装速度更快
- 可编辑模式:代码修改**立即生效**,无需重新安装
**如果安装失败或速度太慢**,可以手动执行(使用清华镜像):
```bash
pip install -e . -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
uv pip install -r unilabos/utils/requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
#### 9.2 为什么需要自定义设备?
Uni-Lab-OS 内置了常见设备,但您的实验室可能有特殊设备需要集成:
@@ -777,7 +840,7 @@ Uni-Lab-OS 内置了常见设备,但您的实验室可能有特殊设备需要
- 特殊的实验流程
- 第三方设备集成
#### 9.2 创建 Python 包
#### 9.3 创建 Python 包
为了方便开发和管理,建议为您的实验室创建独立的 Python 包。
@@ -814,7 +877,7 @@ touch my_lab_devices/my_lab_devices/__init__.py
touch my_lab_devices/my_lab_devices/devices/__init__.py
```
#### 9.3 创建 setup.py
#### 9.4 创建 setup.py
```python
# my_lab_devices/setup.py
@@ -845,7 +908,7 @@ setup(
)
```
#### 9.4 开发安装
#### 9.5 开发安装
使用 `-e` 参数进行可编辑安装,这样代码修改后立即生效:
@@ -860,7 +923,7 @@ pip install -e . -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
- 方便调试和测试
- 支持版本控制git
#### 9.5 编写设备驱动
#### 9.6 编写设备驱动
创建设备驱动文件:
@@ -1001,7 +1064,7 @@ class MyPump:
- **返回 Dict**:所有动作方法返回字典类型
- **文档字符串**:详细说明参数和功能
#### 9.6 测试设备驱动
#### 9.7 测试设备驱动
创建简单的测试脚本:

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@@ -13,15 +13,26 @@
- 开发者需要 Git 和基本的 Python 开发知识
- 自定义 msgs 需要 GitHub 账号
## 安装包选择
Uni-Lab-OS 提供三个安装包版本,根据您的需求选择:
| 安装包 | 适用场景 | 包含组件 | 磁盘占用 |
|--------|----------|----------|----------|
| **unilabos** | **推荐大多数用户**,生产部署 | 完整安装包,开箱即用 | ~2-3 GB |
| **unilabos-env** | 开发者环境(可编辑安装) | 仅环境依赖,通过 pip 安装 unilabos | ~2 GB |
| **unilabos-full** | 仿真可视化、完整功能体验 | unilabos + 完整 ROS2 桌面版 + Gazebo + MoveIt | ~8-10 GB |
## 安装方式选择
根据您的使用场景,选择合适的安装方式:
| 安装方式 | 适用人群 | 特点 | 安装时间 |
| ---------------------- | -------------------- | ------------------------------ | ---------------------------- |
| **方式一:一键安装** | 实验室用户、快速体验 | 预打包环境,离线可用,无需配置 | 5-10 分钟 (网络良好的情况下) |
| **方式二:手动安装** | 标准用户、生产环境 | 灵活配置,版本可控 | 10-20 分钟 |
| **方式三:开发者安装** | 开发者、需要修改源码 | 可编辑模式,支持自定义 msgs | 20-30 分钟 |
| 安装方式 | 适用人群 | 推荐安装包 | 特点 | 安装时间 |
| ---------------------- | -------------------- | ----------------- | ------------------------------ | ---------------------------- |
| **方式一:一键安装** | 快速体验、演示 | 预打包环境 | 离线可用,无需配置 | 5-10 分钟 (网络良好的情况下) |
| **方式二:手动安装** | **大多数用户** | `unilabos` | 完整功能,开箱即用 | 10-20 分钟 |
| **方式三:开发者安装** | 开发者、需要修改源码 | `unilabos-env` | 可编辑模式,支持自定义开发 | 20-30 分钟 |
| **仿真/可视化** | 仿真测试、可视化调试 | `unilabos-full` | 含 Gazebo、rviz2、MoveIt | 30-60 分钟 |
---
@@ -144,17 +155,38 @@ bash Miniforge3-$(uname)-$(uname -m).sh
使用以下命令创建 Uni-Lab 专用环境:
```bash
mamba create -n unilab python=3.11.11 # 目前ros2组件依赖版本大多为3.11.11
mamba create -n unilab python=3.11.14 # 目前ros2组件依赖版本大多为3.11.14
mamba activate unilab
mamba install -n unilab uni-lab::unilabos -c robostack-staging -c conda-forge
# 选择安装包(三选一):
# 方案 A标准安装推荐大多数用户
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
# 方案 B开发者环境可编辑模式开发
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# 然后安装 unilabos 和 pip 依赖:
git clone https://github.com/deepmodeling/Uni-Lab-OS.git && cd Uni-Lab-OS
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
# 方案 C完整版含仿真和可视化工具
mamba install uni-lab::unilabos-full -c robostack-staging -c conda-forge
```
**参数说明**:
- `-n unilab`: 创建名为 "unilab" 的环境
- `uni-lab::unilabos`: 从 uni-lab channel 安装 unilabos 包
- `uni-lab::unilabos`: 安装 unilabos 完整包,开箱即用(推荐)
- `uni-lab::unilabos-env`: 仅安装环境依赖,适合开发者使用 `pip install -e .`
- `uni-lab::unilabos-full`: 安装完整包(含 ROS2 Desktop、Gazebo、MoveIt 等)
- `-c robostack-staging -c conda-forge`: 添加额外的软件源
**包选择建议**
- **日常使用/生产部署**:安装 `unilabos`(推荐,完整功能,开箱即用)
- **开发者**:安装 `unilabos-env`,然后使用 `uv pip install -r unilabos/utils/requirements.txt` 安装依赖,再 `pip install -e .` 进行可编辑安装
- **仿真/可视化**:安装 `unilabos-full`Gazebo、rviz2、MoveIt
**如果遇到网络问题**,可以使用清华镜像源加速下载:
```bash
@@ -163,8 +195,14 @@ mamba config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/m
mamba config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
mamba config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
# 然后重新执行安装命令
# 然后重新执行安装命令(推荐标准安装)
mamba create -n unilab uni-lab::unilabos -c robostack-staging
# 或完整版(仿真/可视化)
mamba create -n unilab uni-lab::unilabos-full -c robostack-staging
# pip 安装时使用清华镜像(开发者安装时使用)
uv pip install -r unilabos/utils/requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
### 第三步:激活环境
@@ -203,58 +241,87 @@ cd Uni-Lab-OS
cd Uni-Lab-OS
```
### 第二步:安装基础环境
### 第二步:安装开发环境unilabos-env
**推荐方式**:先通过**方式一(一键安装)**或**方式二(手动安装)**完成基础环境的安装这将包含所有必需的依赖项ROS2、msgs 等)。
#### 选项 A通过一键安装推荐
参考上文"方式一:一键安装",完成基础环境的安装后,激活环境:
**重要**:开发者请使用 `unilabos-env` 包,它专为开发者设计:
- 包含 ROS2 核心组件和消息包ros-humble-ros-core、std-msgs、geometry-msgs 等)
- 包含 transforms3d、cv-bridge、tf2 等 conda 依赖
- 包含 `uv` 工具,用于快速安装 pip 依赖
- **不包含** pip 依赖和 unilabos 包(由 `pip install -e .` 和 `uv pip install` 安装)
```bash
# 创建并激活环境
mamba create -n unilab python=3.11.14
conda activate unilab
# 安装开发者环境包ROS2 + conda 依赖 + uv
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
```
#### 选项 B通过手动安装
### 第三步:安装 pip 依赖和可编辑模式安装
参考上文"方式二:手动安装",创建并安装环境
```bash
mamba create -n unilab python=3.11.11
conda activate unilab
mamba install -n unilab uni-lab::unilabos -c robostack-staging -c conda-forge
```
**说明**:这会安装包括 Python 3.11.11、ROS2 Humble、ros-humble-unilabos-msgs 和所有必需依赖
### 第三步:切换到开发版本
现在你已经有了一个完整可用的 Uni-Lab 环境,接下来将 unilabos 包切换为开发版本:
克隆代码并安装依赖
```bash
# 确保环境已激活
conda activate unilab
# 卸载 pip 安装的 unilabos保留所有 conda 依赖
pip uninstall unilabos -y
# 克隆 dev 分支(如果还未克隆)
cd /path/to/your/workspace
git clone -b dev https://github.com/deepmodeling/Uni-Lab-OS.git
# 或者如果已经克隆,切换到 dev 分支
# 克隆仓库(如果还未克隆
git clone https://github.com/deepmodeling/Uni-Lab-OS.git
cd Uni-Lab-OS
# 切换到 dev 分支(可选)
git checkout dev
git pull
# 以可编辑模式安装开发版 unilabos
pip install -e . -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
**参数说明**
**推荐:使用安装脚本**(自动检测中文环境,使用 uv 加速)
- `-e`: editable mode可编辑模式代码修改立即生效无需重新安装
- `-i`: 使用清华镜像源加速下载
- `pip uninstall unilabos`: 只卸载 pip 安装的 unilabos 包,不影响 conda 安装的其他依赖(如 ROS2、msgs 等)
```bash
# 自动检测中文环境,如果是中文系统则使用清华镜像
python scripts/dev_install.py
# 或者手动指定:
python scripts/dev_install.py --china # 强制使用清华镜像
python scripts/dev_install.py --no-mirror # 强制使用 PyPI
python scripts/dev_install.py --skip-deps # 跳过 pip 依赖安装
python scripts/dev_install.py --use-pip # 使用 pip 而非 uv
```
**手动安装**(如果脚本安装失败或速度太慢):
```bash
# 1. 安装 unilabos可编辑模式
pip install -e .
# 2. 使用 uv 安装 pip 依赖(推荐,速度更快)
uv pip install -r unilabos/utils/requirements.txt
# 国内用户使用清华镜像:
pip install -e . -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
uv pip install -r unilabos/utils/requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
**注意**
- `uv` 已包含在 `unilabos-env` 中,无需单独安装
- `unilabos/utils/requirements.txt` 包含运行 unilabos 所需的所有 pip 依赖
- 部分特殊包(如 pylabrobot会在运行时由 unilabos 自动检测并安装
**为什么使用可编辑模式?**
- `-e` (editable mode):代码修改**立即生效**,无需重新安装
- 适合开发调试:修改代码后直接运行测试
- 与 `unilabos-env` 配合:环境依赖由 conda 管理unilabos 代码由 pip 管理
**验证安装**
```bash
# 检查 unilabos 版本
python -c "import unilabos; print(unilabos.__version__)"
# 检查安装位置(应该指向你的代码目录)
pip show unilabos | grep Location
```
### 第四步:安装或自定义 ros-humble-unilabos-msgs可选
@@ -464,7 +531,45 @@ cd $CONDA_PREFIX/envs/unilab
### 问题 8: 环境很大,有办法减小吗?
**解决方案**: 预打包的环境包含所有依赖,通常较大(压缩后 2-5GB。这是为了确保离线安装和完整功能。如果空间有限考虑使用方式二手动安装只安装需要的组件。
**解决方案**:
1. **使用 `unilabos` 标准版**(推荐大多数用户):
```bash
mamba install uni-lab::unilabos -c robostack-staging -c conda-forge
```
标准版包含完整功能,环境大小约 2-3GB相比完整版的 8-10GB
2. **使用 `unilabos-env` 开发者版**(最小化):
```bash
mamba install uni-lab::unilabos-env -c robostack-staging -c conda-forge
# 然后手动安装依赖
pip install -e .
uv pip install -r unilabos/utils/requirements.txt
```
开发者版只包含环境依赖,体积最小约 2GB。
3. **按需安装额外组件**
如果后续需要特定功能,可以单独安装:
```bash
# 需要 Jupyter
mamba install jupyter jupyros
# 需要可视化
mamba install matplotlib opencv
# 需要仿真(注意:这会安装大量依赖)
mamba install ros-humble-gazebo-ros
```
4. **预打包环境问题**
预打包环境(方式一)包含所有依赖,通常较大(压缩后 2-5GB。这是为了确保离线安装和完整功能。
**包选择建议**
| 需求 | 推荐包 | 预估大小 |
|------|--------|----------|
| 日常使用/生产部署 | `unilabos` | ~2-3 GB |
| 开发调试(可编辑模式) | `unilabos-env` | ~2 GB |
| 仿真/可视化 | `unilabos-full` | ~8-10 GB |
### 问题 9: 如何更新到最新版本?
@@ -511,6 +616,7 @@ mamba update ros-humble-unilabos-msgs -c uni-lab -c robostack-staging -c conda-f
**提示**:
- 生产环境推荐使用方式二(手动安装)的稳定版本
- 开发和测试推荐使用方式三(开发者安装)
- 快速体验和演示推荐使用方式一(一键安装)
- **大多数用户**推荐使用方式二(手动安装)的 `unilabos` 标准版
- **开发者**推荐使用方式三(开发者安装),安装 `unilabos-env` 后使用 `uv pip install -r unilabos/utils/requirements.txt` 安装依赖
- **仿真/可视化**推荐安装 `unilabos-full` 完整版
- **快速体验和演示**推荐使用方式一(一键安装)

View File

@@ -22,7 +22,6 @@ options:
--is_slave Run the backend as slave node (without host privileges).
--slave_no_host Skip waiting for host service in slave mode
--upload_registry Upload registry information when starting unilab
--use_remote_resource Use remote resources when starting unilab
--config CONFIG Configuration file path, supports .py format Python config files
--port PORT Port for web service information page
--disable_browser Disable opening information page on startup
@@ -85,7 +84,7 @@ Uni-Lab 的启动过程分为以下几个阶段:
支持两种方式:
- **本地文件**:使用 `-g` 指定图谱文件(支持 JSON 和 GraphML 格式)
- **远程资源**使用 `--use_remote_resource` 从云端获取
- **远程资源**不指定本地文件即可
### 7. 注册表构建
@@ -196,7 +195,7 @@ unilab --config path/to/your/config.py
unilab --ak your_ak --sk your_sk -g path/to/graph.json --upload_registry
# 使用远程资源启动
unilab --ak your_ak --sk your_sk --use_remote_resource
unilab --ak your_ak --sk your_sk
# 更新注册表
unilab --ak your_ak --sk your_sk --complete_registry

View File

@@ -1,6 +1,6 @@
package:
name: ros-humble-unilabos-msgs
version: 0.10.15
version: 0.10.19
source:
path: ../../unilabos_msgs
target_directory: src
@@ -25,7 +25,7 @@ requirements:
build:
- ${{ compiler('cxx') }}
- ${{ compiler('c') }}
- python ==3.11.11
- python ==3.11.14
- numpy
- if: build_platform != target_platform
then:
@@ -63,14 +63,14 @@ requirements:
- robostack-staging::ros-humble-rosidl-default-generators
- robostack-staging::ros-humble-std-msgs
- robostack-staging::ros-humble-geometry-msgs
- robostack-staging::ros2-distro-mutex=0.6
- robostack-staging::ros2-distro-mutex=0.7
run:
- robostack-staging::ros-humble-action-msgs
- robostack-staging::ros-humble-ros-workspace
- robostack-staging::ros-humble-rosidl-default-runtime
- robostack-staging::ros-humble-std-msgs
- robostack-staging::ros-humble-geometry-msgs
- robostack-staging::ros2-distro-mutex=0.6
- robostack-staging::ros2-distro-mutex=0.7
- if: osx and x86_64
then:
- __osx >=${{ MACOSX_DEPLOYMENT_TARGET|default('10.14') }}

View File

@@ -1,6 +1,6 @@
package:
name: unilabos
version: "0.10.15"
version: "0.10.19"
source:
path: ../..

View File

@@ -85,7 +85,7 @@ Verification:
-------------
The verify_installation.py script will check:
- Python version (3.11.11)
- Python version (3.11.14)
- ROS2 rclpy installation
- UniLabOS installation and dependencies
@@ -104,7 +104,7 @@ Build Information:
Branch: {branch}
Platform: {platform}
Python: 3.11.11
Python: 3.11.14
Date: {build_date}
Troubleshooting:

214
scripts/dev_install.py Normal file
View File

@@ -0,0 +1,214 @@
#!/usr/bin/env python3
"""
Development installation script for UniLabOS.
Auto-detects Chinese locale and uses appropriate mirror.
Usage:
python scripts/dev_install.py
python scripts/dev_install.py --no-mirror # Force no mirror
python scripts/dev_install.py --china # Force China mirror
python scripts/dev_install.py --skip-deps # Skip pip dependencies installation
Flow:
1. pip install -e . (install unilabos in editable mode)
2. Detect Chinese locale
3. Use uv to install pip dependencies from requirements.txt
4. Special packages (like pylabrobot) are handled by environment_check.py at runtime
"""
import locale
import subprocess
import sys
import argparse
from pathlib import Path
# Tsinghua mirror URL
TSINGHUA_MIRROR = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple"
def is_chinese_locale() -> bool:
"""
Detect if system is in Chinese locale.
Same logic as EnvironmentChecker._is_chinese_locale()
"""
try:
lang = locale.getdefaultlocale()[0]
if lang and ("zh" in lang.lower() or "chinese" in lang.lower()):
return True
except Exception:
pass
return False
def run_command(cmd: list, description: str, retry: int = 2) -> bool:
"""Run command with retry support."""
print(f"[INFO] {description}")
print(f"[CMD] {' '.join(cmd)}")
for attempt in range(retry + 1):
try:
result = subprocess.run(cmd, check=True, timeout=600)
print(f"[OK] {description}")
return True
except subprocess.CalledProcessError as e:
if attempt < retry:
print(f"[WARN] Attempt {attempt + 1} failed, retrying...")
else:
print(f"[ERROR] {description} failed: {e}")
return False
except subprocess.TimeoutExpired:
print(f"[ERROR] {description} timed out")
return False
return False
def install_editable(project_root: Path, use_mirror: bool) -> bool:
"""Install unilabos in editable mode using pip."""
cmd = [sys.executable, "-m", "pip", "install", "-e", str(project_root)]
if use_mirror:
cmd.extend(["-i", TSINGHUA_MIRROR])
return run_command(cmd, "Installing unilabos in editable mode")
def install_requirements_uv(requirements_file: Path, use_mirror: bool) -> bool:
"""Install pip dependencies using uv (installed via conda-forge::uv)."""
cmd = ["uv", "pip", "install", "-r", str(requirements_file)]
if use_mirror:
cmd.extend(["-i", TSINGHUA_MIRROR])
return run_command(cmd, "Installing pip dependencies with uv", retry=2)
def install_requirements_pip(requirements_file: Path, use_mirror: bool) -> bool:
"""Fallback: Install pip dependencies using pip."""
cmd = [sys.executable, "-m", "pip", "install", "-r", str(requirements_file)]
if use_mirror:
cmd.extend(["-i", TSINGHUA_MIRROR])
return run_command(cmd, "Installing pip dependencies with pip", retry=2)
def check_uv_available() -> bool:
"""Check if uv is available (installed via conda-forge::uv)."""
try:
subprocess.run(["uv", "--version"], capture_output=True, check=True)
return True
except (subprocess.CalledProcessError, FileNotFoundError):
return False
def main():
parser = argparse.ArgumentParser(description="Development installation script for UniLabOS")
parser.add_argument("--china", action="store_true", help="Force use China mirror (Tsinghua)")
parser.add_argument("--no-mirror", action="store_true", help="Force use default PyPI (no mirror)")
parser.add_argument(
"--skip-deps", action="store_true", help="Skip pip dependencies installation (only install unilabos)"
)
parser.add_argument("--use-pip", action="store_true", help="Use pip instead of uv for dependencies")
args = parser.parse_args()
# Determine project root
script_dir = Path(__file__).parent
project_root = script_dir.parent
requirements_file = project_root / "unilabos" / "utils" / "requirements.txt"
if not (project_root / "setup.py").exists():
print(f"[ERROR] setup.py not found in {project_root}")
sys.exit(1)
print("=" * 60)
print("UniLabOS Development Installation")
print("=" * 60)
print(f"Project root: {project_root}")
print()
# Determine mirror usage based on locale
if args.no_mirror:
use_mirror = False
print("[INFO] Mirror disabled by --no-mirror flag")
elif args.china:
use_mirror = True
print("[INFO] China mirror enabled by --china flag")
else:
use_mirror = is_chinese_locale()
if use_mirror:
print("[INFO] Chinese locale detected, using Tsinghua mirror")
else:
print("[INFO] Non-Chinese locale detected, using default PyPI")
print()
# Step 1: Install unilabos in editable mode
print("[STEP 1] Installing unilabos in editable mode...")
if not install_editable(project_root, use_mirror):
print("[ERROR] Failed to install unilabos")
print()
print("Manual fallback:")
if use_mirror:
print(f" pip install -e {project_root} -i {TSINGHUA_MIRROR}")
else:
print(f" pip install -e {project_root}")
sys.exit(1)
print()
# Step 2: Install pip dependencies
if args.skip_deps:
print("[INFO] Skipping pip dependencies installation (--skip-deps)")
else:
print("[STEP 2] Installing pip dependencies...")
if not requirements_file.exists():
print(f"[WARN] Requirements file not found: {requirements_file}")
print("[INFO] Skipping dependencies installation")
else:
# Try uv first (faster), fallback to pip
if args.use_pip:
print("[INFO] Using pip (--use-pip flag)")
success = install_requirements_pip(requirements_file, use_mirror)
elif check_uv_available():
print("[INFO] Using uv (installed via conda-forge::uv)")
success = install_requirements_uv(requirements_file, use_mirror)
if not success:
print("[WARN] uv failed, falling back to pip...")
success = install_requirements_pip(requirements_file, use_mirror)
else:
print("[WARN] uv not available (should be installed via: mamba install conda-forge::uv)")
print("[INFO] Falling back to pip...")
success = install_requirements_pip(requirements_file, use_mirror)
if not success:
print()
print("[WARN] Failed to install some dependencies automatically.")
print("You can manually install them:")
if use_mirror:
print(f" uv pip install -r {requirements_file} -i {TSINGHUA_MIRROR}")
print(" or:")
print(f" pip install -r {requirements_file} -i {TSINGHUA_MIRROR}")
else:
print(f" uv pip install -r {requirements_file}")
print(" or:")
print(f" pip install -r {requirements_file}")
print()
print("=" * 60)
print("Installation complete!")
print("=" * 60)
print()
print("Note: Some special packages (like pylabrobot) are installed")
print("automatically at runtime by unilabos if needed.")
print()
print("Verify installation:")
print(' python -c "import unilabos; print(unilabos.__version__)"')
print()
print("If you encounter issues, you can manually install dependencies:")
if use_mirror:
print(f" uv pip install -r unilabos/utils/requirements.txt -i {TSINGHUA_MIRROR}")
else:
print(" uv pip install -r unilabos/utils/requirements.txt")
print()
if __name__ == "__main__":
main()

View File

@@ -4,7 +4,7 @@ package_name = 'unilabos'
setup(
name=package_name,
version='0.10.15',
version='0.10.19',
packages=find_packages(),
include_package_data=True,
install_requires=['setuptools'],

213
tests/workflow/test.json Normal file
View File

@@ -0,0 +1,213 @@
{
"workflow": [
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines",
"targets": "Liquid_1",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines",
"targets": "Liquid_2",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines",
"targets": "Liquid_3",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_2",
"targets": "Liquid_4",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_2",
"targets": "Liquid_5",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_2",
"targets": "Liquid_6",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_3",
"targets": "dest_set",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_3",
"targets": "dest_set_2",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
},
{
"action": "transfer_liquid",
"action_args": {
"sources": "cell_lines_3",
"targets": "dest_set_3",
"asp_vol": 100.0,
"dis_vol": 74.75,
"asp_flow_rate": 94.0,
"dis_flow_rate": 95.5
}
}
],
"reagent": {
"Liquid_1": {
"slot": 1,
"well": [
"A4",
"A7",
"A10"
],
"labware": "rep 1"
},
"Liquid_4": {
"slot": 1,
"well": [
"A4",
"A7",
"A10"
],
"labware": "rep 1"
},
"dest_set": {
"slot": 1,
"well": [
"A4",
"A7",
"A10"
],
"labware": "rep 1"
},
"Liquid_2": {
"slot": 2,
"well": [
"A3",
"A5",
"A8"
],
"labware": "rep 2"
},
"Liquid_5": {
"slot": 2,
"well": [
"A3",
"A5",
"A8"
],
"labware": "rep 2"
},
"dest_set_2": {
"slot": 2,
"well": [
"A3",
"A5",
"A8"
],
"labware": "rep 2"
},
"Liquid_3": {
"slot": 3,
"well": [
"A4",
"A6",
"A10"
],
"labware": "rep 3"
},
"Liquid_6": {
"slot": 3,
"well": [
"A4",
"A6",
"A10"
],
"labware": "rep 3"
},
"dest_set_3": {
"slot": 3,
"well": [
"A4",
"A6",
"A10"
],
"labware": "rep 3"
},
"cell_lines": {
"slot": 4,
"well": [
"A1",
"A3",
"A5"
],
"labware": "DRUG + YOYO-MEDIA"
},
"cell_lines_2": {
"slot": 4,
"well": [
"A1",
"A3",
"A5"
],
"labware": "DRUG + YOYO-MEDIA"
},
"cell_lines_3": {
"slot": 4,
"well": [
"A1",
"A3",
"A5"
],
"labware": "DRUG + YOYO-MEDIA"
}
}
}

View File

@@ -1 +1 @@
__version__ = "0.10.15"
__version__ = "0.10.19"

6
unilabos/__main__.py Normal file
View File

@@ -0,0 +1,6 @@
"""Entry point for `python -m unilabos`."""
from unilabos.app.main import main
if __name__ == "__main__":
main()

View File

@@ -1,13 +1,14 @@
import argparse
import asyncio
import os
import platform
import shutil
import signal
import subprocess
import sys
import threading
import time
from typing import Dict, Any, List
import networkx as nx
import yaml
@@ -17,14 +18,92 @@ unilabos_dir = os.path.dirname(os.path.dirname(current_dir))
if unilabos_dir not in sys.path:
sys.path.append(unilabos_dir)
from unilabos.app.utils import cleanup_for_restart
from unilabos.utils.banner_print import print_status, print_unilab_banner
from unilabos.config.config import load_config, BasicConfig, HTTPConfig
from unilabos.app.utils import cleanup_for_restart
# Global restart flags (used by ws_client and web/server)
_restart_requested: bool = False
_restart_reason: str = ""
RESTART_EXIT_CODE = 42
def _build_child_argv():
"""Build sys.argv for child process, stripping supervisor-only arguments."""
result = []
skip_next = False
for arg in sys.argv:
if skip_next:
skip_next = False
continue
if arg in ("--restart_mode", "--restart-mode"):
continue
if arg in ("--auto_restart_count", "--auto-restart-count"):
skip_next = True
continue
if arg.startswith("--auto_restart_count=") or arg.startswith("--auto-restart-count="):
continue
result.append(arg)
return result
def _run_as_supervisor(max_restarts: int):
"""
Supervisor process that spawns and monitors child processes.
Similar to Uvicorn's --reload: the supervisor itself does no heavy work,
it only launches the real process as a child and restarts it when the child
exits with RESTART_EXIT_CODE.
"""
child_argv = [sys.executable] + _build_child_argv()
restart_count = 0
print_status(
f"[Supervisor] Restart mode enabled (max restarts: {max_restarts}), "
f"child command: {' '.join(child_argv)}",
"info",
)
while True:
print_status(
f"[Supervisor] Launching process (restart {restart_count}/{max_restarts})...",
"info",
)
try:
process = subprocess.Popen(child_argv)
exit_code = process.wait()
except KeyboardInterrupt:
print_status("[Supervisor] Interrupted, terminating child process...", "info")
process.terminate()
try:
process.wait(timeout=10)
except subprocess.TimeoutExpired:
process.kill()
process.wait()
sys.exit(1)
if exit_code == RESTART_EXIT_CODE:
restart_count += 1
if restart_count > max_restarts:
print_status(
f"[Supervisor] Maximum restart count ({max_restarts}) reached, exiting",
"warning",
)
sys.exit(1)
print_status(
f"[Supervisor] Child requested restart ({restart_count}/{max_restarts}), restarting in 2s...",
"info",
)
time.sleep(2)
else:
if exit_code != 0:
print_status(f"[Supervisor] Child exited with code {exit_code}", "warning")
else:
print_status("[Supervisor] Child exited normally", "info")
sys.exit(exit_code)
def load_config_from_file(config_path):
if config_path is None:
@@ -66,6 +145,13 @@ def parse_args():
action="append",
help="Path to the registry directory",
)
parser.add_argument(
"--devices",
type=str,
default=None,
action="append",
help="Path to Python code directory for AST-based device/resource scanning",
)
parser.add_argument(
"--working_dir",
type=str,
@@ -155,17 +241,53 @@ def parse_args():
action="store_true",
help="Skip environment dependency check on startup",
)
parser.add_argument(
"--check_mode",
action="store_true",
default=False,
help="Run in check mode for CI: validates registry imports and ensures no file changes",
)
parser.add_argument(
"--complete_registry",
action="store_true",
default=False,
help="Complete registry information",
help="Complete and rewrite YAML registry files using AST analysis results",
)
parser.add_argument(
"--no_update_feedback",
action="store_true",
help="Disable sending update feedback to server",
)
parser.add_argument(
"--test_mode",
action="store_true",
default=False,
help="Test mode: all actions simulate execution and return mock results without running real hardware",
)
parser.add_argument(
"--external_devices_only",
action="store_true",
default=False,
help="Only load external device packages (--devices), skip built-in unilabos/devices/ scanning and YAML device registry",
)
parser.add_argument(
"--extra_resource",
action="store_true",
default=False,
help="Load extra lab_ prefixed labware resources (529 auto-generated definitions from lab_resources.py)",
)
parser.add_argument(
"--restart_mode",
action="store_true",
default=False,
help="Enable supervisor mode: automatically restart the process when triggered via WebSocket",
)
parser.add_argument(
"--auto_restart_count",
type=int,
default=500,
help="Maximum number of automatic restarts in restart mode (default: 500)",
)
# workflow upload subcommand
workflow_parser = subparsers.add_parser(
"workflow_upload",
@@ -199,6 +321,12 @@ def parse_args():
default=False,
help="Whether to publish the workflow (default: False)",
)
workflow_parser.add_argument(
"--description",
type=str,
default="",
help="Workflow description, used when publishing the workflow",
)
return parser
@@ -210,61 +338,102 @@ def main():
args = parser.parse_args()
args_dict = vars(args)
# Supervisor mode: spawn child processes and monitor for restart
if args_dict.get("restart_mode", False):
_run_as_supervisor(args_dict.get("auto_restart_count", 5))
return
# 环境检查 - 检查并自动安装必需的包 (可选)
if not args_dict.get("skip_env_check", False):
from unilabos.utils.environment_check import check_environment
skip_env_check = args_dict.get("skip_env_check", False)
check_mode = args_dict.get("check_mode", False)
if not skip_env_check:
from unilabos.utils.environment_check import check_environment, check_device_package_requirements
if not check_environment(auto_install=True):
print_status("环境检查失败,程序退出", "error")
os._exit(1)
# 第一次设备包依赖检查build_registry 之前,确保 import map 可用
devices_dirs_for_req = args_dict.get("devices", None)
if devices_dirs_for_req:
if not check_device_package_requirements(devices_dirs_for_req):
print_status("设备包依赖检查失败,程序退出", "error")
os._exit(1)
else:
print_status("跳过环境依赖检查", "warning")
# 加载配置文件优先加载config然后从env读取
config_path = args_dict.get("config")
if os.getcwd().endswith("unilabos_data"):
working_dir = os.path.abspath(os.getcwd())
else:
working_dir = os.path.abspath(os.path.join(os.getcwd(), "unilabos_data"))
if args_dict.get("working_dir"):
working_dir = args_dict.get("working_dir", "")
if config_path and not os.path.exists(config_path):
config_path = os.path.join(working_dir, "local_config.py")
if not os.path.exists(config_path):
print_status(
f"当前工作目录 {working_dir} 未找到local_config.py请通过 --config 传入 local_config.py 文件路径",
"error",
)
os._exit(1)
# === 解析 working_dir ===
# 规则1: working_dir 传入 → 检测 unilabos_data 子目录,已是则不修改
# 规则2: 仅 config_path 传入 → 用其父目录作为 working_dir
# 规则4: 两者都传入 → 各用各的,但 working_dir 仍做 unilabos_data 子目录检测
raw_working_dir = args_dict.get("working_dir")
if raw_working_dir:
working_dir = os.path.abspath(raw_working_dir)
elif config_path and os.path.exists(config_path):
working_dir = os.path.dirname(config_path)
elif os.path.exists(working_dir) and os.path.exists(os.path.join(working_dir, "local_config.py")):
config_path = os.path.join(working_dir, "local_config.py")
elif not config_path and (
not os.path.exists(working_dir) or not os.path.exists(os.path.join(working_dir, "local_config.py"))
):
print_status(f"未指定config路径可通过 --config 传入 local_config.py 文件路径", "info")
print_status(f"您是否为第一次使用?并将当前路径 {working_dir} 作为工作目录? (Y/n)", "info")
if input() != "n":
os.makedirs(working_dir, exist_ok=True)
config_path = os.path.join(working_dir, "local_config.py")
shutil.copy(
os.path.join(os.path.dirname(os.path.dirname(__file__)), "config", "example_config.py"), config_path
)
print_status(f"已创建 local_config.py 路径: {config_path}", "info")
working_dir = os.path.dirname(os.path.abspath(config_path))
else:
working_dir = os.path.abspath(os.getcwd())
# unilabos_data 子目录自动检测
if os.path.basename(working_dir) != "unilabos_data":
unilabos_data_sub = os.path.join(working_dir, "unilabos_data")
if os.path.isdir(unilabos_data_sub):
working_dir = unilabos_data_sub
elif not raw_working_dir and not (config_path and os.path.exists(config_path)):
# 未显式指定路径,默认使用 cwd/unilabos_data
working_dir = os.path.abspath(os.path.join(os.getcwd(), "unilabos_data"))
# === 解析 config_path ===
if config_path and not os.path.exists(config_path):
# config_path 传入但不存在,尝试在 working_dir 中查找
candidate = os.path.join(working_dir, "local_config.py")
if os.path.exists(candidate):
config_path = candidate
print_status(f"在工作目录中发现配置文件: {config_path}", "info")
else:
print_status(
f"配置文件 {config_path} 不存在,工作目录 {working_dir} 中也未找到 local_config.py"
f"请通过 --config 传入 local_config.py 文件路径",
"error",
)
os._exit(1)
# 加载配置文件
elif not config_path:
# 规则3: 未传入 config_path尝试 working_dir/local_config.py
candidate = os.path.join(working_dir, "local_config.py")
if os.path.exists(candidate):
config_path = candidate
print_status(f"发现本地配置文件: {config_path}", "info")
else:
print_status(f"未指定config路径可通过 --config 传入 local_config.py 文件路径", "info")
print_status(f"您是否为第一次使用?并将当前路径 {working_dir} 作为工作目录? (Y/n)", "info")
if check_mode or input() != "n":
os.makedirs(working_dir, exist_ok=True)
config_path = os.path.join(working_dir, "local_config.py")
shutil.copy(
os.path.join(os.path.dirname(os.path.dirname(__file__)), "config", "example_config.py"),
config_path,
)
print_status(f"已创建 local_config.py 路径: {config_path}", "info")
else:
os._exit(1)
# 加载配置文件 (check_mode 跳过)
print_status(f"当前工作目录为 {working_dir}", "info")
load_config_from_file(config_path)
if not check_mode:
load_config_from_file(config_path)
# 根据配置重新设置日志级别
from unilabos.utils.log import configure_logger, logger
if hasattr(BasicConfig, "log_level"):
logger.info(f"Log level set to '{BasicConfig.log_level}' from config file.")
configure_logger(loglevel=BasicConfig.log_level, working_dir=working_dir)
file_path = configure_logger(loglevel=BasicConfig.log_level, working_dir=working_dir)
if file_path is not None:
logger.info(f"[LOG_FILE] {file_path}")
if args.addr != parser.get_default("addr"):
if args.addr == "test":
@@ -308,41 +477,66 @@ def main():
BasicConfig.slave_no_host = args_dict.get("slave_no_host", False)
BasicConfig.upload_registry = args_dict.get("upload_registry", False)
BasicConfig.no_update_feedback = args_dict.get("no_update_feedback", False)
BasicConfig.test_mode = args_dict.get("test_mode", False)
if BasicConfig.test_mode:
print_status("启用测试模式:所有动作将模拟执行,不调用真实硬件", "warning")
BasicConfig.extra_resource = args_dict.get("extra_resource", False)
if BasicConfig.extra_resource:
print_status("启用额外资源加载将加载lab_开头的labware资源定义", "info")
BasicConfig.communication_protocol = "websocket"
machine_name = os.popen("hostname").read().strip()
machine_name = platform.node()
machine_name = "".join([c if c.isalnum() or c == "_" else "_" for c in machine_name])
BasicConfig.machine_name = machine_name
BasicConfig.vis_2d_enable = args_dict["2d_vis"]
BasicConfig.check_mode = check_mode
from unilabos.resources.graphio import (
read_node_link_json,
read_graphml,
dict_from_graph,
)
from unilabos.app.communication import get_communication_client
from unilabos.registry.registry import build_registry
from unilabos.app.backend import start_backend
from unilabos.app.web import http_client
from unilabos.app.web import start_server
from unilabos.app.register import register_devices_and_resources
from unilabos.resources.graphio import modify_to_backend_format
from unilabos.resources.resource_tracker import ResourceTreeSet, ResourceDict
# 显示启动横幅
print_unilab_banner(args_dict)
# 注册表
# Step 0: AST 分析优先 + YAML 注册表加载
# check_mode 和 upload_registry 都会执行实际 import 验证
devices_dirs = args_dict.get("devices", None)
complete_registry = args_dict.get("complete_registry", False) or check_mode
external_only = args_dict.get("external_devices_only", False)
lab_registry = build_registry(
args_dict["registry_path"], args_dict.get("complete_registry", False), BasicConfig.upload_registry
registry_paths=args_dict["registry_path"],
devices_dirs=devices_dirs,
upload_registry=BasicConfig.upload_registry,
check_mode=check_mode,
complete_registry=complete_registry,
external_only=external_only,
)
# Check mode: 注册表验证完成后直接退出
if check_mode:
device_count = len(lab_registry.device_type_registry)
resource_count = len(lab_registry.resource_type_registry)
print_status(f"Check mode: 注册表验证完成 ({device_count} 设备, {resource_count} 资源),退出", "info")
os._exit(0)
# 以下导入依赖 ROS2 环境check_mode 已退出不需要
from unilabos.resources.graphio import (
read_node_link_json,
read_graphml,
dict_from_graph,
modify_to_backend_format,
)
from unilabos.app.communication import get_communication_client
from unilabos.app.backend import start_backend
from unilabos.app.web import http_client
from unilabos.app.web import start_server
from unilabos.app.register import register_devices_and_resources
from unilabos.resources.resource_tracker import ResourceTreeSet, ResourceDict
# Step 1: 上传全部注册表到服务端,同步保存到 unilabos_data
if BasicConfig.upload_registry:
# 设备注册到服务端 - 需要 ak 和 sk
if BasicConfig.ak and BasicConfig.sk:
print_status("开始注册设备到服务端...", "info")
# print_status("开始注册设备到服务端...", "info")
try:
register_devices_and_resources(lab_registry)
print_status("设备注册完成", "info")
# print_status("设备注册完成", "info")
except Exception as e:
print_status(f"设备注册失败: {e}", "error")
else:
@@ -427,12 +621,16 @@ def main():
continue
# 如果从远端获取了物料信息,则与本地物料进行同步
if request_startup_json and "nodes" in request_startup_json:
if file_path is not None and request_startup_json and "nodes" in request_startup_json:
print_status("开始同步远端物料到本地...", "info")
remote_tree_set = ResourceTreeSet.from_raw_dict_list(request_startup_json["nodes"])
resource_tree_set.merge_remote_resources(remote_tree_set)
print_status("远端物料同步完成", "info")
# 第二次设备包依赖检查云端物料同步后community 包可能引入新的 requirements
# TODO: 当 community device package 功能上线后,在这里调用
# install_requirements_txt(community_pkg_path / "requirements.txt", label="community.xxx")
# 使用 ResourceTreeSet 代替 list
args_dict["resources_config"] = resource_tree_set
args_dict["devices_config"] = resource_tree_set
@@ -524,6 +722,10 @@ def main():
open_browser=not args_dict["disable_browser"],
port=BasicConfig.port,
)
if restart_requested:
print_status("[Main] Restart requested, cleaning up...", "info")
cleanup_for_restart()
os._exit(RESTART_EXIT_CODE)
if __name__ == "__main__":

View File

@@ -54,6 +54,7 @@ class JobAddReq(BaseModel):
action_type: str = Field(
examples=["unilabos_msgs.action._str_single_input.StrSingleInput"], description="action type", default=""
)
sample_material: dict = Field(examples=[{"string": "string"}], description="sample uuid to material uuid")
action_args: dict = Field(examples=[{"string": "string"}], description="action arguments", default_factory=dict)
task_id: str = Field(examples=["task_id"], description="task uuid (auto-generated if empty)", default="")
job_id: str = Field(examples=["job_id"], description="goal uuid (auto-generated if empty)", default="")

View File

@@ -1,9 +1,8 @@
import json
import time
from typing import Optional, Tuple, Dict, Any
from typing import Any, Dict, Optional, Tuple
from unilabos.utils.log import logger
from unilabos.utils.type_check import TypeEncoder
from unilabos.utils.tools import normalize_json as _normalize_device
def register_devices_and_resources(lab_registry, gather_only=False) -> Optional[Tuple[Dict[str, Any], Dict[str, Any]]]:
@@ -11,50 +10,63 @@ def register_devices_and_resources(lab_registry, gather_only=False) -> Optional[
注册设备和资源到服务器仅支持HTTP
"""
# 注册资源信息 - 使用HTTP方式
from unilabos.app.web.client import http_client
logger.info("[UniLab Register] 开始注册设备和资源...")
# 注册设备信息
devices_to_register = {}
for device_info in lab_registry.obtain_registry_device_info():
devices_to_register[device_info["id"]] = json.loads(
json.dumps(device_info, ensure_ascii=False, cls=TypeEncoder)
)
logger.debug(f"[UniLab Register] 收集设备: {device_info['id']}")
devices_to_register[device_info["id"]] = _normalize_device(device_info)
logger.trace(f"[UniLab Register] 收集设备: {device_info['id']}")
resources_to_register = {}
for resource_info in lab_registry.obtain_registry_resource_info():
resources_to_register[resource_info["id"]] = resource_info
logger.debug(f"[UniLab Register] 收集资源: {resource_info['id']}")
logger.trace(f"[UniLab Register] 收集资源: {resource_info['id']}")
if gather_only:
return devices_to_register, resources_to_register
# 注册设备
if devices_to_register:
try:
start_time = time.time()
response = http_client.resource_registry({"resources": list(devices_to_register.values())})
response = http_client.resource_registry(
{"resources": list(devices_to_register.values())},
tag="device_registry",
)
cost_time = time.time() - start_time
if response.status_code in [200, 201]:
logger.info(f"[UniLab Register] 成功注册 {len(devices_to_register)} 个设备 {cost_time}ms")
res_data = response.json() if response.status_code == 200 else {}
skipped = res_data.get("data", {}).get("skipped", False)
if skipped:
logger.info(
f"[UniLab Register] 设备注册跳过(内容未变化)"
f" {len(devices_to_register)}{cost_time:.3f}s"
)
elif response.status_code in [200, 201]:
logger.info(f"[UniLab Register] 成功注册 {len(devices_to_register)} 个设备 {cost_time:.3f}s")
else:
logger.error(f"[UniLab Register] 设备注册失败: {response.status_code}, {response.text} {cost_time}ms")
logger.error(f"[UniLab Register] 设备注册失败: {response.status_code}, {response.text} {cost_time:.3f}s")
except Exception as e:
logger.error(f"[UniLab Register] 设备注册异常: {e}")
# 注册资源
if resources_to_register:
try:
start_time = time.time()
response = http_client.resource_registry({"resources": list(resources_to_register.values())})
response = http_client.resource_registry(
{"resources": list(resources_to_register.values())},
tag="resource_registry",
)
cost_time = time.time() - start_time
if response.status_code in [200, 201]:
logger.info(f"[UniLab Register] 成功注册 {len(resources_to_register)} 个资源 {cost_time}ms")
res_data = response.json() if response.status_code == 200 else {}
skipped = res_data.get("data", {}).get("skipped", False)
if skipped:
logger.info(
f"[UniLab Register] 资源注册跳过(内容未变化)"
f" {len(resources_to_register)}{cost_time:.3f}s"
)
elif response.status_code in [200, 201]:
logger.info(f"[UniLab Register] 成功注册 {len(resources_to_register)} 个资源 {cost_time:.3f}s")
else:
logger.error(f"[UniLab Register] 资源注册失败: {response.status_code}, {response.text} {cost_time}ms")
logger.error(f"[UniLab Register] 资源注册失败: {response.status_code}, {response.text} {cost_time:.3f}s")
except Exception as e:
logger.error(f"[UniLab Register] 资源注册异常: {e}")
logger.info("[UniLab Register] 设备和资源注册完成.")

View File

@@ -4,8 +4,40 @@ UniLabOS 应用工具函数
提供清理、重启等工具函数
"""
import gc
import glob
import os
import shutil
import sys
def patch_rclpy_dll_windows():
"""在 Windows + conda 环境下为 rclpy 打 DLL 加载补丁"""
if sys.platform != "win32" or not os.environ.get("CONDA_PREFIX"):
return
try:
import rclpy
return
except ImportError as e:
if not str(e).startswith("DLL load failed"):
return
cp = os.environ["CONDA_PREFIX"]
impl = os.path.join(cp, "Lib", "site-packages", "rclpy", "impl", "implementation_singleton.py")
pyd = glob.glob(os.path.join(cp, "Lib", "site-packages", "rclpy", "_rclpy_pybind11*.pyd"))
if not os.path.exists(impl) or not pyd:
return
with open(impl, "r", encoding="utf-8") as f:
content = f.read()
lib_bin = os.path.join(cp, "Library", "bin").replace("\\", "/")
patch = f'# UniLabOS DLL Patch\nimport os,ctypes\nos.add_dll_directory("{lib_bin}") if hasattr(os,"add_dll_directory") else None\ntry: ctypes.CDLL("{pyd[0].replace(chr(92),"/")}")\nexcept: pass\n# End Patch\n'
shutil.copy2(impl, impl + ".bak")
with open(impl, "w", encoding="utf-8") as f:
f.write(patch + content)
patch_rclpy_dll_windows()
import gc
import threading
import time

View File

@@ -1052,7 +1052,7 @@ async def handle_file_import(websocket: WebSocket, request_data: dict):
"result": {},
"schema": lab_registry._generate_unilab_json_command_schema(v["args"], k),
"goal_default": {i["name"]: i["default"] for i in v["args"]},
"handles": [],
"handles": {},
}
# 不生成已配置action的动作
for k, v in enhanced_info["action_methods"].items()
@@ -1340,5 +1340,5 @@ def setup_api_routes(app):
# 启动广播任务
@app.on_event("startup")
async def startup_event():
asyncio.create_task(broadcast_device_status())
asyncio.create_task(broadcast_status_page_data())
asyncio.create_task(broadcast_device_status(), name="web-api-startup-device")
asyncio.create_task(broadcast_status_page_data(), name="web-api-startup-status")

View File

@@ -3,11 +3,13 @@ HTTP客户端模块
提供与远程服务器通信的客户端功能只有host需要用
"""
import gzip
import json
import os
from typing import List, Dict, Any, Optional
from unilabos.utils.tools import fast_dumps as _fast_dumps, fast_dumps_pretty as _fast_dumps_pretty
import requests
from unilabos.resources.resource_tracker import ResourceTreeSet
from unilabos.utils.log import info
@@ -78,19 +80,20 @@ class HTTPClient:
f.write(json.dumps(payload, indent=4))
# 从序列化数据中提取所有节点的UUID保存旧UUID
old_uuids = {n.res_content.uuid: n for n in resources.all_nodes}
nodes_info = [x for xs in resources.dump() for x in xs]
if not self.initialized or first_add:
self.initialized = True
info(f"首次添加资源,当前远程地址: {self.remote_addr}")
response = requests.post(
f"{self.remote_addr}/edge/material",
json={"nodes": [x for xs in resources.dump() for x in xs], "mount_uuid": mount_uuid},
json={"nodes": nodes_info, "mount_uuid": mount_uuid},
headers={"Authorization": f"Lab {self.auth}"},
timeout=60,
)
else:
response = requests.put(
f"{self.remote_addr}/edge/material",
json={"nodes": [x for xs in resources.dump() for x in xs], "mount_uuid": mount_uuid},
json={"nodes": nodes_info, "mount_uuid": mount_uuid},
headers={"Authorization": f"Lab {self.auth}"},
timeout=10,
)
@@ -109,6 +112,7 @@ class HTTPClient:
uuid_mapping[i["uuid"]] = i["cloud_uuid"]
else:
logger.error(f"添加物料失败: {response.text}")
logger.trace(f"添加物料失败: {nodes_info}")
for u, n in old_uuids.items():
if u in uuid_mapping:
n.res_content.uuid = uuid_mapping[u]
@@ -280,22 +284,54 @@ class HTTPClient:
)
return response
def resource_registry(self, registry_data: Dict[str, Any] | List[Dict[str, Any]]) -> requests.Response:
def resource_registry(
self, registry_data: Dict[str, Any] | List[Dict[str, Any]], tag: str = "registry",
) -> requests.Response:
"""
注册资源到服务器
注册资源到服务器,同步保存请求/响应到 unilabos_data
Args:
registry_data: 注册表数据,格式为 {resource_id: resource_info} / [{resource_info}]
tag: 保存文件的标签后缀 (如 "device_registry" / "resource_registry")
Returns:
Response: API响应对象
"""
# 序列化一次,同时用于保存和发送
json_bytes = _fast_dumps(registry_data)
# 保存请求数据到 unilabos_data
req_path = os.path.join(BasicConfig.working_dir, f"req_{tag}_upload.json")
try:
os.makedirs(BasicConfig.working_dir, exist_ok=True)
with open(req_path, "wb") as f:
f.write(_fast_dumps_pretty(registry_data))
logger.trace(f"注册表请求数据已保存: {req_path}")
except Exception as e:
logger.warning(f"保存注册表请求数据失败: {e}")
compressed_body = gzip.compress(json_bytes)
headers = {
"Authorization": f"Lab {self.auth}",
"Content-Type": "application/json",
"Content-Encoding": "gzip",
}
response = requests.post(
f"{self.remote_addr}/lab/resource",
json=registry_data,
headers={"Authorization": f"Lab {self.auth}"},
data=compressed_body,
headers=headers,
timeout=30,
)
# 保存响应数据到 unilabos_data
res_path = os.path.join(BasicConfig.working_dir, f"res_{tag}_upload.json")
try:
with open(res_path, "w", encoding="utf-8") as f:
f.write(f"{response.status_code}\n{response.text}")
logger.trace(f"注册表响应数据已保存: {res_path}")
except Exception as e:
logger.warning(f"保存注册表响应数据失败: {e}")
if response.status_code not in [200, 201]:
logger.error(f"注册资源失败: {response.status_code}, {response.text}")
if response.status_code == 200:
@@ -343,9 +379,10 @@ class HTTPClient:
edges: List[Dict[str, Any]],
tags: Optional[List[str]] = None,
published: bool = False,
description: str = "",
) -> Dict[str, Any]:
"""
导入工作流到服务器
导入工作流到服务器,如果 published 为 True则额外发起发布请求
Args:
name: 工作流名称(顶层)
@@ -355,13 +392,12 @@ class HTTPClient:
edges: 工作流边列表
tags: 工作流标签列表,默认为空列表
published: 是否发布工作流默认为False
description: 工作流描述,发布时使用
Returns:
Dict: API响应数据包含 code 和 data (uuid, name)
"""
# target_lab_uuid 暂时使用默认值,后续由后端根据 ak/sk 获取
payload = {
"target_lab_uuid": "28c38bb0-63f6-4352-b0d8-b5b8eb1766d5",
"name": name,
"data": {
"workflow_uuid": workflow_uuid,
@@ -369,7 +405,6 @@ class HTTPClient:
"nodes": nodes,
"edges": edges,
"tags": tags if tags is not None else [],
"published": published,
},
}
# 保存请求到文件
@@ -390,11 +425,51 @@ class HTTPClient:
res = response.json()
if "code" in res and res["code"] != 0:
logger.error(f"导入工作流失败: {response.text}")
return res
# 导入成功后,如果需要发布则额外发起发布请求
if published:
imported_uuid = res.get("data", {}).get("uuid", workflow_uuid)
publish_res = self.workflow_publish(imported_uuid, description)
res["publish_result"] = publish_res
return res
else:
logger.error(f"导入工作流失败: {response.status_code}, {response.text}")
return {"code": response.status_code, "message": response.text}
def workflow_publish(self, workflow_uuid: str, description: str = "") -> Dict[str, Any]:
"""
发布工作流
Args:
workflow_uuid: 工作流UUID
description: 工作流描述
Returns:
Dict: API响应数据
"""
payload = {
"uuid": workflow_uuid,
"description": description,
"published": True,
}
logger.info(f"正在发布工作流: {workflow_uuid}")
response = requests.patch(
f"{self.remote_addr}/lab/workflow/owner",
json=payload,
headers={"Authorization": f"Lab {self.auth}"},
timeout=60,
)
if response.status_code == 200:
res = response.json()
if "code" in res and res["code"] != 0:
logger.error(f"发布工作流失败: {response.text}")
else:
logger.info(f"工作流发布成功: {workflow_uuid}")
return res
else:
logger.error(f"发布工作流失败: {response.status_code}, {response.text}")
return {"code": response.status_code, "message": response.text}
# 创建默认客户端实例
http_client = HTTPClient()

View File

@@ -58,14 +58,14 @@ class JobResultStore:
feedback=feedback or {},
timestamp=time.time(),
)
logger.debug(f"[JobResultStore] Stored result for job {job_id[:8]}, status={status}")
logger.trace(f"[JobResultStore] Stored result for job {job_id[:8]}, status={status}")
def get_and_remove(self, job_id: str) -> Optional[JobResult]:
"""获取并删除任务结果"""
with self._results_lock:
result = self._results.pop(job_id, None)
if result:
logger.debug(f"[JobResultStore] Retrieved and removed result for job {job_id[:8]}")
logger.trace(f"[JobResultStore] Retrieved and removed result for job {job_id[:8]}")
return result
def get_result(self, job_id: str) -> Optional[JobResult]:
@@ -327,6 +327,7 @@ def job_add(req: JobAddReq) -> JobData:
queue_item,
action_type=action_type,
action_kwargs=action_args,
sample_material=req.sample_material,
server_info=server_info,
)

View File

@@ -86,7 +86,7 @@ def setup_server() -> FastAPI:
# 设置页面路由
try:
setup_web_pages(pages)
info("[Web] 已加载Web UI模块")
# info("[Web] 已加载Web UI模块")
except ImportError as e:
info(f"[Web] 未找到Web页面模块: {str(e)}")
except Exception as e:
@@ -138,7 +138,7 @@ def start_server(host: str = "0.0.0.0", port: int = 8002, open_browser: bool = T
server_thread = threading.Thread(target=server.run, daemon=True, name="uvicorn_server")
server_thread.start()
info("[Web] Server started, monitoring for restart requests...")
# info("[Web] Server started, monitoring for restart requests...")
# 监控重启标志
import unilabos.app.main as main_module

View File

@@ -23,9 +23,10 @@ from typing import Optional, Dict, Any, List
from urllib.parse import urlparse
from enum import Enum
from jedi.inference.gradual.typing import TypedDict
from typing_extensions import TypedDict
from unilabos.app.model import JobAddReq
from unilabos.resources.resource_tracker import ResourceDictType
from unilabos.ros.nodes.presets.host_node import HostNode
from unilabos.utils.type_check import serialize_result_info
from unilabos.app.communication import BaseCommunicationClient
@@ -76,6 +77,7 @@ class JobInfo:
start_time: float
last_update_time: float = field(default_factory=time.time)
ready_timeout: Optional[float] = None # READY状态的超时时间
always_free: bool = False # 是否为永久闲置动作(不受排队限制)
def update_timestamp(self):
"""更新最后更新时间"""
@@ -127,6 +129,15 @@ class DeviceActionManager:
# 总是将job添加到all_jobs中
self.all_jobs[job_info.job_id] = job_info
# always_free的动作不受排队限制直接设为READY
if job_info.always_free:
job_info.status = JobStatus.READY
job_info.update_timestamp()
job_info.set_ready_timeout(10)
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.trace(f"[DeviceActionManager] Job {job_log} always_free, start immediately")
return True
# 检查是否有正在执行或准备执行的任务
if device_key in self.active_jobs:
# 有正在执行或准备执行的任务,加入队列
@@ -154,7 +165,7 @@ class DeviceActionManager:
job_info.set_ready_timeout(10) # 设置10秒超时
self.active_jobs[device_key] = job_info
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.info(f"[DeviceActionManager] Job {job_log} can start immediately for {device_key}")
logger.trace(f"[DeviceActionManager] Job {job_log} can start immediately for {device_key}")
return True
def start_job(self, job_id: str) -> bool:
@@ -176,11 +187,15 @@ class DeviceActionManager:
logger.error(f"[DeviceActionManager] Job {job_log} is not in READY status, current: {job_info.status}")
return False
# 检查设备上是否是这个job
if device_key not in self.active_jobs or self.active_jobs[device_key].job_id != job_id:
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.error(f"[DeviceActionManager] Job {job_log} is not the active job for {device_key}")
return False
# always_free的job不需要检查active_jobs
if not job_info.always_free:
# 检查设备上是否是这个job
if device_key not in self.active_jobs or self.active_jobs[device_key].job_id != job_id:
job_log = format_job_log(
job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name
)
logger.error(f"[DeviceActionManager] Job {job_log} is not the active job for {device_key}")
return False
# 开始执行任务将状态从READY转换为STARTED
job_info.status = JobStatus.STARTED
@@ -203,6 +218,13 @@ class DeviceActionManager:
job_info = self.all_jobs[job_id]
device_key = job_info.device_action_key
# always_free的job直接清理不影响队列
if job_info.always_free:
job_info.status = JobStatus.ENDED
job_info.update_timestamp()
del self.all_jobs[job_id]
return None
# 移除活跃任务
if device_key in self.active_jobs and self.active_jobs[device_key].job_id == job_id:
del self.active_jobs[device_key]
@@ -210,8 +232,9 @@ class DeviceActionManager:
job_info.update_timestamp()
# 从all_jobs中移除已结束的job
del self.all_jobs[job_id]
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.info(f"[DeviceActionManager] Job {job_log} ended for {device_key}")
# job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
# logger.debug(f"[DeviceActionManager] Job {job_log} ended for {device_key}")
pass
else:
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.warning(f"[DeviceActionManager] Job {job_log} was not active for {device_key}")
@@ -227,15 +250,20 @@ class DeviceActionManager:
next_job_log = format_job_log(
next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
)
logger.info(f"[DeviceActionManager] Next job {next_job_log} can start for {device_key}")
logger.trace(f"[DeviceActionManager] Next job {next_job_log} can start for {device_key}")
return next_job
return None
def get_active_jobs(self) -> List[JobInfo]:
"""获取所有正在执行的任务"""
"""获取所有正在执行的任务(含active_jobs和always_free的STARTED job)"""
with self.lock:
return list(self.active_jobs.values())
jobs = list(self.active_jobs.values())
# 补充 always_free 的 STARTED job(它们不在 active_jobs 中)
for job in self.all_jobs.values():
if job.always_free and job.status == JobStatus.STARTED and job not in jobs:
jobs.append(job)
return jobs
def get_queued_jobs(self) -> List[JobInfo]:
"""获取所有排队中的任务"""
@@ -260,6 +288,14 @@ class DeviceActionManager:
job_info = self.all_jobs[job_id]
device_key = job_info.device_action_key
# always_free的job直接清理
if job_info.always_free:
job_info.status = JobStatus.ENDED
del self.all_jobs[job_id]
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.trace(f"[DeviceActionManager] Always-free job {job_log} cancelled")
return True
# 如果是正在执行的任务
if device_key in self.active_jobs and self.active_jobs[device_key].job_id == job_id:
# 清理active job状态
@@ -268,7 +304,7 @@ class DeviceActionManager:
# 从all_jobs中移除
del self.all_jobs[job_id]
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
logger.info(f"[DeviceActionManager] Active job {job_log} cancelled for {device_key}")
logger.trace(f"[DeviceActionManager] Active job {job_log} cancelled for {device_key}")
# 启动下一个任务
if device_key in self.device_queues and self.device_queues[device_key]:
@@ -281,7 +317,7 @@ class DeviceActionManager:
next_job_log = format_job_log(
next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name
)
logger.info(f"[DeviceActionManager] Next job {next_job_log} can start after cancel")
logger.trace(f"[DeviceActionManager] Next job {next_job_log} can start after cancel")
return True
# 如果是排队中的任务
@@ -295,7 +331,7 @@ class DeviceActionManager:
job_log = format_job_log(
job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name
)
logger.info(f"[DeviceActionManager] Queued job {job_log} cancelled for {device_key}")
logger.trace(f"[DeviceActionManager] Queued job {job_log} cancelled for {device_key}")
return True
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
@@ -333,13 +369,18 @@ class DeviceActionManager:
timeout_jobs = []
with self.lock:
# 统计READY状态的任务数量
ready_jobs_count = sum(1 for job in self.active_jobs.values() if job.status == JobStatus.READY)
# 收集所有需要检查的 READY 任务(active_jobs + always_free READY jobs)
ready_candidates = list(self.active_jobs.values())
for job in self.all_jobs.values():
if job.always_free and job.status == JobStatus.READY and job not in ready_candidates:
ready_candidates.append(job)
ready_jobs_count = sum(1 for job in ready_candidates if job.status == JobStatus.READY)
if ready_jobs_count > 0:
logger.trace(f"[DeviceActionManager] Checking {ready_jobs_count} READY jobs for timeout") # type: ignore # noqa: E501
# 找到所有超时的READY任务只检测不处理
for job_info in self.active_jobs.values():
for job_info in ready_candidates:
if job_info.is_ready_timeout():
timeout_jobs.append(job_info)
job_log = format_job_log(
@@ -368,6 +409,7 @@ class MessageProcessor:
# 线程控制
self.is_running = False
self.thread = None
self._loop = None # asyncio event loop引用用于外部关闭websocket
self.reconnect_count = 0
logger.info(f"[MessageProcessor] Initialized for URL: {websocket_url}")
@@ -394,22 +436,31 @@ class MessageProcessor:
def stop(self) -> None:
"""停止消息处理线程"""
self.is_running = False
# 主动关闭websocket以快速中断消息接收循环
ws = self.websocket
loop = self._loop
if ws and loop and loop.is_running():
try:
asyncio.run_coroutine_threadsafe(ws.close(), loop)
except Exception:
pass
if self.thread and self.thread.is_alive():
self.thread.join(timeout=2)
logger.info("[MessageProcessor] Stopped")
def _run(self):
"""运行消息处理主循环"""
loop = asyncio.new_event_loop()
self._loop = asyncio.new_event_loop()
try:
asyncio.set_event_loop(loop)
loop.run_until_complete(self._connection_handler())
asyncio.set_event_loop(self._loop)
self._loop.run_until_complete(self._connection_handler())
except Exception as e:
logger.error(f"[MessageProcessor] Thread error: {str(e)}")
logger.error(traceback.format_exc())
finally:
if loop:
loop.close()
if self._loop:
self._loop.close()
self._loop = None
async def _connection_handler(self):
"""处理WebSocket连接和重连逻辑"""
@@ -426,8 +477,10 @@ class MessageProcessor:
async with websockets.connect(
self.websocket_url,
ssl=ssl_context,
open_timeout=20,
ping_interval=WSConfig.ping_interval,
ping_timeout=10,
close_timeout=5,
additional_headers={
"Authorization": f"Lab {BasicConfig.auth_secret()}",
"EdgeSession": f"{self.session_id}",
@@ -438,77 +491,94 @@ class MessageProcessor:
self.connected = True
self.reconnect_count = 0
logger.trace(f"[MessageProcessor] Connected to {self.websocket_url}")
logger.info(f"[MessageProcessor] 已连接到 {self.websocket_url}")
# 启动发送协程
send_task = asyncio.create_task(self._send_handler())
send_task = asyncio.create_task(self._send_handler(), name="websocket-send_task")
# 每次连接(含重连)后重新向服务端注册,
# 否则服务端不知道客户端已上线,不会推送消息。
if self.websocket_client:
self.websocket_client.publish_host_ready()
try:
# 接收消息循环
await self._message_handler()
finally:
# 必须在 async with __aexit__ 之前停止 send_task
# 否则 send_task 会在关闭握手期间继续发送数据,
# 干扰 websockets 库的内部清理,导致 task 泄漏。
self.connected = False
send_task.cancel()
try:
await send_task
except asyncio.CancelledError:
pass
self.connected = False
except websockets.exceptions.ConnectionClosed:
logger.warning("[MessageProcessor] Connection closed")
self.connected = False
logger.warning("[MessageProcessor] 与服务端连接中断")
except TimeoutError:
logger.warning(
f"[MessageProcessor] 与服务端连接通信超时 (已尝试 {self.reconnect_count + 1} 次),请检查您的网络状况"
)
except websockets.exceptions.InvalidStatus as e:
logger.warning(
f"[MessageProcessor] 收到服务端注册码 {e.response.status_code}, 上一进程可能还未退出"
)
except Exception as e:
logger.error(f"[MessageProcessor] Connection error: {str(e)}")
logger.error(traceback.format_exc())
self.connected = False
logger.error(f"[MessageProcessor] 尝试重连时出错 {str(e)}")
finally:
self.connected = False
self.websocket = None
# 重连逻辑
if self.is_running and self.reconnect_count < WSConfig.max_reconnect_attempts:
if not self.is_running:
break
if self.reconnect_count < WSConfig.max_reconnect_attempts:
self.reconnect_count += 1
backoff = WSConfig.reconnect_interval
logger.info(
f"[MessageProcessor] Reconnecting in {WSConfig.reconnect_interval}s "
f"(attempt {self.reconnect_count}/{WSConfig.max_reconnect_attempts})"
f"[MessageProcessor] 即将在 {backoff} 秒后重连 (已尝试 {self.reconnect_count}/{WSConfig.max_reconnect_attempts})"
)
await asyncio.sleep(WSConfig.reconnect_interval)
elif self.reconnect_count >= WSConfig.max_reconnect_attempts:
await asyncio.sleep(backoff)
else:
logger.error("[MessageProcessor] Max reconnection attempts reached")
break
else:
self.reconnect_count -= 1
async def _message_handler(self):
"""处理接收到的消息"""
"""处理接收到的消息
ConnectionClosed 不在此处捕获,让其向上传播到 _connection_handler
以便 async with websockets.connect() 的 __aexit__ 能感知连接已断,
正确清理内部 task避免 task 泄漏。
"""
if not self.websocket:
logger.error("[MessageProcessor] WebSocket connection is None")
return
try:
async for message in self.websocket:
try:
data = json.loads(message)
message_type = data.get("action", "")
message_data = data.get("data")
if self.session_id and self.session_id == data.get("edge_session"):
await self._process_message(message_type, message_data)
async for message in self.websocket:
try:
data = json.loads(message)
message_type = data.get("action", "")
message_data = data.get("data")
if self.session_id and self.session_id == data.get("edge_session"):
await self._process_message(message_type, message_data)
else:
if message_type.endswith("_material"):
logger.trace(
f"[MessageProcessor] 收到一条归属 {data.get('edge_session')} 的旧消息:{data}"
)
logger.debug(
f"[MessageProcessor] 跳过了一条归属 {data.get('edge_session')} 的旧消息: {data.get('action')}"
)
else:
if message_type.endswith("_material"):
logger.trace(f"[MessageProcessor] 收到一条归属 {data.get('edge_session')} 的旧消息:{data}")
logger.debug(f"[MessageProcessor] 跳过了一条归属 {data.get('edge_session')} 的旧消息: {data.get('action')}")
else:
await self._process_message(message_type, message_data)
except json.JSONDecodeError:
logger.error(f"[MessageProcessor] Invalid JSON received: {message}")
except Exception as e:
logger.error(f"[MessageProcessor] Error processing message: {str(e)}")
logger.error(traceback.format_exc())
except websockets.exceptions.ConnectionClosed:
logger.info("[MessageProcessor] Message handler stopped - connection closed")
except Exception as e:
logger.error(f"[MessageProcessor] Message handler error: {str(e)}")
logger.error(traceback.format_exc())
await self._process_message(message_type, message_data)
except json.JSONDecodeError:
logger.error(f"[MessageProcessor] Invalid JSON received: {message}")
except Exception as e:
logger.error(f"[MessageProcessor] Error processing message: {str(e)}")
logger.error(traceback.format_exc())
async def _send_handler(self):
"""处理发送队列中的消息"""
@@ -540,7 +610,7 @@ class MessageProcessor:
try:
message_str = json.dumps(msg, ensure_ascii=False)
await self.websocket.send(message_str)
logger.trace(f"[MessageProcessor] Message sent: {msg.get('action', 'unknown')}") # type: ignore # noqa: E501
# logger.trace(f"[MessageProcessor] Message sent: {msg.get('action', 'unknown')}") # type: ignore # noqa: E501
except Exception as e:
logger.error(f"[MessageProcessor] Failed to send message: {str(e)}")
logger.error(traceback.format_exc())
@@ -557,6 +627,7 @@ class MessageProcessor:
except asyncio.CancelledError:
logger.debug("[MessageProcessor] Send handler cancelled")
raise
except Exception as e:
logger.error(f"[MessageProcessor] Fatal error in send handler: {str(e)}")
logger.error(traceback.format_exc())
@@ -565,7 +636,7 @@ class MessageProcessor:
async def _process_message(self, message_type: str, message_data: Dict[str, Any]):
"""处理收到的消息"""
logger.debug(f"[MessageProcessor] Processing message: {message_type}")
logger.trace(f"[MessageProcessor] Processing message: {message_type}")
try:
if message_type == "pong":
@@ -588,6 +659,10 @@ class MessageProcessor:
# elif message_type == "session_id":
# self.session_id = message_data.get("session_id")
# logger.info(f"[MessageProcessor] Session ID: {self.session_id}")
elif message_type == "add_device":
await self._handle_device_manage(message_data, "add")
elif message_type == "remove_device":
await self._handle_device_manage(message_data, "remove")
elif message_type == "request_restart":
await self._handle_request_restart(message_data)
else:
@@ -603,6 +678,24 @@ class MessageProcessor:
if host_node:
host_node.handle_pong_response(pong_data)
def _check_action_always_free(self, device_id: str, action_name: str) -> bool:
"""检查该action是否标记为always_free通过HostNode统一的_action_value_mappings查找"""
try:
host_node = HostNode.get_instance(0)
if not host_node:
return False
# noinspection PyProtectedMember
action_mappings = host_node._action_value_mappings.get(device_id)
if not action_mappings:
return False
# 尝试直接匹配或 auto- 前缀匹配
for key in [action_name, f"auto-{action_name}"]:
if key in action_mappings:
return action_mappings[key].get("always_free", False)
return False
except Exception:
return False
async def _handle_query_action_state(self, data: Dict[str, Any]):
"""处理query_action_state消息"""
device_id = data.get("device_id", "")
@@ -617,6 +710,9 @@ class MessageProcessor:
device_action_key = f"/devices/{device_id}/{action_name}"
# 检查action是否为always_free
action_always_free = self._check_action_always_free(device_id, action_name)
# 创建任务信息
job_info = JobInfo(
job_id=job_id,
@@ -626,6 +722,7 @@ class MessageProcessor:
device_action_key=device_action_key,
status=JobStatus.QUEUE,
start_time=time.time(),
always_free=action_always_free,
)
# 添加到设备管理器
@@ -637,13 +734,13 @@ class MessageProcessor:
await self._send_action_state_response(
device_id, action_name, task_id, job_id, "query_action_status", True, 0
)
logger.info(f"[MessageProcessor] Job {job_log} can start immediately")
logger.trace(f"[MessageProcessor] Job {job_log} can start immediately")
else:
# 需要排队
await self._send_action_state_response(
device_id, action_name, task_id, job_id, "query_action_status", False, 10
)
logger.info(f"[MessageProcessor] Job {job_log} queued")
logger.trace(f"[MessageProcessor] Job {job_log} queued")
# 通知QueueProcessor有新的队列更新
if self.queue_processor:
@@ -652,9 +749,37 @@ class MessageProcessor:
async def _handle_job_start(self, data: Dict[str, Any]):
"""处理job_start消息"""
try:
if not data.get("sample_material"):
data["sample_material"] = {}
req = JobAddReq(**data)
job_log = format_job_log(req.job_id, req.task_id, req.device_id, req.action)
# 服务端对always_free动作可能跳过query_action_state直接发job_start
# 此时job尚未注册需要自动补注册
existing_job = self.device_manager.get_job_info(req.job_id)
if not existing_job:
action_name = req.action
device_action_key = f"/devices/{req.device_id}/{action_name}"
action_always_free = self._check_action_always_free(req.device_id, action_name)
if action_always_free:
job_info = JobInfo(
job_id=req.job_id,
task_id=req.task_id,
device_id=req.device_id,
action_name=action_name,
device_action_key=device_action_key,
status=JobStatus.QUEUE,
start_time=time.time(),
always_free=True,
)
self.device_manager.add_queue_request(job_info)
logger.info(f"[MessageProcessor] Job {job_log} always_free, auto-registered from direct job_start")
else:
logger.error(f"[MessageProcessor] Job {job_log} not registered (missing query_action_state)")
return
success = self.device_manager.start_job(req.job_id)
if not success:
logger.error(f"[MessageProcessor] Failed to start job {job_log}")
@@ -683,6 +808,7 @@ class MessageProcessor:
queue_item,
action_type=req.action_type,
action_kwargs=req.action_args,
sample_material=req.sample_material,
server_info=req.server_info,
)
@@ -847,9 +973,7 @@ class MessageProcessor:
device_action_groups[key_add] = []
device_action_groups[key_add].append(item["uuid"])
logger.info(
f"[资源同步] 跨站Transfer: {item['uuid'][:8]} from {device_old_id} to {device_id}"
)
logger.info(f"[资源同步] 跨站Transfer: {item['uuid'][:8]} from {device_old_id} to {device_id}")
else:
# 正常update
key = (device_id, "update")
@@ -863,7 +987,9 @@ class MessageProcessor:
device_action_groups[key] = []
device_action_groups[key].append(item["uuid"])
logger.trace(f"[资源同步] 动作 {action} 分组数量: {len(device_action_groups)}, 总数量: {len(resource_uuid_list)}")
logger.trace(
f"[资源同步] 动作 {action} 分组数量: {len(device_action_groups)}, 总数量: {len(resource_uuid_list)}"
)
# 为每个(device_id, action)创建独立的更新线程
for (device_id, actual_action), items in device_action_groups.items():
@@ -899,6 +1025,37 @@ class MessageProcessor:
)
thread.start()
async def _handle_device_manage(self, device_list: list[ResourceDictType], action: str):
"""Handle add_device / remove_device from LabGo server."""
if not device_list:
return
for item in device_list:
target_node_id = item.get("target_node_id", "host_node")
def _notify(target_id: str, act: str, cfg: ResourceDictType):
try:
host_node = HostNode.get_instance(timeout=5)
if not host_node:
logger.error(f"[DeviceManage] HostNode not available for {act}_device")
return
success = host_node.notify_device_manage(target_id, act, cfg)
if success:
logger.info(f"[DeviceManage] {act}_device completed on {target_id}")
else:
logger.warning(f"[DeviceManage] {act}_device failed on {target_id}")
except Exception as e:
logger.error(f"[DeviceManage] Error in {act}_device: {e}")
logger.error(traceback.format_exc())
thread = threading.Thread(
target=_notify,
args=(target_node_id, action, item),
daemon=True,
name=f"DeviceManage-{action}-{item.get('id', '')}",
)
thread.start()
async def _handle_request_restart(self, data: Dict[str, Any]):
"""
处理重启请求
@@ -910,14 +1067,13 @@ class MessageProcessor:
logger.info(f"[MessageProcessor] Received restart request, reason: {reason}, delay: {delay}s")
# 发送确认消息
if self.websocket_client:
await self.websocket_client.send_message({
"action": "restart_acknowledged",
"data": {"reason": reason, "delay": delay}
})
self.send_message(
{"action": "restart_acknowledged", "data": {"reason": reason, "delay": delay}}
)
# 设置全局重启标志
import unilabos.app.main as main_module
main_module._restart_requested = True
main_module._restart_reason = reason
@@ -927,10 +1083,12 @@ class MessageProcessor:
# 在新线程中执行清理,避免阻塞当前事件循环
def do_cleanup():
import time
time.sleep(0.5) # 给当前消息处理完成的时间
logger.info(f"[MessageProcessor] Starting cleanup for restart, reason: {reason}")
try:
from unilabos.app.utils import cleanup_for_restart
if cleanup_for_restart():
logger.info("[MessageProcessor] Cleanup successful, main() will restart")
else:
@@ -955,7 +1113,7 @@ class MessageProcessor:
"task_id": task_id,
"job_id": job_id,
"free": free,
"need_more": need_more,
"need_more": need_more + 1,
},
}
@@ -1013,6 +1171,7 @@ class QueueProcessor:
def stop(self) -> None:
"""停止队列处理线程"""
self.is_running = False
self.queue_update_event.set() # 立即唤醒等待中的线程
if self.thread and self.thread.is_alive():
self.thread.join(timeout=2)
logger.info("[QueueProcessor] Stopped")
@@ -1094,7 +1253,7 @@ class QueueProcessor:
"task_id": job_info.task_id,
"job_id": job_info.job_id,
"free": False,
"need_more": 10,
"need_more": 10 + 1,
},
}
self.message_processor.send_message(message)
@@ -1113,6 +1272,11 @@ class QueueProcessor:
logger.debug(f"[QueueProcessor] Sending busy status for {len(queued_jobs)} queued jobs")
for job_info in queued_jobs:
# 快照可能已过期:在遍历过程中 end_job() 可能已将此 job 移至 READY
# 此时不应再发送 busy/need_more否则会覆盖已发出的 free=True 通知
if job_info.status != JobStatus.QUEUE:
continue
message = {
"action": "report_action_state",
"data": {
@@ -1122,13 +1286,13 @@ class QueueProcessor:
"task_id": job_info.task_id,
"job_id": job_info.job_id,
"free": False,
"need_more": 10,
"need_more": 10 + 1,
},
}
success = self.message_processor.send_message(message)
job_log = format_job_log(job_info.job_id, job_info.task_id, job_info.device_id, job_info.action_name)
if success:
logger.debug(f"[QueueProcessor] Sent busy/need_more for queued job {job_log}")
logger.trace(f"[QueueProcessor] Sent busy/need_more for queued job {job_log}")
else:
logger.warning(f"[QueueProcessor] Failed to send busy status for job {job_log}")
@@ -1151,7 +1315,7 @@ class QueueProcessor:
job_info.action_name,
)
logger.info(f"[QueueProcessor] Job {job_log} completed with status: {status}")
logger.trace(f"[QueueProcessor] Job {job_log} completed with status: {status}")
# 结束任务,获取下一个可执行的任务
next_job = self.device_manager.end_job(job_id)
@@ -1171,8 +1335,8 @@ class QueueProcessor:
},
}
self.message_processor.send_message(message)
next_job_log = format_job_log(next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name)
logger.info(f"[QueueProcessor] Notified next job {next_job_log} can start")
# next_job_log = format_job_log(next_job.job_id, next_job.task_id, next_job.device_id, next_job.action_name)
# logger.debug(f"[QueueProcessor] Notified next job {next_job_log} can start")
# 立即触发下一轮状态检查
self.notify_queue_update()
@@ -1205,6 +1369,10 @@ class WebSocketClient(BaseCommunicationClient):
self.message_processor = MessageProcessor(self.websocket_url, self.send_queue, self.device_manager)
self.queue_processor = QueueProcessor(self.device_manager, self.message_processor)
# running状态debounce缓存: {job_id: (last_send_timestamp, last_feedback_data)}
self._job_running_last_sent: Dict[str, tuple] = {}
self._job_running_debounce_interval: float = 10.0 # 秒
# 设置相互引用
self.message_processor.set_queue_processor(self.queue_processor)
self.message_processor.set_websocket_client(self)
@@ -1261,8 +1429,8 @@ class WebSocketClient(BaseCommunicationClient):
message = {"action": "normal_exit", "data": {"session_id": session_id}}
self.message_processor.send_message(message)
logger.info(f"[WebSocketClient] Sent normal_exit message with session_id: {session_id}")
# 给一点时间让消息发送出去
time.sleep(1)
# send_handler 每100ms检查一次队列等300ms足以让消息发
time.sleep(0.3)
except Exception as e:
logger.warning(f"[WebSocketClient] Failed to send normal_exit message: {str(e)}")
@@ -1294,7 +1462,7 @@ class WebSocketClient(BaseCommunicationClient):
},
}
self.message_processor.send_message(message)
logger.trace(f"[WebSocketClient] Device status published: {device_id}.{property_name}")
# logger.trace(f"[WebSocketClient] Device status published: {device_id}.{property_name}")
def publish_job_status(
self, feedback_data: dict, item: QueueItem, status: str, return_info: Optional[dict] = None
@@ -1304,22 +1472,32 @@ class WebSocketClient(BaseCommunicationClient):
logger.debug(f"[WebSocketClient] Not connected, cannot publish job status for job_id: {item.job_id}")
return
job_log = format_job_log(item.job_id, item.task_id, item.device_id, item.action_name)
# 拦截最终结果状态,与原版本逻辑一致
if status in ["success", "failed"]:
self._job_running_last_sent.pop(item.job_id, None)
host_node = HostNode.get_instance(0)
if host_node:
# 从HostNode的device_action_status中移除job_id
try:
host_node._device_action_status[item.device_action_key].job_ids.pop(item.job_id, None)
except (KeyError, AttributeError):
logger.warning(f"[WebSocketClient] Failed to remove job {item.job_id} from HostNode status")
logger.info(f"[WebSocketClient] Intercepting final status for job_id: {item.job_id} - {status}")
# 通知队列处理器job完成包括timeout的job
self.queue_processor.handle_job_completed(item.job_id, status)
# 发送job状态消息
# running状态按job_id做debounce内容变化时仍然上报
if status == "running":
now = time.time()
cached = self._job_running_last_sent.get(item.job_id)
if cached is not None:
last_ts, last_data = cached
if now - last_ts < self._job_running_debounce_interval and last_data == feedback_data:
logger.trace(f"[WebSocketClient] Job status debounced (skip): {job_log} - {status}")
return
self._job_running_last_sent[item.job_id] = (now, feedback_data)
message = {
"action": "job_status",
"data": {
@@ -1335,7 +1513,6 @@ class WebSocketClient(BaseCommunicationClient):
}
self.message_processor.send_message(message)
job_log = format_job_log(item.job_id, item.task_id, item.device_id, item.action_name)
logger.trace(f"[WebSocketClient] Job status published: {job_log} - {status}")
def send_ping(self, ping_id: str, timestamp: float) -> None:
@@ -1381,7 +1558,9 @@ class WebSocketClient(BaseCommunicationClient):
if host_node:
# 获取设备信息
for device_id, namespace in host_node.devices_names.items():
device_key = f"{namespace}/{device_id}" if namespace.startswith("/") else f"/{namespace}/{device_id}"
device_key = (
f"{namespace}/{device_id}" if namespace.startswith("/") else f"/{namespace}/{device_id}"
)
is_online = device_key in host_node._online_devices
# 获取设备的动作信息
@@ -1395,14 +1574,16 @@ class WebSocketClient(BaseCommunicationClient):
"action_type": str(type(client).__name__),
}
devices.append({
"device_id": device_id,
"namespace": namespace,
"device_key": device_key,
"is_online": is_online,
"machine_name": host_node.device_machine_names.get(device_id, machine_name),
"actions": actions,
})
devices.append(
{
"device_id": device_id,
"namespace": namespace,
"device_key": device_key,
"is_online": is_online,
"machine_name": host_node.device_machine_names.get(device_id, machine_name),
"actions": actions,
}
)
logger.info(f"[WebSocketClient] Collected {len(devices)} devices for host_ready")
except Exception as e:

View File

@@ -95,8 +95,29 @@ def get_vessel_liquid_volume(G: nx.DiGraph, vessel: str) -> float:
return total_volume
def is_integrated_pump(node_name):
return "pump" in node_name and "valve" in node_name
def is_integrated_pump(node_class: str, node_name: str = "") -> bool:
"""
判断是否为泵阀一体设备
"""
class_lower = (node_class or "").lower()
name_lower = (node_name or "").lower()
if "pump" not in class_lower and "pump" not in name_lower:
return False
integrated_markers = [
"valve",
"pump_valve",
"pumpvalve",
"integrated",
"transfer_pump",
]
for marker in integrated_markers:
if marker in class_lower or marker in name_lower:
return True
return False
def find_connected_pump(G, valve_node):
@@ -186,7 +207,9 @@ def build_pump_valve_maps(G, pump_backbone):
debug_print(f"🔧 过滤后的骨架: {filtered_backbone}")
for node in filtered_backbone:
if is_integrated_pump(G.nodes[node]["class"]):
node_data = G.nodes.get(node, {})
node_class = node_data.get("class", "") or ""
if is_integrated_pump(node_class, node):
pumps_from_node[node] = node
valve_from_node[node] = node
debug_print(f" - 集成泵-阀: {node}")

View File

@@ -22,6 +22,9 @@ class BasicConfig:
startup_json_path = None # 填写绝对路径
disable_browser = False # 禁止浏览器自动打开
port = 8002 # 本地HTTP服务
check_mode = False # CI 检查模式,用于验证 registry 导入和文件一致性
test_mode = False # 测试模式,所有动作不实际执行,返回模拟结果
extra_resource = False # 是否加载lab_开头的额外资源
# 'TRACE', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'
log_level: Literal["TRACE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"] = "DEBUG"
@@ -38,7 +41,7 @@ class BasicConfig:
class WSConfig:
reconnect_interval = 5 # 重连间隔(秒)
max_reconnect_attempts = 999 # 最大重连次数
ping_interval = 30 # ping间隔
ping_interval = 20 # ping间隔
# HTTP配置
@@ -144,5 +147,5 @@ def load_config(config_path=None):
traceback.print_exc()
exit(1)
else:
config_path = os.path.join(os.path.dirname(__file__), "local_config.py")
config_path = os.path.join(os.path.dirname(__file__), "example_config.py")
load_config(config_path)

File diff suppressed because it is too large Load Diff

View File

@@ -1,4 +1,3 @@
from abc import abstractmethod
from functools import wraps
import inspect

File diff suppressed because it is too large Load Diff

View File

@@ -30,9 +30,32 @@ from pylabrobot.liquid_handling.standard import (
ResourceMove,
ResourceDrop,
)
from pylabrobot.resources import ResourceHolder, ResourceStack, Tip, Deck, Plate, Well, TipRack, Resource, Container, Coordinate, TipSpot, Trash, PlateAdapter, TubeRack
from pylabrobot.resources import (
ResourceHolder,
ResourceStack,
Tip,
Deck,
Plate,
Well,
TipRack,
Resource,
Container,
Coordinate,
TipSpot,
Trash,
PlateAdapter,
TubeRack,
)
from unilabos.devices.liquid_handling.liquid_handler_abstract import LiquidHandlerAbstract, SimpleReturn
from unilabos.devices.liquid_handling.liquid_handler_abstract import (
LiquidHandlerAbstract,
SimpleReturn,
SetLiquidReturn,
SetLiquidFromPlateReturn,
TransferLiquidReturn,
)
from unilabos.registry.placeholder_type import ResourceSlot
from unilabos.resources.resource_tracker import ResourceTreeSet
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
@@ -68,19 +91,103 @@ class PRCXI9300Deck(Deck):
该类定义了 PRCXI 9300 的工作台布局和槽位信息。
"""
def __init__(self, name: str, size_x: float, size_y: float, size_z: float, **kwargs):
super().__init__(name, size_x, size_y, size_z)
self.slots = [None] * 16 # PRCXI 9300/9320 最大有 16 个槽位
self.slot_locations = [Coordinate(0, 0, 0)] * 16
# T1-T16 默认位置 (4列×4行)
_DEFAULT_SITE_POSITIONS = [
(0, 0, 0), (138, 0, 0), (276, 0, 0), (414, 0, 0), # T1-T4
(0, 96, 0), (138, 96, 0), (276, 96, 0), (414, 96, 0), # T5-T8
(0, 192, 0), (138, 192, 0), (276, 192, 0), (414, 192, 0), # T9-T12
(0, 288, 0), (138, 288, 0), (276, 288, 0), (414, 288, 0), # T13-T16
]
_DEFAULT_SITE_SIZE = {"width": 128.0, "height": 86, "depth": 0}
_DEFAULT_CONTENT_TYPE = ["plate", "tip_rack", "plates", "tip_racks", "tube_rack", "adaptor"]
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
sites: Optional[List[Dict[str, Any]]] = None, **kwargs):
super().__init__(size_x, size_y, size_z, name)
if sites is not None:
self.sites: List[Dict[str, Any]] = [dict(s) for s in sites]
else:
self.sites = []
for i, (x, y, z) in enumerate(self._DEFAULT_SITE_POSITIONS):
self.sites.append({
"label": f"T{i + 1}",
"visible": True,
"position": {"x": x, "y": y, "z": z},
"size": dict(self._DEFAULT_SITE_SIZE),
"content_type": list(self._DEFAULT_CONTENT_TYPE),
})
# _ordering: label -> None, 用于外部通过 list(keys()).index(site) 将 Tn 转换为 spot index
self._ordering = collections.OrderedDict(
(site["label"], None) for site in self.sites
)
def _get_site_location(self, idx: int) -> Coordinate:
pos = self.sites[idx]["position"]
return Coordinate(pos["x"], pos["y"], pos["z"])
def _get_site_resource(self, idx: int) -> Optional[Resource]:
site_loc = self._get_site_location(idx)
for child in self.children:
if child.location == site_loc:
return child
return None
def assign_child_resource(
self,
resource: Resource,
location: Optional[Coordinate] = None,
reassign: bool = True,
spot: Optional[int] = None,
):
idx = spot
if spot is not None:
idx = spot
else:
for i, site in enumerate(self.sites):
site_loc = self._get_site_location(i)
if site.get("label") == resource.name:
idx = i
break
if location is not None and site_loc == location:
idx = i
break
if idx is None:
for i in range(len(self.sites)):
if self._get_site_resource(i) is None:
idx = i
break
if idx is None:
raise ValueError(f"No available site on deck '{self.name}' for resource '{resource.name}'")
if not reassign and self._get_site_resource(idx) is not None:
raise ValueError(f"Site {idx} ('{self.sites[idx]['label']}') is already occupied")
loc = self._get_site_location(idx)
super().assign_child_resource(resource, location=loc, reassign=reassign)
def assign_child_at_slot(self, resource: Resource, slot: int, reassign: bool = False) -> None:
if self.slots[slot - 1] is not None and not reassign:
raise ValueError(f"Spot {slot} is already occupied")
self.assign_child_resource(resource, spot=slot - 1, reassign=reassign)
self.slots[slot - 1] = resource
super().assign_child_resource(resource, location=self.slot_locations[slot - 1])
def serialize(self) -> dict:
data = super().serialize()
sites_out = []
for i, site in enumerate(self.sites):
occupied = self._get_site_resource(i)
sites_out.append({
"label": site["label"],
"visible": site.get("visible", True),
"occupied_by": occupied.name if occupied is not None else None,
"position": site["position"],
"size": site["size"],
"content_type": site["content_type"],
})
data["sites"] = sites_out
return data
class PRCXI9300Container(Plate):
class PRCXI9300Container(Container):
"""PRCXI 9300 的专用 Container 类,继承自 Plate用于槽位定位和未知模块。
该类定义了 PRCXI 9300 的工作台布局和槽位信息。
@@ -93,11 +200,10 @@ class PRCXI9300Container(Plate):
size_y: float,
size_z: float,
category: str,
ordering: collections.OrderedDict,
model: Optional[str] = None,
**kwargs,
):
super().__init__(name, size_x, size_y, size_z, category=category, ordering=ordering, model=model)
super().__init__(name, size_x, size_y, size_z, category=category, model=model)
self._unilabos_state = {}
def load_state(self, state: Dict[str, Any]) -> None:
@@ -108,74 +214,81 @@ class PRCXI9300Container(Plate):
def serialize_state(self) -> Dict[str, Dict[str, Any]]:
data = super().serialize_state()
data.update(self._unilabos_state)
return data
return data
class PRCXI9300Plate(Plate):
"""
"""
专用孔板类:
1. 继承自 PLR 原生 Plate保留所有物理特性。
2. 增加 material_info 参数,用于在初始化时直接绑定 Unilab UUID。
"""
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
category: str = "plate",
ordered_items: collections.OrderedDict = None,
ordering: Optional[collections.OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs):
def __init__(
self,
name: str,
size_x: float,
size_y: float,
size_z: float,
category: str = "plate",
ordered_items: collections.OrderedDict = None,
ordering: Optional[collections.OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs,
):
# 如果 ordered_items 不为 None直接使用
items = None
ordering_param = None
if ordered_items is not None:
items = ordered_items
elif ordering is not None:
# 检查 ordering 中的值是否是字符串(从 JSON 反序列化时的情况)
# 如果是字符串,说明这是位置名称,需要让 Plate 自己创建 Well 对象
# 我们只传递位置信息(键),不传递值,使用 ordering 参数
if ordering and isinstance(next(iter(ordering.values()), None), str):
# ordering 的值是字符串,只使用键(位置信息)创建新的 OrderedDict
# 传递 ordering 参数而不是 ordered_items让 Plate 自己创建 Well 对象
items = None
# 使用 ordering 参数,只包含位置信息(键)
ordering_param = collections.OrderedDict((k, None) for k in ordering.keys())
if ordering:
values = list(ordering.values())
value = values[0]
if isinstance(value, str):
# ordering 的值是字符串,只使用键(位置信息)创建新的 OrderedDict
# 传递 ordering 参数而不是 ordered_items让 Plate 自己创建 Well 对象
items = None
# 使用 ordering 参数,只包含位置信息(键)
ordering_param = collections.OrderedDict((k, None) for k in ordering.keys())
elif value is None:
ordering_param = ordering
else:
# ordering 的值已经是对象,可以直接使用
items = ordering
ordering_param = None
else:
items = None
ordering_param = None
# 根据情况传递不同的参数
if items is not None:
super().__init__(name, size_x, size_y, size_z,
ordered_items=items,
category=category,
model=model, **kwargs)
super().__init__(
name, size_x, size_y, size_z, ordered_items=items, category=category, model=model, **kwargs
)
elif ordering_param is not None:
# 传递 ordering 参数,让 Plate 自己创建 Well 对象
super().__init__(name, size_x, size_y, size_z,
ordering=ordering_param,
category=category,
model=model, **kwargs)
super().__init__(
name, size_x, size_y, size_z, ordering=ordering_param, category=category, model=model, **kwargs
)
else:
super().__init__(name, size_x, size_y, size_z,
category=category,
model=model, **kwargs)
super().__init__(name, size_x, size_y, size_z, category=category, model=model, **kwargs)
self._unilabos_state = {}
if material_info:
self._unilabos_state["Material"] = material_info
def load_state(self, state: Dict[str, Any]) -> None:
super().load_state(state)
self._unilabos_state = state
def serialize_state(self) -> Dict[str, Dict[str, Any]]:
try:
data = super().serialize_state()
except AttributeError:
data = {}
if hasattr(self, '_unilabos_state') and self._unilabos_state:
if hasattr(self, "_unilabos_state") and self._unilabos_state:
safe_state = {}
for k, v in self._unilabos_state.items():
# 如果是 Material 字典,深入检查
@@ -188,35 +301,45 @@ class PRCXI9300Plate(Plate):
else:
# 打印日志提醒(可选)
# print(f"Warning: Removing non-serializable key {mk} from {self.name}")
pass
pass
safe_state[k] = safe_material
# 其他顶层属性也进行类型检查
elif isinstance(v, (str, int, float, bool, list, dict, type(None))):
safe_state[k] = v
data.update(safe_state)
return data # 其他顶层属性也进行类型检查
return data # 其他顶层属性也进行类型检查
class PRCXI9300TipRack(TipRack):
""" 专用吸头盒类 """
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
category: str = "tip_rack",
ordered_items: collections.OrderedDict = None,
ordering: Optional[collections.OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs):
"""专用吸头盒类"""
def __init__(
self,
name: str,
size_x: float,
size_y: float,
size_z: float,
category: str = "tip_rack",
ordered_items: collections.OrderedDict = None,
ordering: Optional[collections.OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs,
):
# 如果 ordered_items 不为 None直接使用
if ordered_items is not None:
items = ordered_items
elif ordering is not None:
# 检查 ordering 中的值是否是字符串(从 JSON 反序列化时的情况)
# 如果是字符串,说明这是位置名称,需要让 TipRack 自己创建 Tip 对象
# 我们只传递位置信息(键),不传递值,使用 ordering 参数
if ordering and isinstance(next(iter(ordering.values()), None), str):
# ordering 的值是字符串,只使用键(位置信息)创建新的 OrderedDict
# 检查 ordering 中的值类型来决定如何处理:
# - 字符串值(从 JSON 反序列化): 只用键创建 ordering_param
# - None 值(从第二次往返序列化): 同样只用键创建 ordering_param
# - 对象值(已经是实际的 Resource 对象): 直接作为 ordered_items 使用
first_val = next(iter(ordering.values()), None) if ordering else None
if not ordering or first_val is None or isinstance(first_val, str):
# ordering 的值是字符串或 None只使用键位置信息创建新的 OrderedDict
# 传递 ordering 参数而不是 ordered_items让 TipRack 自己创建 Tip 对象
items = None
# 使用 ordering 参数,只包含位置信息(键)
ordering_param = collections.OrderedDict((k, None) for k in ordering.keys())
else:
# ordering 的值已经是对象,可以直接使用
@@ -225,27 +348,23 @@ class PRCXI9300TipRack(TipRack):
else:
items = None
ordering_param = None
# 根据情况传递不同的参数
if items is not None:
super().__init__(name, size_x, size_y, size_z,
ordered_items=items,
category=category,
model=model, **kwargs)
super().__init__(
name, size_x, size_y, size_z, ordered_items=items, category=category, model=model, **kwargs
)
elif ordering_param is not None:
# 传递 ordering 参数,让 TipRack 自己创建 Tip 对象
super().__init__(name, size_x, size_y, size_z,
ordering=ordering_param,
category=category,
model=model, **kwargs)
super().__init__(
name, size_x, size_y, size_z, ordering=ordering_param, category=category, model=model, **kwargs
)
else:
super().__init__(name, size_x, size_y, size_z,
category=category,
model=model, **kwargs)
super().__init__(name, size_x, size_y, size_z, category=category, model=model, **kwargs)
self._unilabos_state = {}
if material_info:
self._unilabos_state["Material"] = material_info
def load_state(self, state: Dict[str, Any]) -> None:
super().load_state(state)
self._unilabos_state = state
@@ -255,7 +374,7 @@ class PRCXI9300TipRack(TipRack):
data = super().serialize_state()
except AttributeError:
data = {}
if hasattr(self, '_unilabos_state') and self._unilabos_state:
if hasattr(self, "_unilabos_state") and self._unilabos_state:
safe_state = {}
for k, v in self._unilabos_state.items():
# 如果是 Material 字典,深入检查
@@ -268,26 +387,33 @@ class PRCXI9300TipRack(TipRack):
else:
# 打印日志提醒(可选)
# print(f"Warning: Removing non-serializable key {mk} from {self.name}")
pass
pass
safe_state[k] = safe_material
# 其他顶层属性也进行类型检查
elif isinstance(v, (str, int, float, bool, list, dict, type(None))):
safe_state[k] = v
data.update(safe_state)
return data
class PRCXI9300Trash(Trash):
"""PRCXI 9300 的专用 Trash 类,继承自 Trash。
该类定义了 PRCXI 9300 的工作台布局和槽位信息。
"""
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
category: str = "trash",
material_info: Optional[Dict[str, Any]] = None,
**kwargs):
def __init__(
self,
name: str,
size_x: float,
size_y: float,
size_z: float,
category: str = "trash",
material_info: Optional[Dict[str, Any]] = None,
**kwargs,
):
if name != "trash":
print(f"Warning: PRCXI9300Trash usually expects name='trash' for backend logic, but got '{name}'.")
super().__init__(name, size_x, size_y, size_z, **kwargs)
@@ -306,7 +432,7 @@ class PRCXI9300Trash(Trash):
data = super().serialize_state()
except AttributeError:
data = {}
if hasattr(self, '_unilabos_state') and self._unilabos_state:
if hasattr(self, "_unilabos_state") and self._unilabos_state:
safe_state = {}
for k, v in self._unilabos_state.items():
# 如果是 Material 字典,深入检查
@@ -319,42 +445,51 @@ class PRCXI9300Trash(Trash):
else:
# 打印日志提醒(可选)
# print(f"Warning: Removing non-serializable key {mk} from {self.name}")
pass
pass
safe_state[k] = safe_material
# 其他顶层属性也进行类型检查
elif isinstance(v, (str, int, float, bool, list, dict, type(None))):
safe_state[k] = v
data.update(safe_state)
return data
class PRCXI9300TubeRack(TubeRack):
"""
专用管架类:用于 EP 管架、试管架等。
继承自 PLR 的 TubeRack并支持注入 material_info (UUID)。
"""
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
category: str = "tube_rack",
items: Optional[Dict[str, Any]] = None,
ordered_items: Optional[OrderedDict] = None,
ordering: Optional[OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs):
def __init__(
self,
name: str,
size_x: float,
size_y: float,
size_z: float,
category: str = "tube_rack",
items: Optional[Dict[str, Any]] = None,
ordered_items: Optional[OrderedDict] = None,
ordering: Optional[OrderedDict] = None,
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
**kwargs,
):
# 如果 ordered_items 不为 None直接使用
if ordered_items is not None:
items_to_pass = ordered_items
ordering_param = None
elif ordering is not None:
# 检查 ordering 中的值是否是字符串(从 JSON 反序列化时的情况)
# 如果是字符串,说明这是位置名称,需要让 TubeRack 自己创建 Tube 对象
# 我们只传递位置信息(键),不传递值,使用 ordering 参数
if ordering and isinstance(next(iter(ordering.values()), None), str):
# ordering 的值是字符串,只使用键(位置信息)创建新的 OrderedDict
# 检查 ordering 中的值类型来决定如何处理:
# - 字符串值(从 JSON 反序列化): 只用键创建 ordering_param
# - None 值(从第二次往返序列化): 同样只用键创建 ordering_param
# - 对象值(已经是实际的 Resource 对象): 直接作为 ordered_items 使用
first_val = next(iter(ordering.values()), None) if ordering else None
if not ordering or first_val is None or isinstance(first_val, str):
# ordering 的值是字符串或 None只使用键位置信息创建新的 OrderedDict
# 传递 ordering 参数而不是 ordered_items让 TubeRack 自己创建 Tube 对象
items_to_pass = None
# 使用 ordering 参数,只包含位置信息(键)
ordering_param = collections.OrderedDict((k, None) for k in ordering.keys())
else:
# ordering 的值已经是对象,可以直接使用
@@ -367,24 +502,16 @@ class PRCXI9300TubeRack(TubeRack):
else:
items_to_pass = None
ordering_param = None
# 根据情况传递不同的参数
if items_to_pass is not None:
super().__init__(name, size_x, size_y, size_z,
ordered_items=items_to_pass,
model=model,
**kwargs)
super().__init__(name, size_x, size_y, size_z, ordered_items=items_to_pass, model=model, **kwargs)
elif ordering_param is not None:
# 传递 ordering 参数,让 TubeRack 自己创建 Tube 对象
super().__init__(name, size_x, size_y, size_z,
ordering=ordering_param,
model=model,
**kwargs)
super().__init__(name, size_x, size_y, size_z, ordering=ordering_param, model=model, **kwargs)
else:
super().__init__(name, size_x, size_y, size_z,
model=model,
**kwargs)
super().__init__(name, size_x, size_y, size_z, model=model, **kwargs)
self._unilabos_state = {}
if material_info:
self._unilabos_state["Material"] = material_info
@@ -394,7 +521,7 @@ class PRCXI9300TubeRack(TubeRack):
data = super().serialize_state()
except AttributeError:
data = {}
if hasattr(self, '_unilabos_state') and self._unilabos_state:
if hasattr(self, "_unilabos_state") and self._unilabos_state:
safe_state = {}
for k, v in self._unilabos_state.items():
# 如果是 Material 字典,深入检查
@@ -407,33 +534,41 @@ class PRCXI9300TubeRack(TubeRack):
else:
# 打印日志提醒(可选)
# print(f"Warning: Removing non-serializable key {mk} from {self.name}")
pass
pass
safe_state[k] = safe_material
# 其他顶层属性也进行类型检查
elif isinstance(v, (str, int, float, bool, list, dict, type(None))):
safe_state[k] = v
data.update(safe_state)
return data
class PRCXI9300PlateAdapter(PlateAdapter):
"""
专用板式适配器类:用于承载 Plate 的底座(如 PCR 适配器、磁吸架等)。
支持注入 material_info (UUID)。
"""
def __init__(self, name: str, size_x: float, size_y: float, size_z: float,
category: str = "plate_adapter",
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
# 参数给予默认值 (标准96孔板尺寸)
adapter_hole_size_x: float = 127.76,
adapter_hole_size_y: float = 85.48,
adapter_hole_size_z: float = 10.0, # 假设凹槽深度或板子放置高度
dx: Optional[float] = None,
dy: Optional[float] = None,
dz: float = 0.0, # 默认Z轴偏移
**kwargs):
def __init__(
self,
name: str,
size_x: float,
size_y: float,
size_z: float,
category: str = "plate_adapter",
model: Optional[str] = None,
material_info: Optional[Dict[str, Any]] = None,
# 参数给予默认值 (标准96孔板尺寸)
adapter_hole_size_x: float = 127.76,
adapter_hole_size_y: float = 85.48,
adapter_hole_size_z: float = 10.0, # 假设凹槽深度或板子放置高度
dx: Optional[float] = None,
dy: Optional[float] = None,
dz: float = 0.0, # 默认Z轴偏移
**kwargs,
):
# 自动居中计算:如果未指定 dx/dy则根据适配器尺寸和孔尺寸计算居中位置
if dx is None:
dx = (size_x - adapter_hole_size_x) / 2
@@ -441,20 +576,20 @@ class PRCXI9300PlateAdapter(PlateAdapter):
dy = (size_y - adapter_hole_size_y) / 2
super().__init__(
name=name,
size_x=size_x,
size_y=size_y,
size_z=size_z,
name=name,
size_x=size_x,
size_y=size_y,
size_z=size_z,
dx=dx,
dy=dy,
dz=dz,
adapter_hole_size_x=adapter_hole_size_x,
adapter_hole_size_y=adapter_hole_size_y,
adapter_hole_size_z=adapter_hole_size_z,
model=model,
**kwargs
model=model,
**kwargs,
)
self._unilabos_state = {}
if material_info:
self._unilabos_state["Material"] = material_info
@@ -464,7 +599,7 @@ class PRCXI9300PlateAdapter(PlateAdapter):
data = super().serialize_state()
except AttributeError:
data = {}
if hasattr(self, '_unilabos_state') and self._unilabos_state:
if hasattr(self, "_unilabos_state") and self._unilabos_state:
safe_state = {}
for k, v in self._unilabos_state.items():
# 如果是 Material 字典,深入检查
@@ -477,15 +612,16 @@ class PRCXI9300PlateAdapter(PlateAdapter):
else:
# 打印日志提醒(可选)
# print(f"Warning: Removing non-serializable key {mk} from {self.name}")
pass
pass
safe_state[k] = safe_material
# 其他顶层属性也进行类型检查
elif isinstance(v, (str, int, float, bool, list, dict, type(None))):
safe_state[k] = v
data.update(safe_state)
return data
class PRCXI9300Handler(LiquidHandlerAbstract):
support_touch_tip = False
@@ -498,7 +634,7 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
def __init__(
self,
deck: Deck,
deck: PRCXI9300Deck,
host: str,
port: int,
timeout: float,
@@ -512,14 +648,16 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
is_9320=False,
):
tablets_info = []
count = 0
for child in deck.children:
if child.children:
if "Material" in child.children[0]._unilabos_state:
number = int(child.name.replace("T", ""))
tablets_info.append(
WorkTablets(Number=number, Code=f"T{number}", Material=child.children[0]._unilabos_state["Material"])
for site_id in range(len(deck.sites)):
child = deck._get_site_resource(site_id)
# 如果放其他类型的物料,是不可以的
if hasattr(child, "_unilabos_state") and "Material" in child._unilabos_state:
number = site_id + 1
tablets_info.append(
WorkTablets(
Number=number, Code=f"T{number}", Material=child._unilabos_state["Material"]
)
)
if is_9320:
print("当前设备是9320")
# 始终初始化 step_mode 属性
@@ -538,9 +676,14 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
super().post_init(ros_node)
self._unilabos_backend.post_init(ros_node)
def set_liquid(self, wells: list[Well], liquid_names: list[str], volumes: list[float]) -> SimpleReturn:
def set_liquid(self, wells: list[Well], liquid_names: list[str], volumes: list[float]) -> SetLiquidReturn:
return super().set_liquid(wells, liquid_names, volumes)
def set_liquid_from_plate(
self, plate: ResourceSlot, well_names: list[str], liquid_names: list[str], volumes: list[float]
) -> SetLiquidFromPlateReturn:
return super().set_liquid_from_plate(plate, well_names, liquid_names, volumes)
def set_group(self, group_name: str, wells: List[Well], volumes: List[float]):
return super().set_group(group_name, wells, volumes)
@@ -660,7 +803,7 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
mix_liquid_height: Optional[float] = None,
delays: Optional[List[int]] = None,
none_keys: List[str] = [],
):
) -> TransferLiquidReturn:
return await super().transfer_liquid(
sources,
targets,
@@ -799,7 +942,8 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
return await self._unilabos_backend.shaker_action(time, module_no, amplitude, is_wait)
async def heater_action(self, temperature: float, time: int):
return await self._unilabos_backend.heater_action(temperature, time)
return await self._unilabos_backend.heater_action(temperature, time)
async def move_plate(
self,
plate: Plate,
@@ -822,10 +966,11 @@ class PRCXI9300Handler(LiquidHandlerAbstract):
drop_direction,
pickup_direction,
pickup_distance_from_top,
target_plate_number = to,
target_plate_number=to,
**backend_kwargs,
)
class PRCXI9300Backend(LiquidHandlerBackend):
"""PRCXI 9300 的后端实现,继承自 LiquidHandlerBackend。
@@ -878,31 +1023,28 @@ class PRCXI9300Backend(LiquidHandlerBackend):
self.steps_todo_list.append(step)
return step
async def pick_up_resource(self, pickup: ResourcePickup, **backend_kwargs):
resource=pickup.resource
offset=pickup.offset
pickup_distance_from_top=pickup.pickup_distance_from_top
direction=pickup.direction
resource = pickup.resource
offset = pickup.offset
pickup_distance_from_top = pickup.pickup_distance_from_top
direction = pickup.direction
plate_number = int(resource.parent.name.replace("T", ""))
is_whole_plate = True
balance_height = 0
step = self.api_client.clamp_jaw_pick_up(plate_number, is_whole_plate, balance_height)
self.steps_todo_list.append(step)
return step
async def drop_resource(self, drop: ResourceDrop, **backend_kwargs):
plate_number = None
target_plate_number = backend_kwargs.get("target_plate_number", None)
if target_plate_number is not None:
plate_number = int(target_plate_number.name.replace("T", ""))
is_whole_plate = True
balance_height = 0
if plate_number is None:
@@ -911,7 +1053,6 @@ class PRCXI9300Backend(LiquidHandlerBackend):
self.steps_todo_list.append(step)
return step
async def heater_action(self, temperature: float, time: int):
print(f"\n\nHeater action: temperature={temperature}, time={time}\n\n")
# return await self.api_client.heater_action(temperature, time)
@@ -968,7 +1109,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
error_code = self.api_client.get_error_code()
if error_code:
print(f"PRCXI9300 error code detected: {error_code}")
# 清除错误代码
self.api_client.clear_error_code()
print("PRCXI9300 error code cleared.")
@@ -976,11 +1117,11 @@ class PRCXI9300Backend(LiquidHandlerBackend):
# 执行重置
print("Starting PRCXI9300 reset...")
self.api_client.call("IAutomation", "Reset")
# 检查重置状态并等待完成
while not self.is_reset_ok:
print("Waiting for PRCXI9300 to reset...")
if hasattr(self, '_ros_node') and self._ros_node is not None:
if hasattr(self, "_ros_node") and self._ros_node is not None:
await self._ros_node.sleep(1)
else:
await asyncio.sleep(1)
@@ -998,7 +1139,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
"""Pick up tips from the specified resource."""
# INSERT_YOUR_CODE
# Ensure use_channels is converted to a list of ints if it's an array
if hasattr(use_channels, 'tolist'):
if hasattr(use_channels, "tolist"):
_use_channels = use_channels.tolist()
else:
_use_channels = list(use_channels) if use_channels is not None else None
@@ -1052,7 +1193,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
async def drop_tips(self, ops: List[Drop], use_channels: List[int] = None):
"""Pick up tips from the specified resource."""
if hasattr(use_channels, 'tolist'):
if hasattr(use_channels, "tolist"):
_use_channels = use_channels.tolist()
else:
_use_channels = list(use_channels) if use_channels is not None else None
@@ -1135,7 +1276,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
none_keys: List[str] = [],
):
"""Mix liquid in the specified resources."""
plate_indexes = []
for op in targets:
deck = op.parent.parent.parent
@@ -1178,7 +1319,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
async def aspirate(self, ops: List[SingleChannelAspiration], use_channels: List[int] = None):
"""Aspirate liquid from the specified resources."""
if hasattr(use_channels, 'tolist'):
if hasattr(use_channels, "tolist"):
_use_channels = use_channels.tolist()
else:
_use_channels = list(use_channels) if use_channels is not None else None
@@ -1235,7 +1376,7 @@ class PRCXI9300Backend(LiquidHandlerBackend):
async def dispense(self, ops: List[SingleChannelDispense], use_channels: List[int] = None):
"""Dispense liquid into the specified resources."""
if hasattr(use_channels, 'tolist'):
if hasattr(use_channels, "tolist"):
_use_channels = use_channels.tolist()
else:
_use_channels = list(use_channels) if use_channels is not None else None
@@ -1416,7 +1557,6 @@ class PRCXI9300Api:
time.sleep(1)
return success
def call(self, service: str, method: str, params: Optional[list] = None) -> Any:
payload = json.dumps(
{"ServiceName": service, "MethodName": method, "Paramters": params or []}, separators=(",", ":")
@@ -1543,7 +1683,7 @@ class PRCXI9300Api:
assist_fun5: str = "",
liquid_method: str = "NormalDispense",
axis: str = "Left",
) -> Dict[str, Any]:
) -> Dict[str, Any]:
return {
"StepAxis": axis,
"Function": "Imbibing",
@@ -1621,7 +1761,7 @@ class PRCXI9300Api:
assist_fun5: str = "",
liquid_method: str = "NormalDispense",
axis: str = "Left",
) -> Dict[str, Any]:
) -> Dict[str, Any]:
return {
"StepAxis": axis,
"Function": "Blending",
@@ -1681,11 +1821,11 @@ class PRCXI9300Api:
"LiquidDispensingMethod": liquid_method,
}
def clamp_jaw_pick_up(self,
def clamp_jaw_pick_up(
self,
plate_no: int,
is_whole_plate: bool,
balance_height: int,
) -> Dict[str, Any]:
return {
"StepAxis": "ClampingJaw",
@@ -1695,7 +1835,7 @@ class PRCXI9300Api:
"HoleRow": 1,
"HoleCol": 1,
"BalanceHeight": balance_height,
"PlateOrHoleNum": f"T{plate_no}"
"PlateOrHoleNum": f"T{plate_no}",
}
def clamp_jaw_drop(
@@ -1703,7 +1843,6 @@ class PRCXI9300Api:
plate_no: int,
is_whole_plate: bool,
balance_height: int,
) -> Dict[str, Any]:
return {
"StepAxis": "ClampingJaw",
@@ -1713,7 +1852,7 @@ class PRCXI9300Api:
"HoleRow": 1,
"HoleCol": 1,
"BalanceHeight": balance_height,
"PlateOrHoleNum": f"T{plate_no}"
"PlateOrHoleNum": f"T{plate_no}",
}
def shaker_action(self, time: int, module_no: int, amplitude: int, is_wait: bool):
@@ -1726,6 +1865,7 @@ class PRCXI9300Api:
"AssistFun4": is_wait,
}
class DefaultLayout:
def __init__(self, product_name: str = "PRCXI9300"):
@@ -2104,7 +2244,9 @@ if __name__ == "__main__":
size_y=50,
size_z=10,
category="tip_rack",
ordered_items=collections.OrderedDict({k: f"{child_prefix}_{k}" for k, v in tip_racks["ordering"].items()}),
ordered_items=collections.OrderedDict(
{k: f"{child_prefix}_{k}" for k, v in tip_racks["ordering"].items()}
),
)
tip_rack_serialized = tip_rack.serialize()
tip_rack_serialized["parent_name"] = deck.name
@@ -2299,43 +2441,37 @@ if __name__ == "__main__":
A = tree_to_list([resource_plr_to_ulab(deck)])
with open("deck.json", "w", encoding="utf-8") as f:
A.insert(0, {
"id": "PRCXI",
"name": "PRCXI",
"parent": None,
"type": "device",
"class": "liquid_handler.prcxi",
"position": {
"x": 0,
"y": 0,
"z": 0
},
"config": {
"deck": {
"_resource_child_name": "PRCXI_Deck",
"_resource_type": "unilabos.devices.liquid_handling.prcxi.prcxi:PRCXI9300Deck"
A.insert(
0,
{
"id": "PRCXI",
"name": "PRCXI",
"parent": None,
"type": "device",
"class": "liquid_handler.prcxi",
"position": {"x": 0, "y": 0, "z": 0},
"config": {
"deck": {
"_resource_child_name": "PRCXI_Deck",
"_resource_type": "unilabos.devices.liquid_handling.prcxi.prcxi:PRCXI9300Deck",
},
"host": "192.168.0.121",
"port": 9999,
"timeout": 10.0,
"axis": "Right",
"channel_num": 1,
"setup": False,
"debug": True,
"simulator": True,
"matrix_id": "5de524d0-3f95-406c-86dd-f83626ebc7cb",
"is_9320": True,
},
"host": "192.168.0.121",
"port": 9999,
"timeout": 10.0,
"axis": "Right",
"channel_num": 1,
"setup": False,
"debug": True,
"simulator": True,
"matrix_id": "5de524d0-3f95-406c-86dd-f83626ebc7cb",
"is_9320": True
"data": {},
"children": ["PRCXI_Deck"],
},
"data": {},
"children": [
"PRCXI_Deck"
]
})
)
A[1]["parent"] = "PRCXI"
json.dump({
"nodes": A,
"links": []
}, f, indent=4, ensure_ascii=False)
json.dump({"nodes": A, "links": []}, f, indent=4, ensure_ascii=False)
handler = PRCXI9300Handler(
deck=deck,
@@ -2377,7 +2513,6 @@ if __name__ == "__main__":
time.sleep(5)
os._exit(0)
prcxi_api = PRCXI9300Api(host="192.168.0.121", port=9999)
prcxi_api.list_matrices()
prcxi_api.get_all_materials()

View File

@@ -19,10 +19,11 @@ from rclpy.node import Node
import re
class LiquidHandlerJointPublisher(BaseROS2DeviceNode):
def __init__(self,resources_config:list, resource_tracker, rate=50, device_id:str = "lh_joint_publisher", **kwargs):
def __init__(self,resources_config:list, resource_tracker, rate=50, device_id:str = "lh_joint_publisher", registry_name: str = "lh_joint_publisher", **kwargs):
super().__init__(
driver_instance=self,
device_id=device_id,
registry_name=registry_name,
status_types={},
action_value_mappings={},
hardware_interface={},

View File

@@ -0,0 +1,88 @@
"""虚拟样品演示设备 — 用于前端 sample tracking 功能的极简 demo"""
import asyncio
import logging
import random
import time
from typing import Any, Dict, List, Optional
class VirtualSampleDemo:
"""虚拟样品追踪演示设备,提供两种典型返回模式:
- measure_samples: 等长输入输出 (前端按 index 自动对齐)
- split_and_measure: 输出比输入长,附带 samples 列标注归属
"""
def __init__(self, device_id: Optional[str] = None, config: Optional[Dict[str, Any]] = None, **kwargs):
if device_id is None and "id" in kwargs:
device_id = kwargs.pop("id")
if config is None and "config" in kwargs:
config = kwargs.pop("config")
self.device_id = device_id or "unknown_sample_demo"
self.config = config or {}
self.logger = logging.getLogger(f"VirtualSampleDemo.{self.device_id}")
self.data: Dict[str, Any] = {"status": "Idle"}
# ------------------------------------------------------------------
# Action 1: 等长输入输出,无 samples 列
# ------------------------------------------------------------------
async def measure_samples(self, concentrations: List[float]) -> Dict[str, Any]:
"""模拟光度测量。absorbance = concentration * 0.05 + noise
入参和出参 list 长度相等,前端按 index 自动对齐。
"""
self.logger.info(f"measure_samples: concentrations={concentrations}")
absorbance = [round(c * 0.05 + random.gauss(0, 0.005), 4) for c in concentrations]
return {"concentrations": concentrations, "absorbance": absorbance}
# ------------------------------------------------------------------
# Action 2: 输出比输入长,带 samples 列
# ------------------------------------------------------------------
async def split_and_measure(self, volumes: List[float], split_count: int = 3) -> Dict[str, Any]:
"""将每个样品均分为 split_count 份后逐份测量。
返回的 list 长度 = len(volumes) * split_count
附带 samples 列标注每行属于第几个输入样品 (0-based index)。
"""
self.logger.info(f"split_and_measure: volumes={volumes}, split_count={split_count}")
out_volumes: List[float] = []
readings: List[float] = []
samples: List[int] = []
for idx, vol in enumerate(volumes):
split_vol = round(vol / split_count, 2)
for _ in range(split_count):
out_volumes.append(split_vol)
readings.append(round(random.uniform(0.1, 1.0), 4))
samples.append(idx)
return {"volumes": out_volumes, "readings": readings, "unilabos_samples": samples}
# ------------------------------------------------------------------
# Action 3: 入参和出参都带 samples 列(不等长)
# ------------------------------------------------------------------
async def analyze_readings(self, readings: List[float], samples: List[int]) -> Dict[str, Any]:
"""对 split_and_measure 的输出做二次分析。
入参 readings/samples 长度相同但 > 原始样品数,
出参同样带 samples 列,长度与入参一致。
"""
self.logger.info(f"analyze_readings: readings={readings}, samples={samples}")
scores: List[float] = []
passed: List[bool] = []
threshold = 0.4
for r in readings:
score = round(r * 100 + random.gauss(0, 2), 2)
scores.append(score)
passed.append(r >= threshold)
return {"scores": scores, "passed": passed, "unilabos_samples": samples}
# ------------------------------------------------------------------
# 状态属性
# ------------------------------------------------------------------
@property
def status(self) -> str:
return self.data.get("status", "Idle")

View File

@@ -15,35 +15,35 @@ class VirtualPumpMode(Enum):
class VirtualTransferPump:
"""虚拟转移泵类 - 模拟泵的基本功能,无需实际硬件 🚰"""
_ros_node: BaseROS2DeviceNode
def __init__(self, device_id: str = None, config: dict = None, **kwargs):
"""
初始化虚拟转移泵
Args:
device_id: 设备ID
config: 配置字典包含max_volume, port等参数
**kwargs: 其他参数,确保兼容性
"""
self.device_id = device_id or "virtual_transfer_pump"
# 从config或kwargs中获取参数确保类型正确
if config:
self.max_volume = float(config.get('max_volume', 25.0))
self.port = config.get('port', 'VIRTUAL')
self.max_volume = float(config.get("max_volume", 25.0))
self.port = config.get("port", "VIRTUAL")
else:
self.max_volume = float(kwargs.get('max_volume', 25.0))
self.port = kwargs.get('port', 'VIRTUAL')
self._transfer_rate = float(kwargs.get('transfer_rate', 0))
self.mode = kwargs.get('mode', VirtualPumpMode.Normal)
self.max_volume = float(kwargs.get("max_volume", 25.0))
self.port = kwargs.get("port", "VIRTUAL")
self._transfer_rate = float(kwargs.get("transfer_rate", 0))
self.mode = kwargs.get("mode", VirtualPumpMode.Normal)
# 状态变量 - 确保都是正确类型
self._status = "Idle"
self._position = 0.0 # float
self._max_velocity = 5.0 # float
self._max_velocity = 5.0 # float
self._current_volume = 0.0 # float
# 🚀 新增:快速模式设置 - 大幅缩短执行时间
@@ -52,14 +52,16 @@ class VirtualTransferPump:
self._fast_dispense_time = 1.0 # 快速喷射时间(秒)
self.logger = logging.getLogger(f"VirtualTransferPump.{self.device_id}")
print(f"🚰 === 虚拟转移泵 {self.device_id} 已创建 === ✨")
print(f"💨 快速模式: {'启用' if self._fast_mode else '禁用'} | 移动时间: {self._fast_move_time}s | 喷射时间: {self._fast_dispense_time}s")
print(
f"💨 快速模式: {'启用' if self._fast_mode else '禁用'} | 移动时间: {self._fast_move_time}s | 喷射时间: {self._fast_dispense_time}s"
)
print(f"📊 最大容量: {self.max_volume}mL | 端口: {self.port}")
def post_init(self, ros_node: BaseROS2DeviceNode):
self._ros_node = ros_node
async def initialize(self) -> bool:
"""初始化虚拟泵 🚀"""
self.logger.info(f"🔧 初始化虚拟转移泵 {self.device_id}")
@@ -68,33 +70,33 @@ class VirtualTransferPump:
self._current_volume = 0.0
self.logger.info(f"✅ 转移泵 {self.device_id} 初始化完成 🚰")
return True
async def cleanup(self) -> bool:
"""清理虚拟泵 🧹"""
self.logger.info(f"🧹 清理虚拟转移泵 {self.device_id} 🔚")
self._status = "Idle"
self.logger.info(f"✅ 转移泵 {self.device_id} 清理完成 💤")
return True
# 基本属性
@property
def status(self) -> str:
return self._status
@property
def position(self) -> float:
"""当前柱塞位置 (ml) 📍"""
return self._position
@property
def current_volume(self) -> float:
"""当前注射器中的体积 (ml) 💧"""
return self._current_volume
@property
def max_velocity(self) -> float:
return self._max_velocity
@property
def transfer_rate(self) -> float:
return self._transfer_rate
@@ -103,17 +105,17 @@ class VirtualTransferPump:
"""设置最大速度 (ml/s) 🌊"""
self._max_velocity = max(0.1, min(50.0, velocity)) # 限制在合理范围内
self.logger.info(f"🌊 设置最大速度为 {self._max_velocity} mL/s")
def get_status(self) -> str:
"""获取泵状态 📋"""
return self._status
async def _simulate_operation(self, duration: float):
"""模拟操作延时 ⏱️"""
self._status = "Busy"
await self._ros_node.sleep(duration)
self._status = "Idle"
def _calculate_duration(self, volume: float, velocity: float = None) -> float:
"""
计算操作持续时间 ⏰
@@ -121,10 +123,10 @@ class VirtualTransferPump:
"""
if velocity is None:
velocity = self._max_velocity
# 📊 计算理论时间(用于日志显示)
theoretical_duration = abs(volume) / velocity
# 🚀 如果启用快速模式,使用固定的快速时间
if self._fast_mode:
# 根据操作类型选择快速时间
@@ -132,13 +134,13 @@ class VirtualTransferPump:
actual_duration = self._fast_move_time
else: # 很小的操作
actual_duration = 0.5
self.logger.debug(f"⚡ 快速模式: 理论时间 {theoretical_duration:.2f}s → 实际时间 {actual_duration:.2f}s")
return actual_duration
else:
# 正常模式使用理论时间
return theoretical_duration
def _calculate_display_duration(self, volume: float, velocity: float = None) -> float:
"""
计算显示用的持续时间(用于日志) 📊
@@ -147,16 +149,16 @@ class VirtualTransferPump:
if velocity is None:
velocity = self._max_velocity
return abs(volume) / velocity
# 新的set_position方法 - 专门用于SetPumpPosition动作
async def set_position(self, position: float, max_velocity: float = None):
"""
移动到绝对位置 - 专门用于SetPumpPosition动作 🎯
Args:
position (float): 目标位置 (ml)
max_velocity (float): 移动速度 (ml/s)
Returns:
dict: 符合SetPumpPosition.action定义的结果
"""
@@ -164,19 +166,19 @@ class VirtualTransferPump:
# 验证并转换参数
target_position = float(position)
velocity = float(max_velocity) if max_velocity is not None else self._max_velocity
# 限制位置在有效范围内
target_position = max(0.0, min(float(self.max_volume), target_position))
# 计算移动距离
volume_to_move = abs(target_position - self._position)
# 📊 计算显示用的时间(用于日志)
display_duration = self._calculate_display_duration(volume_to_move, velocity)
# ⚡ 计算实际执行时间(快速模式)
actual_duration = self._calculate_duration(volume_to_move, velocity)
# 🎯 确定操作类型和emoji
if target_position > self._position:
operation_type = "吸液"
@@ -187,28 +189,34 @@ class VirtualTransferPump:
else:
operation_type = "保持"
operation_emoji = "📍"
self.logger.info(f"🎯 SET_POSITION: {operation_type} {operation_emoji}")
self.logger.info(f" 📍 位置: {self._position:.2f}mL → {target_position:.2f}mL (移动 {volume_to_move:.2f}mL)")
self.logger.info(
f" 📍 位置: {self._position:.2f}mL → {target_position:.2f}mL (移动 {volume_to_move:.2f}mL)"
)
self.logger.info(f" 🌊 速度: {velocity:.2f} mL/s")
self.logger.info(f" ⏰ 预计时间: {display_duration:.2f}s")
if self._fast_mode:
self.logger.info(f" ⚡ 快速模式: 实际用时 {actual_duration:.2f}s")
# 🚀 模拟移动过程
if volume_to_move > 0.01: # 只有当移动距离足够大时才显示进度
start_position = self._position
steps = 5 if actual_duration > 0.5 else 2 # 根据实际时间调整步数
step_duration = actual_duration / steps
self.logger.info(f"🚀 开始{operation_type}... {operation_emoji}")
for i in range(steps + 1):
# 计算当前位置和进度
progress = (i / steps) * 100 if steps > 0 else 100
current_pos = start_position + (target_position - start_position) * (i / steps) if steps > 0 else target_position
current_pos = (
start_position + (target_position - start_position) * (i / steps)
if steps > 0
else target_position
)
# 更新状态
if i < steps:
self._status = f"{operation_type}"
@@ -216,10 +224,10 @@ class VirtualTransferPump:
else:
self._status = "Idle"
status_emoji = ""
self._position = current_pos
self._current_volume = current_pos
# 显示进度每25%或最后一步)
if i == 0:
self.logger.debug(f" 🔄 {operation_type}开始: {progress:.0f}%")
@@ -227,7 +235,7 @@ class VirtualTransferPump:
self.logger.debug(f" 🔄 {operation_type}进度: {progress:.0f}%")
elif i == steps:
self.logger.info(f"{operation_type}完成: {progress:.0f}% | 当前位置: {current_pos:.2f}mL")
# 等待一小步时间
if i < steps and step_duration > 0:
await self._ros_node.sleep(step_duration)
@@ -236,25 +244,27 @@ class VirtualTransferPump:
self._position = target_position
self._current_volume = target_position
self.logger.info(f" 📍 微调完成: {target_position:.2f}mL")
# 确保最终位置准确
self._position = target_position
self._current_volume = target_position
self._status = "Idle"
# 📊 最终状态日志
if volume_to_move > 0.01:
self.logger.info(f"🎉 SET_POSITION 完成! 📍 最终位置: {self._position:.2f}mL | 💧 当前体积: {self._current_volume:.2f}mL")
self.logger.info(
f"🎉 SET_POSITION 完成! 📍 最终位置: {self._position:.2f}mL | 💧 当前体积: {self._current_volume:.2f}mL"
)
# 返回符合action定义的结果
return {
"success": True,
"message": f"✅ 成功移动到位置 {self._position:.2f}mL ({operation_type})",
"final_position": self._position,
"final_volume": self._current_volume,
"operation_type": operation_type
"operation_type": operation_type,
}
except Exception as e:
error_msg = f"❌ 设置位置失败: {str(e)}"
self.logger.error(error_msg)
@@ -262,134 +272,136 @@ class VirtualTransferPump:
"success": False,
"message": error_msg,
"final_position": self._position,
"final_volume": self._current_volume
"final_volume": self._current_volume,
}
# 其他泵操作方法
async def pull_plunger(self, volume: float, velocity: float = None):
"""
拉取柱塞(吸液) 📥
Args:
volume (float): 要拉取的体积 (ml)
velocity (float): 拉取速度 (ml/s)
"""
new_position = min(self.max_volume, self._position + volume)
actual_volume = new_position - self._position
if actual_volume <= 0:
self.logger.warning("⚠️ 无法吸液 - 已达到最大容量")
return
display_duration = self._calculate_display_duration(actual_volume, velocity)
actual_duration = self._calculate_duration(actual_volume, velocity)
self.logger.info(f"📥 开始吸液: {actual_volume:.2f}mL")
self.logger.info(f" 📍 位置: {self._position:.2f}mL → {new_position:.2f}mL")
self.logger.info(f" ⏰ 预计时间: {display_duration:.2f}s")
if self._fast_mode:
self.logger.info(f" ⚡ 快速模式: 实际用时 {actual_duration:.2f}s")
await self._simulate_operation(actual_duration)
self._position = new_position
self._current_volume = new_position
self.logger.info(f"✅ 吸液完成: {actual_volume:.2f}mL | 💧 当前体积: {self._current_volume:.2f}mL")
async def push_plunger(self, volume: float, velocity: float = None):
"""
推出柱塞(排液) 📤
Args:
volume (float): 要推出的体积 (ml)
velocity (float): 推出速度 (ml/s)
"""
new_position = max(0, self._position - volume)
actual_volume = self._position - new_position
if actual_volume <= 0:
self.logger.warning("⚠️ 无法排液 - 已达到最小容量")
return
display_duration = self._calculate_display_duration(actual_volume, velocity)
actual_duration = self._calculate_duration(actual_volume, velocity)
self.logger.info(f"📤 开始排液: {actual_volume:.2f}mL")
self.logger.info(f" 📍 位置: {self._position:.2f}mL → {new_position:.2f}mL")
self.logger.info(f" ⏰ 预计时间: {display_duration:.2f}s")
if self._fast_mode:
self.logger.info(f" ⚡ 快速模式: 实际用时 {actual_duration:.2f}s")
await self._simulate_operation(actual_duration)
self._position = new_position
self._current_volume = new_position
self.logger.info(f"✅ 排液完成: {actual_volume:.2f}mL | 💧 当前体积: {self._current_volume:.2f}mL")
# 便捷操作方法
async def aspirate(self, volume: float, velocity: float = None):
"""吸液操作 📥"""
await self.pull_plunger(volume, velocity)
async def dispense(self, volume: float, velocity: float = None):
"""排液操作 📤"""
await self.push_plunger(volume, velocity)
async def transfer(self, volume: float, aspirate_velocity: float = None, dispense_velocity: float = None):
"""转移操作(先吸后排) 🔄"""
self.logger.info(f"🔄 开始转移操作: {volume:.2f}mL")
# 吸液
await self.aspirate(volume, aspirate_velocity)
# 短暂停顿
self.logger.debug("⏸️ 短暂停顿...")
await self._ros_node.sleep(0.1)
# 排液
await self.dispense(volume, dispense_velocity)
async def empty_syringe(self, velocity: float = None):
"""清空注射器"""
await self.set_position(0, velocity)
async def fill_syringe(self, velocity: float = None):
"""充满注射器"""
await self.set_position(self.max_volume, velocity)
async def stop_operation(self):
"""停止当前操作"""
self._status = "Idle"
self.logger.info("Operation stopped")
# 状态查询方法
def get_position(self) -> float:
"""获取当前位置"""
return self._position
def get_current_volume(self) -> float:
"""获取当前体积"""
return self._current_volume
def get_remaining_capacity(self) -> float:
"""获取剩余容量"""
return self.max_volume - self._current_volume
def is_empty(self) -> bool:
"""检查是否为空"""
return self._current_volume <= 0.01 # 允许小量误差
def is_full(self) -> bool:
"""检查是否已满"""
return self._current_volume >= (self.max_volume - 0.01) # 允许小量误差
def __str__(self):
return f"VirtualTransferPump({self.device_id}: {self._current_volume:.2f}/{self.max_volume} ml, {self._status})"
return (
f"VirtualTransferPump({self.device_id}: {self._current_volume:.2f}/{self.max_volume} ml, {self._status})"
)
def __repr__(self):
return self.__str__()
@@ -398,20 +410,20 @@ class VirtualTransferPump:
async def demo():
"""虚拟泵使用示例"""
pump = VirtualTransferPump("demo_pump", {"max_volume": 50.0})
await pump.initialize()
print(f"Initial state: {pump}")
# 测试set_position方法
result = await pump.set_position(10.0, max_velocity=2.0)
print(f"Set position result: {result}")
print(f"After setting position to 10ml: {pump}")
# 吸液测试
await pump.aspirate(5.0, velocity=2.0)
print(f"After aspirating 5ml: {pump}")
# 清空测试
result = await pump.set_position(0.0)
print(f"Empty result: {result}")

View File

@@ -0,0 +1,874 @@
"""
Virtual Workbench Device - 模拟工作台设备
包含:
- 1个机械臂 (每次操作3s, 独占锁)
- 3个加热台 (每次加热10s, 可并行)
工作流程:
1. A1-A5 物料同时启动, 竞争机械臂
2. 机械臂将物料移动到空闲加热台
3. 加热完成后, 机械臂将物料移动到C1-C5
注意: 调用来自线程池, 使用 threading.Lock 进行同步
"""
import logging
import time
from typing import Dict, Any, Optional, List
from dataclasses import dataclass
from enum import Enum
from threading import Lock, RLock
from typing_extensions import TypedDict
from unilabos.registry.decorators import (
device, action, ActionInputHandle, ActionOutputHandle, DataSource, topic_config, not_action
)
from unilabos.ros.nodes.base_device_node import BaseROS2DeviceNode
from unilabos.resources.resource_tracker import SampleUUIDsType, LabSample
# ============ TypedDict 返回类型定义 ============
class MoveToHeatingStationResult(TypedDict):
"""move_to_heating_station 返回类型"""
success: bool
station_id: int
material_id: str
material_number: int
message: str
unilabos_samples: List[LabSample]
class StartHeatingResult(TypedDict):
"""start_heating 返回类型"""
success: bool
station_id: int
material_id: str
material_number: int
message: str
unilabos_samples: List[LabSample]
class MoveToOutputResult(TypedDict):
"""move_to_output 返回类型"""
success: bool
station_id: int
material_id: str
output_position: str
message: str
unilabos_samples: List[LabSample]
class PrepareMaterialsResult(TypedDict):
"""prepare_materials 返回类型 - 批量准备物料"""
success: bool
count: int
material_1: int # 物料编号1
material_2: int # 物料编号2
material_3: int # 物料编号3
material_4: int # 物料编号4
material_5: int # 物料编号5
message: str
unilabos_samples: List[LabSample]
# ============ 状态枚举 ============
class HeatingStationState(Enum):
"""加热台状态枚举"""
IDLE = "idle" # 空闲
OCCUPIED = "occupied" # 已放置物料, 等待加热
HEATING = "heating" # 加热中
COMPLETED = "completed" # 加热完成, 等待取走
class ArmState(Enum):
"""机械臂状态枚举"""
IDLE = "idle" # 空闲
BUSY = "busy" # 工作中
@dataclass
class HeatingStation:
"""加热台数据结构"""
station_id: int
state: HeatingStationState = HeatingStationState.IDLE
current_material: Optional[str] = None # 当前物料 (如 "A1", "A2")
material_number: Optional[int] = None # 物料编号 (1-5)
heating_start_time: Optional[float] = None
heating_progress: float = 0.0
@device(
id="virtual_workbench",
category=["virtual_device"],
description="Virtual Workbench with 1 robotic arm and 3 heating stations for concurrent material processing",
)
class VirtualWorkbench:
"""
Virtual Workbench Device - 虚拟工作台设备
模拟一个包含1个机械臂和3个加热台的工作站
- 机械臂操作耗时3秒, 同一时间只能执行一个操作
- 加热台加热耗时10秒, 3个加热台可并行工作
工作流:
1. 物料A1-A5并发启动(线程池), 竞争机械臂使用权
2. 获取机械臂后, 查找空闲加热台
3. 机械臂将物料放入加热台, 开始加热
4. 加热完成后, 机械臂将物料移动到目标位置Cn
"""
_ros_node: BaseROS2DeviceNode
# 配置常量
ARM_OPERATION_TIME: float = 2 # 机械臂操作时间(秒)
HEATING_TIME: float = 60.0 # 加热时间(秒)
NUM_HEATING_STATIONS: int = 3 # 加热台数量
def __init__(self, device_id: Optional[str] = None, config: Optional[Dict[str, Any]] = None, **kwargs):
# 处理可能的不同调用方式
if device_id is None and "id" in kwargs:
device_id = kwargs.pop("id")
if config is None and "config" in kwargs:
config = kwargs.pop("config")
self.device_id = device_id or "virtual_workbench"
self.config = config or {}
self.logger = logging.getLogger(f"VirtualWorkbench.{self.device_id}")
self.data: Dict[str, Any] = {}
# 从config中获取可配置参数
self.ARM_OPERATION_TIME = float(self.config.get("arm_operation_time", self.ARM_OPERATION_TIME))
self.HEATING_TIME = float(self.config.get("heating_time", self.HEATING_TIME))
self.NUM_HEATING_STATIONS = int(self.config.get("num_heating_stations", self.NUM_HEATING_STATIONS))
# 机械臂状态和锁
self._arm_lock = Lock()
self._arm_state = ArmState.IDLE
self._arm_current_task: Optional[str] = None
# 加热台状态
self._heating_stations: Dict[int, HeatingStation] = {
i: HeatingStation(station_id=i) for i in range(1, self.NUM_HEATING_STATIONS + 1)
}
self._stations_lock = RLock()
# 任务追踪
self._active_tasks: Dict[str, Dict[str, Any]] = {}
self._tasks_lock = Lock()
# 处理其他kwargs参数
skip_keys = {"arm_operation_time", "heating_time", "num_heating_stations"}
for key, value in kwargs.items():
if key not in skip_keys and not hasattr(self, key):
setattr(self, key, value)
self.logger.info(f"=== 虚拟工作台 {self.device_id} 已创建 ===")
self.logger.info(
f"机械臂操作时间: {self.ARM_OPERATION_TIME}s | "
f"加热时间: {self.HEATING_TIME}s | "
f"加热台数量: {self.NUM_HEATING_STATIONS}"
)
@not_action
def post_init(self, ros_node: BaseROS2DeviceNode):
"""ROS节点初始化后回调"""
self._ros_node = ros_node
@not_action
def initialize(self) -> bool:
"""初始化虚拟工作台"""
self.logger.info(f"初始化虚拟工作台 {self.device_id}")
with self._stations_lock:
for station in self._heating_stations.values():
station.state = HeatingStationState.IDLE
station.current_material = None
station.material_number = None
station.heating_progress = 0.0
self.data.update(
{
"status": "Ready",
"arm_state": ArmState.IDLE.value,
"arm_current_task": None,
"heating_stations": self._get_stations_status(),
"active_tasks_count": 0,
"message": "工作台就绪",
}
)
self.logger.info(f"工作台初始化完成: {self.NUM_HEATING_STATIONS}个加热台就绪")
return True
@not_action
def cleanup(self) -> bool:
"""清理虚拟工作台"""
self.logger.info(f"清理虚拟工作台 {self.device_id}")
self._arm_state = ArmState.IDLE
self._arm_current_task = None
with self._stations_lock:
self._heating_stations.clear()
with self._tasks_lock:
self._active_tasks.clear()
self.data.update(
{
"status": "Offline",
"arm_state": ArmState.IDLE.value,
"heating_stations": {},
"message": "工作台已关闭",
}
)
return True
def _get_stations_status(self) -> Dict[int, Dict[str, Any]]:
"""获取所有加热台状态"""
with self._stations_lock:
return {
station_id: {
"state": station.state.value,
"current_material": station.current_material,
"material_number": station.material_number,
"heating_progress": station.heating_progress,
}
for station_id, station in self._heating_stations.items()
}
def _update_data_status(self, message: Optional[str] = None):
"""更新状态数据"""
self.data.update(
{
"arm_state": self._arm_state.value,
"arm_current_task": self._arm_current_task,
"heating_stations": self._get_stations_status(),
"active_tasks_count": len(self._active_tasks),
}
)
if message:
self.data["message"] = message
def _find_available_heating_station(self) -> Optional[int]:
"""查找空闲的加热台"""
with self._stations_lock:
for station_id, station in self._heating_stations.items():
if station.state == HeatingStationState.IDLE:
return station_id
return None
def _acquire_arm(self, task_description: str) -> bool:
"""获取机械臂使用权(阻塞直到获取)"""
self.logger.info(f"[{task_description}] 等待获取机械臂...")
self._arm_lock.acquire()
self._arm_state = ArmState.BUSY
self._arm_current_task = task_description
self._update_data_status(f"机械臂执行: {task_description}")
self.logger.info(f"[{task_description}] 成功获取机械臂使用权")
return True
def _release_arm(self):
"""释放机械臂"""
task = self._arm_current_task
self._arm_state = ArmState.IDLE
self._arm_current_task = None
self._arm_lock.release()
self._update_data_status(f"机械臂已释放 (完成: {task})")
self.logger.info(f"机械臂已释放 (完成: {task})")
@action(
auto_prefix=True,
description="批量准备物料 - 虚拟起始节点, 生成A1-A5物料, 输出5个handle供后续节点使用",
handles=[
ActionOutputHandle(key="channel_1", data_type="workbench_material",
label="实验1", data_key="material_1", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="channel_2", data_type="workbench_material",
label="实验2", data_key="material_2", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="channel_3", data_type="workbench_material",
label="实验3", data_key="material_3", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="channel_4", data_type="workbench_material",
label="实验4", data_key="material_4", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="channel_5", data_type="workbench_material",
label="实验5", data_key="material_5", data_source=DataSource.EXECUTOR),
],
)
def prepare_materials(
self,
sample_uuids: SampleUUIDsType,
count: int = 5,
) -> PrepareMaterialsResult:
"""
批量准备物料 - 虚拟起始节点
作为工作流的起始节点, 生成指定数量的物料编号供后续节点使用。
输出5个handle (material_1 ~ material_5), 分别对应实验1~5。
"""
materials = [i for i in range(1, count + 1)]
self.logger.info(
f"[准备物料] 生成 {count} 个物料: A1-A{count} -> material_1~material_{count}"
)
return {
"success": True,
"count": count,
"material_1": materials[0] if len(materials) > 0 else 0,
"material_2": materials[1] if len(materials) > 1 else 0,
"material_3": materials[2] if len(materials) > 2 else 0,
"material_4": materials[3] if len(materials) > 3 else 0,
"material_5": materials[4] if len(materials) > 4 else 0,
"message": f"已准备 {count} 个物料: A1-A{count}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra={"material_uuid": content} if isinstance(content, str) else (content.serialize() if content else {}),
)
for sample_uuid, content in sample_uuids.items()
],
}
@action(
auto_prefix=True,
description="将物料从An位置移动到空闲加热台, 返回分配的加热台ID",
handles=[
ActionInputHandle(key="material_input", data_type="workbench_material",
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
ActionOutputHandle(key="heating_station_output", data_type="workbench_station",
label="加热台ID", data_key="station_id", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="material_number_output", data_type="workbench_material",
label="物料编号", data_key="material_number", data_source=DataSource.EXECUTOR),
],
)
def move_to_heating_station(
self,
sample_uuids: SampleUUIDsType,
material_number: int,
) -> MoveToHeatingStationResult:
"""
将物料从An位置移动到加热台
多线程并发调用时, 会竞争机械臂使用权, 并自动查找空闲加热台
"""
material_id = f"A{material_number}"
task_desc = f"移动{material_id}到加热台"
self.logger.info(f"[任务] {task_desc} - 开始执行")
with self._tasks_lock:
self._active_tasks[material_id] = {
"status": "waiting_for_arm",
"start_time": time.time(),
}
try:
with self._tasks_lock:
self._active_tasks[material_id]["status"] = "waiting_for_arm"
self._acquire_arm(task_desc)
with self._tasks_lock:
self._active_tasks[material_id]["status"] = "finding_station"
station_id = None
while station_id is None:
station_id = self._find_available_heating_station()
if station_id is None:
self.logger.info(f"[{material_id}] 没有空闲加热台, 等待中...")
self._release_arm()
time.sleep(0.5)
self._acquire_arm(task_desc)
with self._stations_lock:
self._heating_stations[station_id].state = HeatingStationState.OCCUPIED
self._heating_stations[station_id].current_material = material_id
self._heating_stations[station_id].material_number = material_number
with self._tasks_lock:
self._active_tasks[material_id]["status"] = "arm_moving"
self._active_tasks[material_id]["assigned_station"] = station_id
self.logger.info(f"[{material_id}] 机械臂正在移动到加热台{station_id}...")
time.sleep(self.ARM_OPERATION_TIME)
self._update_data_status(f"{material_id}已放入加热台{station_id}")
self.logger.info(
f"[{material_id}] 已放入加热台{station_id} (用时{self.ARM_OPERATION_TIME}s)"
)
self._release_arm()
with self._tasks_lock:
self._active_tasks[material_id]["status"] = "placed_on_station"
return {
"success": True,
"station_id": station_id,
"material_id": material_id,
"material_number": material_number,
"message": f"{material_id}已成功移动到加热台{station_id}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
except Exception as e:
self.logger.error(f"[{material_id}] 移动失败: {str(e)}")
if self._arm_lock.locked():
self._release_arm()
return {
"success": False,
"station_id": -1,
"material_id": material_id,
"material_number": material_number,
"message": f"移动失败: {str(e)}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
@action(
auto_prefix=True,
always_free=True,
description="启动指定加热台的加热程序",
handles=[
ActionInputHandle(key="station_id_input", data_type="workbench_station",
label="加热台ID", data_key="station_id", data_source=DataSource.HANDLE),
ActionInputHandle(key="material_number_input", data_type="workbench_material",
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
ActionOutputHandle(key="heating_done_station", data_type="workbench_station",
label="加热完成-加热台ID", data_key="station_id", data_source=DataSource.EXECUTOR),
ActionOutputHandle(key="heating_done_material", data_type="workbench_material",
label="加热完成-物料编号", data_key="material_number", data_source=DataSource.EXECUTOR),
],
)
def start_heating(
self,
sample_uuids: SampleUUIDsType,
station_id: int,
material_number: int,
) -> StartHeatingResult:
"""
启动指定加热台的加热程序
"""
self.logger.info(f"[加热台{station_id}] 开始加热")
if station_id not in self._heating_stations:
return {
"success": False,
"station_id": station_id,
"material_id": "",
"material_number": material_number,
"message": f"无效的加热台ID: {station_id}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
with self._stations_lock:
station = self._heating_stations[station_id]
if station.current_material is None:
return {
"success": False,
"station_id": station_id,
"material_id": "",
"material_number": material_number,
"message": f"加热台{station_id}上没有物料",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
if station.state == HeatingStationState.HEATING:
return {
"success": False,
"station_id": station_id,
"material_id": station.current_material,
"material_number": material_number,
"message": f"加热台{station_id}已经在加热中",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
material_id = station.current_material
station.state = HeatingStationState.HEATING
station.heating_start_time = time.time()
station.heating_progress = 0.0
with self._tasks_lock:
if material_id in self._active_tasks:
self._active_tasks[material_id]["status"] = "heating"
self._update_data_status(f"加热台{station_id}开始加热{material_id}")
with self._stations_lock:
heating_list = [
f"加热台{sid}:{s.current_material}"
for sid, s in self._heating_stations.items()
if s.state == HeatingStationState.HEATING and s.current_material
]
self.logger.info(f"[并行加热] 当前同时加热中: {', '.join(heating_list)}")
start_time = time.time()
last_countdown_log = start_time
while True:
elapsed = time.time() - start_time
remaining = max(0.0, self.HEATING_TIME - elapsed)
progress = min(100.0, (elapsed / self.HEATING_TIME) * 100)
with self._stations_lock:
self._heating_stations[station_id].heating_progress = progress
self._update_data_status(f"加热台{station_id}加热中: {progress:.1f}%")
if time.time() - last_countdown_log >= 5.0:
self.logger.info(f"[加热台{station_id}] {material_id} 剩余 {remaining:.1f}s")
last_countdown_log = time.time()
if elapsed >= self.HEATING_TIME:
break
time.sleep(1.0)
with self._stations_lock:
self._heating_stations[station_id].state = HeatingStationState.COMPLETED
self._heating_stations[station_id].heating_progress = 100.0
with self._tasks_lock:
if material_id in self._active_tasks:
self._active_tasks[material_id]["status"] = "heating_completed"
self._update_data_status(f"加热台{station_id}加热完成")
self.logger.info(f"[加热台{station_id}] {material_id}加热完成 (用时{self.HEATING_TIME}s)")
return {
"success": True,
"station_id": station_id,
"material_id": material_id,
"material_number": material_number,
"message": f"加热台{station_id}加热完成",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
@action(
auto_prefix=True,
description="将物料从加热台移动到输出位置Cn",
handles=[
ActionInputHandle(key="output_station_input", data_type="workbench_station",
label="加热台ID", data_key="station_id", data_source=DataSource.HANDLE),
ActionInputHandle(key="output_material_input", data_type="workbench_material",
label="物料编号", data_key="material_number", data_source=DataSource.HANDLE),
],
)
def move_to_output(
self,
sample_uuids: SampleUUIDsType,
station_id: int,
material_number: int,
) -> MoveToOutputResult:
"""
将物料从加热台移动到输出位置Cn
"""
output_number = material_number
if station_id not in self._heating_stations:
return {
"success": False,
"station_id": station_id,
"material_id": "",
"output_position": f"C{output_number}",
"message": f"无效的加热台ID: {station_id}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
with self._stations_lock:
station = self._heating_stations[station_id]
material_id = station.current_material
if material_id is None:
return {
"success": False,
"station_id": station_id,
"material_id": "",
"output_position": f"C{output_number}",
"message": f"加热台{station_id}上没有物料",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
if station.state != HeatingStationState.COMPLETED:
return {
"success": False,
"station_id": station_id,
"material_id": material_id,
"output_position": f"C{output_number}",
"message": f"加热台{station_id}尚未完成加热 (当前状态: {station.state.value})",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
output_position = f"C{output_number}"
task_desc = f"从加热台{station_id}移动{material_id}{output_position}"
self.logger.info(f"[任务] {task_desc}")
try:
with self._tasks_lock:
if material_id in self._active_tasks:
self._active_tasks[material_id]["status"] = "waiting_for_arm_output"
self._acquire_arm(task_desc)
with self._tasks_lock:
if material_id in self._active_tasks:
self._active_tasks[material_id]["status"] = "arm_moving_to_output"
self.logger.info(
f"[{material_id}] 机械臂正在从加热台{station_id}取出并移动到{output_position}..."
)
time.sleep(self.ARM_OPERATION_TIME)
with self._stations_lock:
self._heating_stations[station_id].state = HeatingStationState.IDLE
self._heating_stations[station_id].current_material = None
self._heating_stations[station_id].material_number = None
self._heating_stations[station_id].heating_progress = 0.0
self._heating_stations[station_id].heating_start_time = None
self._release_arm()
with self._tasks_lock:
if material_id in self._active_tasks:
self._active_tasks[material_id]["status"] = "completed"
self._active_tasks[material_id]["end_time"] = time.time()
self._update_data_status(f"{material_id}已移动到{output_position}")
self.logger.info(
f"[{material_id}] 已成功移动到{output_position} (用时{self.ARM_OPERATION_TIME}s)"
)
return {
"success": True,
"station_id": station_id,
"material_id": material_id,
"output_position": output_position,
"message": f"{material_id}已成功移动到{output_position}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str)
else (content.serialize() if content is not None else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
except Exception as e:
self.logger.error(f"移动到输出位置失败: {str(e)}")
if self._arm_lock.locked():
self._release_arm()
return {
"success": False,
"station_id": station_id,
"material_id": "",
"output_position": output_position,
"message": f"移动失败: {str(e)}",
"unilabos_samples": [
LabSample(
sample_uuid=sample_uuid,
oss_path="",
extra=(
{"material_uuid": content}
if isinstance(content, str) else (content.serialize() if content else {})
),
)
for sample_uuid, content in sample_uuids.items()
],
}
# ============ 状态属性 ============
@property
@topic_config()
def status(self) -> str:
return self.data.get("status", "Unknown")
@property
@topic_config()
def arm_state(self) -> str:
return self._arm_state.value
@property
@topic_config()
def arm_current_task(self) -> str:
return self._arm_current_task or ""
@property
@topic_config()
def heating_station_1_state(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(1)
return station.state.value if station else "unknown"
@property
@topic_config()
def heating_station_1_material(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(1)
return station.current_material or "" if station else ""
@property
@topic_config()
def heating_station_1_progress(self) -> float:
with self._stations_lock:
station = self._heating_stations.get(1)
return station.heating_progress if station else 0.0
@property
@topic_config()
def heating_station_2_state(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(2)
return station.state.value if station else "unknown"
@property
@topic_config()
def heating_station_2_material(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(2)
return station.current_material or "" if station else ""
@property
@topic_config()
def heating_station_2_progress(self) -> float:
with self._stations_lock:
station = self._heating_stations.get(2)
return station.heating_progress if station else 0.0
@property
@topic_config()
def heating_station_3_state(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(3)
return station.state.value if station else "unknown"
@property
@topic_config()
def heating_station_3_material(self) -> str:
with self._stations_lock:
station = self._heating_stations.get(3)
return station.current_material or "" if station else ""
@property
@topic_config()
def heating_station_3_progress(self) -> float:
with self._stations_lock:
station = self._heating_stations.get(3)
return station.heating_progress if station else 0.0
@property
@topic_config()
def active_tasks_count(self) -> int:
with self._tasks_lock:
return len(self._active_tasks)
@property
@topic_config()
def message(self) -> str:
return self.data.get("message", "")

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# Layout Optimizer Handover
**Date**: 2026-04-10 | **Branch**: `feat/3d_layout_and_visualize` | **Commit**: `99dc821a` | **Tests**: 270 (260 pass + 10 LLM skip w/o API key)
This package is a standalone lab layout optimizer. It takes a device list + constraints and returns optimized placements. Your integration points are the HTTP API and the LLM skill document.
---
## 1. Full Pipeline Overview
```
User NL request
┌─────────────────┐ skill doc: llm_skill/layout_intent_translator.md
│ LLM Agent │◄── + device list from scene (GET /devices)
│ (your side) │ + schema discovery (GET /interpret/schema)
└────────┬────────┘
│ structured intents JSON
POST /interpret ← intent_interpreter.py (pure translation)
│ { constraints, translations, workflow_edges, errors }
User confirms ← translations have human-readable explanations
POST /optimize ← full pipeline below
┌────┴─────────────────────────────────────────┐
│ 1. Device catalog (device_catalog.py) │
│ footprints.json → Device objects │
│ bbox, height, openings per device │
│ │
│ 2. Seeder (seeders.py) │
│ Force-directed initial placement │
│ Presets: compact_outward, spread_inward, │
│ workflow_cluster, row_fallback │
│ Accounts for openings, workflow edges │
│ │
│ 3. DE Optimizer (optimizer.py) │
│ Custom DE loop (best1bin/currenttobest1bin│
│ /rand1bin strategies) │
│ 3N-dim: [x0, y0, θ0, x1, y1, θ1, ...] │
│ Broad-phase AABB sweep (broad_phase.py) │
│ θ lattice snap in joint discrete mode │
│ Cost = hard_penalties + soft_penalties │
│ Graduated collision penalties (not binary) │
│ │
│ 4. θ snap (optimizer.snap_theta) │
│ Snap near-cardinal angles to 0/90/180/270 │
│ (opt-in via snap_cardinal=True) │
│ │
│ 5. Final eval (constraints.py) │
│ Binary pass/fail for response.success │
└──────────────────────────────────────────────┘
{ placements, cost, success }
```
---
## 2. API Reference
### `POST /interpret` — LLM intent → constraints
Translates semantic intents into optimizer constraints. The LLM agent calls this after translating user NL.
**Request:**
```json
{
"intents": [
{
"intent": "reachable_by",
"params": {"arm": "arm_slider", "targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"]},
"description": "Robot arm must reach these devices"
},
{
"intent": "workflow_hint",
"params": {"workflow": "pcr", "devices": ["device_a", "device_b", "device_c"]},
"description": "PCR workflow order"
},
{
"intent": "close_together",
"params": {"devices": ["device_a", "device_b"], "priority": "high"},
"description": "Keep these close"
}
]
}
```
**Response:**
```json
{
"constraints": [
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "opentrons_liquid_handler"}, "weight": 1.0},
...
],
"translations": [
{
"source_intent": "reachable_by",
"source_description": "Robot arm must reach these devices",
"source_params": {"arm": "arm_slider", "targets": ["..."]},
"generated_constraints": [...],
"explanation": "机械臂 'arm_slider' 需要能够到达 2 个目标设备",
"confidence": "high"
}
],
"workflow_edges": [["device_a", "device_b"], ["device_b", "device_c"]],
"errors": []
}
```
The `constraints` and `workflow_edges` arrays pass directly to `/optimize` — no transformation needed.
### `GET /interpret/schema` — LLM discovery
Returns all 11 intent types with parameter specs. LLM agent should call this before translating.
### `POST /optimize` — Run layout optimization
**Request:**
```json
{
"devices": [
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel", "device_type": "static"},
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
...
],
"lab": {"width": 6.0, "depth": 4.0},
"constraints": [...],
"workflow_edges": [["device_a", "device_b"]],
"seeder": "compact_outward",
"run_de": true,
"maxiter": 200,
"seed": 42,
"angle_granularity": 4,
"snap_cardinal": false,
"strategy": "currenttobest1bin",
"mutation": [0.5, 1.0],
"theta_mutation": null,
"recombination": 0.7,
"crossover_mode": "device"
}
```
**Response:**
```json
{
"placements": [
{
"device_id": "thermo_orbitor_rs2_hotel",
"uuid": "thermo_orbitor_rs2_hotel",
"position": {"x": 1.33, "y": 2.35, "z": 0.0},
"rotation": {"x": 0.0, "y": 0.0, "z": 1.5708}
},
...
],
"cost": 0.0,
"success": true,
"seeder_used": "compact_outward",
"de_ran": true
}
```
`position`/`rotation` format matches Cloud's `CommonPositionType`. `rotation.z` is θ in radians.
**DE hyperparameters:**
| Param | Default | Description |
|-------|---------|-------------|
| `strategy` | `"currenttobest1bin"` | DE mutation strategy (`best1bin`, `currenttobest1bin`, `rand1bin`) |
| `mutation` | `[0.5, 1.0]` | Dithered F range for position dimensions |
| `theta_mutation` | `null` (same as `mutation`) | Separate F range for θ dimensions (decoupled mutation) |
| `recombination` | `0.7` | Crossover probability |
| `crossover_mode` | `"device"` | `"device"` = per-device CR, `"dimension"` = per-dimension CR |
| `angle_granularity` | `null` | `4`/`8`/`12`/`24` — snaps θ to a discrete lattice during DE (joint mode). `4` = axis-aligned (0/90/180/270). `null` = continuous θ |
| `snap_cardinal` | `false` | Post-DE snap to nearest cardinal angle with collision rollback |
### Scene State API
Shared scene state between the LLM agent and the frontend. The agent pushes layout results here; the frontend polls for updates.
#### `GET /scene/lab` / `POST /scene/lab` — Lab dimensions
**GET** returns current lab dimensions. **POST** sets them (frontend sends this when user changes lab size).
```json
{"width": 6.0, "depth": 4.0}
```
#### `GET /scene/placements` / `POST /scene/placements` / `DELETE /scene/placements`
**GET** returns current placements + a version counter. Frontend polls this every 1s and re-renders when version changes.
```json
{"version": 3, "placements": [...]}
```
**POST** pushes new placements (from `/optimize` result or agent). Bumps version.
**DELETE** clears all placements (resets scene).
### `GET /devices` — Device catalog
Returns all known devices with bbox, openings, model paths. The LLM agent should receive this list as context so it can resolve fuzzy device names.
### `GET /health`
Returns `{"status": "ok"}`.
---
## 3. Intent Types (11 total)
| Intent | Params | Generates | Type |
|--------|--------|-----------|------|
| `reachable_by` | `arm` (str), `targets` (list[str]) | `reachability` per target | hard |
| `close_together` | `devices` (list[str]), `priority` (low/medium/high) | `minimize_distance` per pair | soft |
| `far_apart` | `devices` (list[str]), `priority` | `maximize_distance` per pair | soft |
| `keep_adjacent` | `devices` (list[str]), `priority` | `minimize_distance` per pair | soft |
| `max_distance` | `device_a`, `device_b`, `distance` (float m) | `distance_less_than` | hard |
| `min_distance` | `device_a`, `device_b`, `distance` (float m) | `distance_greater_than` | hard |
| `min_spacing` | `min_gap` (float m, default 0.3) | `min_spacing` | hard |
| `workflow_hint` | `workflow` (str), `devices` (ordered list[str]) | `minimize_distance` consecutive + `workflow_edges` | soft |
| `face_outward` | (none) | `prefer_orientation_mode` outward | soft |
| `face_inward` | (none) | `prefer_orientation_mode` inward | soft |
| `align_cardinal` | (none) | `prefer_aligned` | soft |
Intent priorities are baked into the final emitted constraint `weight` during interpretation. The caller only sees the resulting weight, not a separate constraint-level priority field.
---
## 4. LLM Integration Guide
### What You Need to Build (Your Side)
The LLM agent that converts user natural language → structured intents JSON. We provide:
1. **Skill document** (`llm_skill/layout_intent_translator.md`) — system prompt for the LLM. Contains intent schema, device name resolution rules, translation rules, and PCR workflow examples.
2. **Runtime schema** (`GET /interpret/schema`) — machine-readable intent specs. LLM agent should call this for discovery.
3. **Device context** — before translating, feed the LLM the scene's device list (from `GET /devices` or your scene state). The LLM uses this to resolve fuzzy names like "PCR machine" → `inheco_odtc_96xl`.
### Integration Flow
```
1. User enters NL request in Cloud UI
2. Your LLM agent receives:
- User message
- Scene device list (id, name, type, bbox)
- Skill doc as system prompt
- Optional: GET /interpret/schema for discovery
3. LLM outputs: {"intents": [...]}
4. POST /interpret with LLM output
5. Show user the translations for confirmation
6. POST /optimize with confirmed constraints + workflow_edges
7. Apply placements to scene
```
### Device Name Resolution (handled by LLM, not by optimizer)
The skill doc teaches the LLM to match fuzzy names:
- "PCR machine" / "thermal cycler" → `inheco_odtc_96xl`
- "liquid handler" / "pipetting robot" → `opentrons_liquid_handler`
- "plate hotel" / "storage" → `thermo_orbitor_rs2_hotel`
- "robot arm" / "the arm" → device with `type: articulation`
- "plate sealer" → `agilent_plateloc`
No search endpoint needed — the device list is already in context.
### Tested LLM Outputs
We tested with Claude Sonnet (via subagent, no API key required). Examples:
**Input**: "Take plate from hotel, prepare sample in the pipetting robot, seal it, then run thermal cycling. The arm handles all transfers. Keep liquid handler and sealer close, minimum 15cm gap."
**LLM produced**: `reachable_by` (arm→4 devices), `workflow_hint` (correct PCR order), `close_together` (high, LH+sealer), `min_distance` (0.15m, LH+sealer)
**Input**: "I want an automatic PCR lab, make it compact and neat"
**LLM produced**: `reachable_by`, `workflow_hint`, `close_together` (all devices), `min_spacing` (0.05m), `align_cardinal`
All outputs pass through `/interpret``/optimize` successfully.
---
## 5. Constraint System Details
### Hard Constraints (cost = ∞ on violation)
| Rule Name | Params | What it checks |
|-----------|--------|---------------|
| `no_collision` | (default, always on) | OBB-SAT pairwise collision between all devices |
| `within_bounds` | (default, always on) | All devices within lab boundary |
| `reachability` | `arm_id`, `target_device_id` | Target center within arm reach radius |
| `distance_less_than` | `device_a`, `device_b`, `distance` | OBB edge-to-edge distance ≤ threshold |
| `distance_greater_than` | `device_a`, `device_b`, `distance` | OBB edge-to-edge distance ≥ threshold |
| `min_spacing` | `min_gap` | All device pairs have ≥ min_gap edge-to-edge |
### Soft Constraints (weighted penalty)
| Rule Name | Params | What it minimizes |
|-----------|--------|------------------|
| `minimize_distance` | `device_a`, `device_b` | OBB edge-to-edge distance × weight |
| `maximize_distance` | `device_a`, `device_b` | 1/(distance+ε) × weight |
| `prefer_orientation_mode` | `mode` (outward/inward) | Angle between opening direction and ideal direction |
| `prefer_aligned` | (none) | Deviation from nearest 90° angle |
| `prefer_seeder_orientation` | (none) | Deviation from seeder-assigned θ |
| `crossing_penalty` | (auto, part of `reachability` eval) | Segment-OBB intersection length of opening-to-arm path blocked by other devices (Cyrus-Beck clipping via `obb.segment_obb_intersection_length`) |
### Weight Normalization
| Constant | Value | Meaning |
|----------|-------|---------|
| `DEFAULT_WEIGHT_DISTANCE` | 100.0 | 1 cm → penalty 1.0 |
| `DEFAULT_WEIGHT_ANGLE` | 60.0 | 5° → penalty ~1.0 |
| `HARD_MULTIPLIER` | 5.0 | Hard constraint penalty multiplier during graduated DE |
Constraints support a `priority` field (`critical` / `high` / `normal` / `low`) with multipliers 5× / 2× / 1× / 0.5×.
### Graduated Penalties (DE internals)
Default hard constraints (collision, boundary) use **graduated penalties** during DE optimization — proportional to penetration depth / overshoot distance. This gives DE a smooth gradient instead of binary inf. Final evaluation uses binary mode for pass/fail reporting.
---
## 6. Checker Architecture (Mock → Real)
```
interfaces.py (Protocol definitions)
├── CollisionChecker.check(placements) → collisions
├── CollisionChecker.check_bounds(placements, w, d) → out_of_bounds
└── ReachabilityChecker.is_reachable(arm_id, arm_pose, target) → bool
mock_checkers.py (current, no ROS)
├── MockCollisionChecker — OBB SAT
└── MockReachabilityChecker — Euclidean distance, 100m fallback for unknown arms
ros_checkers.py (for ROS2/MoveIt2 integration)
├── MoveItCollisionChecker — python-fcl direct + OBB fallback
└── IKFastReachabilityChecker — precomputed voxel O(1) + live IK fallback
└── create_checkers(mode) — factory, controlled by LAYOUT_CHECKER_MODE env var
```
To switch to real checkers: `LAYOUT_CHECKER_MODE=moveit` + pass MoveIt2 instance.
---
## 7. File Inventory
### Core Pipeline
| File | Lines | Purpose |
|------|-------|---------|
| `models.py` | 97 | Dataclasses: Device, Lab, Placement, Constraint, Intent, Opening |
| `device_catalog.py` | 303 | Loads devices from footprints.json + uni-lab-assets + registry |
| `footprints.json` | 183KB | 499 device bounding boxes, heights, openings (offline extracted) |
| `seeders.py` | 331 | Force-directed initial layout with presets |
| `optimizer.py` | 1056 | Custom DE loop: per-device crossover, θ wrapping, discrete angle lattice, multi-strategy |
| `broad_phase.py` | 66 | 2-axis sweep-and-prune AABB broad phase for collision pair pruning |
| `constraints.py` | 627 | Unified constraint evaluation (hard + soft + graduated + crossing penalty) |
| `obb.py` | 257 | OBB geometry: corners, overlap SAT, min_distance, penetration_depth, segment intersection |
| `intent_interpreter.py` | 366 | 11 intent handlers, pure translation, no side effects |
| `server.py` | 743 | FastAPI: /interpret, /optimize, /devices, /scene/* endpoints |
| `lab_parser.py` | 50 | Parse lab floor plan JSON to Lab dataclass |
### Reference / Utilities
| File | Purpose |
|------|---------|
| `extract_footprints.py` | How footprints.json was generated (offline STL/GLB → 2D bbox extraction via trimesh) |
| `generate_asset_registry.py` | Generate YAML registry entries for uni-lab-assets devices not already registered |
### Integration Layer
| File | Purpose |
|------|---------|
| `interfaces.py` | Protocol definitions for CollisionChecker / ReachabilityChecker |
| `mock_checkers.py` | Dev-mode checkers (OBB collision, Euclidean reachability) |
| `ros_checkers.py` | MoveIt2/IKFast adapters for real collision + reachability |
### LLM
| File | Purpose |
|------|---------|
| `llm_skill/layout_intent_translator.md` | System prompt for LLM: intent schema, device resolution, translation rules, examples |
| `llm_skill/demo_agent.md` | LLM agent orchestration instructions for demo (GET /devices → intents → /interpret → /optimize → /scene/placements) |
### Demo / Frontend
| File | Purpose |
|------|---------|
| `static/lab3d.html` | Three.js 3D visualization frontend (1227 lines): device library, drag-to-add, auto layout, scene polling |
### Configuration
| File | Purpose |
|------|---------|
| `pyproject.toml` | Package deps: scipy, numpy, fastapi, uvicorn, pydantic |
### Tests (270 total: 260 pass + 10 skip without API key)
| File | Tests | Coverage |
|------|-------|----------|
| `test_intent_interpreter.py` | 19 | All 11 handlers, validation, priority, multi-intent |
| `test_interpret_api.py` | 6 | /interpret and /interpret/schema endpoints |
| `test_e2e_pcr_pipeline.py` | 12 | Full pipeline: interpret → optimize → verify placements |
| `test_llm_skill.py` | 10 | Real LLM fuzzy input → structured output (needs ANTHROPIC_API_KEY) |
| `test_constraints.py` | 30 | Constraint evaluation, hard/soft, graduated penalties, crossing penalty |
| `test_optimizer.py` | 50 | DE optimizer, vector encoding, bounds, discrete angles, strategies |
| `test_mock_checkers.py` | 15 | MockCollisionChecker, MockReachabilityChecker |
| `test_ros_checkers.py` | 40 | MoveIt2/IKFast adapter tests |
| `test_seeders.py` | 12 | Force-directed seeder presets |
| `test_device_catalog.py` | 25 | Device loading, footprint merging |
| `test_obb.py` | 18 | OBB geometry functions, segment intersection |
| `test_bugfixes_v2.py` | 28 | Regression: duplicate IDs, orientation, min_spacing, cardinal snap defaults |
| `test_broad_phase.py` | 5 | Sweep-and-prune AABB broad phase |
---
## 8. How to Run
### Quick Start
```bash
# Install
pip install -e ".[dev]"
# Run server
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
# Run server with debug logging (shows DE cost breakdown per generation)
LAYOUT_DEBUG=1 uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
# Run tests
pytest unilabos/layout_optimizer/tests/ -v
# Run LLM skill tests (needs API key)
ANTHROPIC_API_KEY=sk-... pytest unilabos/layout_optimizer/tests/test_llm_skill.py -v
```
**Log files**: All requests are logged to `unilabos/layout_optimizer/logs/{YYYYMMDD_HHMMSS}.log` at DEBUG level (frontend polling GET /scene/placements excluded).
### Dependencies
- Python ≥ 3.10
- scipy, numpy, fastapi, uvicorn, pydantic
- Optional: anthropic (for LLM skill tests)
- Optional: python-fcl (for real collision checking, not needed for mock mode)
### Environment Variables
| Variable | Default | Purpose |
|----------|---------|---------|
| `UNI_LAB_ASSETS_DIR` | `../uni-lab-assets` | Path to device 3D models |
| `UNI_LAB_OS_DEVICE_MESH_DIR` | `Uni-Lab-OS/unilabos/device_mesh/devices` | Registry device meshes |
| `LAYOUT_CHECKER_MODE` | `mock` | `mock` or `moveit` for checker selection |
| `LAYOUT_DEBUG` | (unset) | Set to `1` for DEBUG-level console logging (DE cost breakdown per generation) |
| `ANTHROPIC_API_KEY` | (none) | For LLM skill tests |
---
## 9. Known Limitations
1. **Mock reachability**: `MockReachabilityChecker` uses 100m fallback for unknown arm IDs — effectively "always reachable" for mock mode. Real arm reach requires `ros_checkers.py` with MoveIt2.
2. **No real LLM in tests**: `test_llm_skill.py` tests are skipped without `ANTHROPIC_API_KEY`. We verified with Claude Sonnet subagent that the skill doc produces correct output for PCR workflow scenarios.
3. **Opening data coverage**: 289/499 devices have opening direction annotations. Devices without openings default to local -Y as front with no alignment penalty.
4. **Single lab room**: No multi-room or corridor support yet. Lab is a single rectangle with optional rectangular obstacles.
5. **Intent interpreter is stateless**: It translates intents one-by-one with no cross-referencing between them. Duplicate/conflicting constraints are the LLM's responsibility to avoid.
6. **`align_weight` and `snap_cardinal` default to off**: `prefer_aligned` weight defaults to 0 (was `DEFAULT_WEIGHT_ANGLE=60`) and `snap_theta_safe` is opt-in via `snap_cardinal=True`. Both remain available when explicitly requested via `align_cardinal` intent or API param.
7. **Hybrid angle mode deprecated**: The angle-first hybrid mode (separate angle sweep + position-only DE) has been replaced by joint discrete mode as the default when `angle_granularity` is set. Joint mode snaps θ to the discrete lattice within the normal 3N DE loop.
---
## 10. Quick Verification (curl)
```bash
# 1. Health check
curl http://localhost:8000/health
# 2. Schema discovery
curl http://localhost:8000/interpret/schema | python3 -m json.tool
# 3. Interpret PCR workflow
curl -X POST http://localhost:8000/interpret \
-H "Content-Type: application/json" \
-d '{
"intents": [
{"intent": "reachable_by", "params": {"arm": "arm_slider", "targets": ["opentrons_liquid_handler", "inheco_odtc_96xl"]}, "description": "arm reaches targets"},
{"intent": "workflow_hint", "params": {"workflow": "pcr", "devices": ["thermo_orbitor_rs2_hotel", "opentrons_liquid_handler", "agilent_plateloc", "inheco_odtc_96xl"]}, "description": "PCR order"}
]
}' | python3 -m json.tool
# 4. Optimize (use constraints from step 3)
curl -X POST http://localhost:8000/optimize \
-H "Content-Type: application/json" \
-d '{
"devices": [
{"id": "thermo_orbitor_rs2_hotel", "name": "Plate Hotel"},
{"id": "arm_slider", "name": "Robot Arm", "device_type": "articulation"},
{"id": "opentrons_liquid_handler", "name": "Liquid Handler"},
{"id": "agilent_plateloc", "name": "Plate Sealer"},
{"id": "inheco_odtc_96xl", "name": "Thermal Cycler"}
],
"lab": {"width": 6.0, "depth": 4.0},
"constraints": [
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "opentrons_liquid_handler"}, "weight": 1.0},
{"type": "hard", "rule_name": "reachability", "params": {"arm_id": "arm_slider", "target_device_id": "inheco_odtc_96xl"}, "weight": 1.0},
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "thermo_orbitor_rs2_hotel", "device_b": "opentrons_liquid_handler"}, "weight": 3.0},
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "opentrons_liquid_handler", "device_b": "agilent_plateloc"}, "weight": 3.0},
{"type": "soft", "rule_name": "minimize_distance", "params": {"device_a": "agilent_plateloc", "device_b": "inheco_odtc_96xl"}, "weight": 3.0}
],
"workflow_edges": [
["thermo_orbitor_rs2_hotel", "opentrons_liquid_handler"],
["opentrons_liquid_handler", "agilent_plateloc"],
["agilent_plateloc", "inheco_odtc_96xl"]
],
"run_de": true,
"angle_granularity": 4,
"maxiter": 100,
"seed": 42
}' | python3 -m json.tool
```
---
## 11. Demo Setup
This section documents the device processing pipeline, test frontend, and LLM agent demo for the layout optimizer.
### 11.1 Device Processing Pipeline
How devices go from 3D meshes to collision footprints:
1. **Source data**:
- `uni-lab-assets/` repository: GLB/STL 3D models + XACRO robot descriptions
- `Uni-Lab-OS/device_mesh/devices/` registry: device metadata directories
2. **Extraction** (`extract_footprints.py`):
- Load meshes via `trimesh` (STL for geometry, GLB for display)
- Compute oriented bounding box (OBB): width, depth, height
- Apply GLB root node rotation to align with world frame
- Detect openings from XACRO `<joint type="fixed">` elements containing "socket" in name
- Compute opening direction: centroid of socket origins → cardinal direction mapping
- Manual overrides for devices with non-standard opening patterns (`MANUAL_OPENINGS` dict)
- Write results to `footprints.json` (499 devices, 183KB)
3. **Catalog merging** (`device_catalog.py`):
- Load `footprints.json` (OBB + openings)
- Load `uni-lab-assets/data.json` (asset tree structure)
- Load `Uni-Lab-OS/device_mesh/devices/` (registry devices)
- Merge: registry devices get priority for metadata, but assets' 3D model paths preferred
- Fallback sizes: `KNOWN_SIZES` dict provides manual dimensions when trimesh extraction fails
4. **Standalone filtering** (`server.py:_is_standalone_device`):
- Bbox >30cm = device (standalone equipment)
- Bbox <5cm = consumable (plates, tubes, tips)
- 5-30cm = keyword heuristic (check name for "plate", "tube", "tip", "rack")
### 11.2 Test Frontend (`static/lab3d.html`)
Interactive 3D lab layout visualization and design tool (1227 lines).
**Technology stack**:
- Three.js v0.169.0 (ES modules from esm.sh CDN)
- WebGL renderer with PCF soft shadow maps, ACES filmic tone mapping
- OrbitControls for camera interaction
**Features**:
- **Device library**: Left sidebar with search/filter, toggle between devices and consumables
- **Drag-to-add**: Click device in library → adds to scene with random position
- **Selected devices panel**: Right panel lists all placed devices, click to remove
- **Lab dimensions**: Width × Depth inputs (meters), collision margin slider
- **View modes**: 3D perspective (default) and top-down orthographic
- **Grid system**: 0.5m grid with lab boundary highlighting
- **Device visualization**: Box geometry with emissive materials, edge highlights, CSS2D labels
- **Opening markers**: Orange arrows and semi-transparent strips showing device access directions
- **Auto Layout button**: Calls `POST /optimize` with current devices + constraints
- **Scene polling**: 1-second polling of `GET /scene/placements` for agent-pushed updates (version-based change detection)
- **Smooth animation**: Lerp interpolation for device placement changes
**Backend integration**:
- `GET /devices` — Load device catalog on startup
- `POST /optimize` — Send devices + constraints, receive placements
- `POST /scene/lab` — Push lab dimensions when changed
- `GET /scene/placements` — Poll every 1s for agent-pushed updates
**Key JavaScript functions**:
- `loadDeviceCatalog()` — Fetch device list, build catalog with color pool
- `createDeviceMesh(deviceId, uuid)` — Create Three.js Group with body, edges, opening markers
- `addDevice(deviceId)` / `removeDevice(uuid)` — Manage selected devices
- `runLayout()` — Call backend `/optimize` or local bin packing fallback
- `animatePlacement(uuid, tx, tz, theta)` — Smooth lerp to target position
- `setView('3d' | 'top')` — Switch camera perspective
### 11.3 LLM Agent Demo (`llm_skill/demo_agent.md`)
LLM agent orchestration instructions for natural language lab layout design.
**Agent workflow**:
1. `GET /devices` — Fetch device catalog for context
2. Parse user natural language request
3. Build structured intents JSON (using `layout_intent_translator.md` skill)
4. `POST /interpret` — Translate intents to constraints
5. `POST /optimize` — Run layout optimization
6. `POST /scene/placements` — Push results to shared scene state
7. Frontend auto-updates via polling (no manual refresh needed)
**Example user requests**:
- "Design a PCR lab with robot arm automation, keep it compact"
- "Place liquid handler, thermal cycler, and plate sealer. Arm must reach all devices."
- "Add a plate hotel, make sure it's close to the liquid handler"
### 11.4 Running the Demo
```bash
# Start the server
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
# Open in browser
# http://localhost:8000/
# Use Claude Code with demo_agent.md skill to orchestrate via natural language
# The agent will call the API endpoints and push results to /scene/placements
# The frontend will automatically update via polling
```
**Demo flow**:
1. Open `http://localhost:8000/` in browser
2. Frontend loads device catalog and displays 3D scene
3. Use Claude Code with `demo_agent.md` skill to send natural language requests
4. Agent translates request → intents → constraints → optimization → scene update
5. Frontend polls `/scene/placements` every 1s and animates changes
6. User can manually add/remove devices or adjust lab size in the UI
7. Click "Auto Layout" to re-optimize with current devices

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"""Layout Optimizer — AI 实验室布局自动排布。
独立开发包,无 ROS 依赖。集成阶段合并到 Uni-Lab-OS。
"""
from .models import Constraint, Device, Lab, Opening, Placement
from .optimizer import optimize
__all__ = ["Device", "Lab", "Opening", "Placement", "Constraint", "optimize"]

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"""2 轴 sweep-and-prune 宽相碰撞检测。
对每个设备计算旋转后的 AABB先沿 x 轴排序并剪枝,
再用 y 轴交叠过滤。返回候选碰撞对(索引对列表),
供后续 OBB SAT 精确检测使用。
"""
from __future__ import annotations
from .models import Device, Placement
def sweep_and_prune_pairs(
devices: list[Device],
placements: list[Placement],
) -> list[tuple[int, int]]:
"""2 轴 sweep-and-prune返回 AABB 交叠的索引对。
Args:
devices: 设备列表,与 placements 一一对应。
placements: 布局位姿列表。
Returns:
候选碰撞对列表,每个元素为 (i, j)
i < j索引对应 placements 原始顺序。
"""
n = len(devices)
if n < 2:
return []
# --- 计算每个设备旋转后的 AABB ---
aabbs: list[tuple[float, float, float, float]] = []
for dev, pl in zip(devices, placements):
hw, hd = pl.rotated_bbox(dev)
aabbs.append((pl.x - hw, pl.x + hw, pl.y - hd, pl.y + hd))
# --- 按 xmin 排序,保留原始索引映射 ---
sorted_indices = sorted(range(n), key=lambda k: aabbs[k][0])
# --- 扫描 x 轴y 轴过滤 ---
candidates: list[tuple[int, int]] = []
for si in range(len(sorted_indices)):
i = sorted_indices[si]
x_min_i, x_max_i, y_min_i, y_max_i = aabbs[i]
for sj in range(si + 1, len(sorted_indices)):
j = sorted_indices[sj]
x_min_j, _x_max_j, y_min_j, y_max_j = aabbs[j]
# 由于按 xmin 排序x_min_j >= x_min_i
if x_min_j > x_max_i:
break # 后续设备 xmin 更大,不可能与 i 在 x 轴交叠
# x 轴交叠确认,检查 y 轴
if y_min_i <= y_max_j and y_min_j <= y_max_i:
# 保证输出 (min_idx, max_idx) 方便去重和测试
pair = (min(i, j), max(i, j))
candidates.append(pair)
return candidates
def broad_phase_device_pairs(
devices: list[Device],
placements: list[Placement],
) -> list[tuple[str, str]]:
"""返回候选碰撞对的 device_id 字符串元组列表。"""
index_pairs = sweep_and_prune_pairs(devices, placements)
return [(placements[i].device_id, placements[j].device_id) for i, j in index_pairs]

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"""约束体系:硬约束 / 软约束定义与统一评估。
硬约束违反 → cost = inf方案直接淘汰
软约束违反 → 加权 penalty 累加到 cost
"""
from __future__ import annotations
import logging
import math
from typing import TYPE_CHECKING
from .broad_phase import sweep_and_prune_pairs
from .models import Constraint, Device, Lab, Placement
from .obb import (
nearest_point_on_obb,
obb_corners,
obb_min_distance,
obb_penetration_depth,
segment_obb_intersection_length,
)
if TYPE_CHECKING:
from typing import Any
from .interfaces import CollisionChecker, ReachabilityChecker
logger = logging.getLogger(__name__)
# 归一化默认权重 — 1cm距离违规 ≈ 5°角度违规 的惩罚量级
DEFAULT_WEIGHT_DISTANCE: float = 100.0 # 1cm → penalty 1.0
DEFAULT_WEIGHT_ANGLE: float = 60.0 # 5° → penalty ~1.0
# 硬约束graduated模式下的惩罚倍数
HARD_MULTIPLIER: float = 5.0
# 优先级等级对应的权重乘数
PRIORITY_MULTIPLIERS: dict[str, float] = {
"critical": 5.0,
"high": 2.0,
"normal": 1.0,
"low": 0.5,
}
def evaluate_constraints(
devices: list[Device],
placements: list[Placement],
lab: Lab,
constraints: list[Constraint],
collision_checker: CollisionChecker,
reachability_checker: ReachabilityChecker | None = None,
*,
graduated: bool = True,
) -> float:
"""统一评估所有约束,返回总 cost。
Args:
devices: 设备列表(与 placements 一一对应)
placements: 当前布局方案
lab: 实验室平面图
constraints: 约束规则列表
collision_checker: 碰撞检测实例
reachability_checker: 可达性检测实例(可选)
graduated: True=比例惩罚DE优化用False=二值inf最终pass/fail用
Returns:
总 cost。硬约束违反在非graduated模式返回 inf否则为加权 penalty 之和。
"""
device_map = {d.id: d for d in devices}
placement_map = {p.device_id: p for p in placements}
total_cost = 0.0
for c in constraints:
cost = _evaluate_single(
c, device_map, placement_map, lab, collision_checker, reachability_checker,
graduated=graduated,
)
if math.isinf(cost):
return math.inf
total_cost += cost
return total_cost
def evaluate_default_hard_constraints(
devices: list[Device],
placements: list[Placement],
lab: Lab,
collision_checker: CollisionChecker,
*,
graduated: bool = True,
collision_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER, # 500
boundary_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER, # 500
) -> float:
"""评估默认硬约束(碰撞 + 边界),无需显式声明约束列表。
始终生效,用于 cost function 的基础检查。
When graduated=True (default), returns a penalty proportional to the
severity of each violation instead of binary inf. This gives DE a
smooth gradient so it can fix specific collision pairs instead of
discarding near-optimal layouts entirely.
When graduated=False, uses the legacy binary inf behaviour.
"""
if not graduated:
return _evaluate_hard_binary(devices, placements, lab, collision_checker)
device_map = {d.id: d for d in devices}
cost = 0.0
# Graduated collision penalty: 2 轴 sweep-and-prune 宽相 + OBB SAT 精确检测
candidate_pairs = sweep_and_prune_pairs(devices, placements)
for i, j in candidate_pairs:
di, dj = device_map[placements[i].device_id], device_map[placements[j].device_id]
ci = obb_corners(placements[i].x, placements[i].y,
di.bbox[0], di.bbox[1], placements[i].theta)
cj = obb_corners(placements[j].x, placements[j].y,
dj.bbox[0], dj.bbox[1], placements[j].theta)
depth = obb_penetration_depth(ci, cj)
if depth > 0:
cost += collision_weight * depth
# Graduated boundary penalty: sum of overshoot distances (rotation-aware)
for p in placements:
dev = device_map[p.device_id]
hw, hd = p.rotated_bbox(dev)
# How far each edge exceeds the lab boundary
overshoot = 0.0
overshoot += max(0.0, hw - p.x) # left wall
overshoot += max(0.0, (p.x + hw) - lab.width) # right wall
overshoot += max(0.0, hd - p.y) # bottom wall
overshoot += max(0.0, (p.y + hd) - lab.depth) # top wall
cost += boundary_weight * overshoot
return cost
def _evaluate_hard_binary(
devices: list[Device],
placements: list[Placement],
lab: Lab,
collision_checker: CollisionChecker,
) -> float:
"""Legacy binary hard-constraint evaluation (inf or 0)."""
checker_placements = _to_checker_format(devices, placements)
collisions = collision_checker.check(checker_placements)
if collisions:
return math.inf
if hasattr(collision_checker, "check_bounds"):
oob = collision_checker.check_bounds(checker_placements, lab.width, lab.depth)
if oob:
return math.inf
return 0.0
def _evaluate_single(
constraint: Constraint,
device_map: dict[str, Device],
placement_map: dict[str, Placement],
lab: Lab,
collision_checker: CollisionChecker,
reachability_checker: ReachabilityChecker | None,
*,
graduated: bool = True,
) -> float:
"""评估单条约束规则。
graduated=True 时硬约束返回比例惩罚DE用
graduated=False 时硬约束返回 inf最终 pass/fail
"""
rule = constraint.rule_name
params = constraint.params
is_hard = constraint.type == "hard"
effective_weight = constraint.weight
if rule == "no_collision":
checker_placements = _to_checker_format_from_maps(device_map, placement_map)
collisions = collision_checker.check(checker_placements)
if collisions:
if is_hard and not graduated:
return math.inf
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * len(collisions)
return 0.0
if rule == "within_bounds":
checker_placements = _to_checker_format_from_maps(device_map, placement_map)
if hasattr(collision_checker, "check_bounds"):
oob = collision_checker.check_bounds(
checker_placements, lab.width, lab.depth
)
if oob:
if is_hard and not graduated:
return math.inf
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * len(oob)
return 0.0
if rule == "distance_less_than":
a_id, b_id = params["device_a"], params["device_b"]
max_dist = params["distance"]
da, db = device_map.get(a_id), device_map.get(b_id)
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
if missing_cost is not None:
return missing_cost
if da and db:
dist = _device_distance_obb(da, pa, db, pb)
else:
dist = _device_distance_center(pa, pb) or 0.0
if dist > max_dist:
if is_hard and not graduated:
return math.inf
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * (dist - max_dist)
return 0.0
if rule == "distance_greater_than":
a_id, b_id = params["device_a"], params["device_b"]
min_dist = params["distance"]
da, db = device_map.get(a_id), device_map.get(b_id)
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
if missing_cost is not None:
return missing_cost
if da and db:
dist = _device_distance_obb(da, pa, db, pb)
else:
dist = _device_distance_center(pa, pb) or 0.0
if dist < min_dist:
if is_hard and not graduated:
return math.inf
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * (min_dist - dist)
return 0.0
if rule == "minimize_distance":
a_id, b_id = params["device_a"], params["device_b"]
da, db = device_map.get(a_id), device_map.get(b_id)
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
if missing_cost is not None:
return missing_cost
if da and db:
dist = _device_distance_obb(da, pa, db, pb)
else:
dist = _device_distance_center(pa, pb) or 0.0
return effective_weight * dist
if rule == "maximize_distance":
a_id, b_id = params["device_a"], params["device_b"]
da, db = device_map.get(a_id), device_map.get(b_id)
pa, pb = placement_map.get(a_id), placement_map.get(b_id)
missing_cost = _missing_reference_cost(constraint, placement_map, a_id, b_id)
if missing_cost is not None:
return missing_cost
if da and db:
dist = _device_distance_obb(da, pa, db, pb)
else:
dist = _device_distance_center(pa, pb) or 0.0
max_possible = math.sqrt(lab.width**2 + lab.depth**2)
return effective_weight * (max_possible - dist)
if rule == "min_spacing":
min_gap = params.get("min_gap", 0.0)
all_placements = list(placement_map.values())
total_penalty = 0.0
for i in range(len(all_placements)):
for j in range(i + 1, len(all_placements)):
pi, pj = all_placements[i], all_placements[j]
di = device_map.get(pi.device_id)
dj = device_map.get(pj.device_id)
if di and dj:
dist = _device_distance_obb(di, pi, dj, pj)
else:
dist = _device_distance_center(pi, pj) or 0.0
if dist < min_gap:
total_penalty += (min_gap - dist)
if total_penalty > 0:
if is_hard and not graduated:
return math.inf
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * total_penalty
return 0.0
if rule == "reachability":
if reachability_checker is None:
return 0.0
arm_id = params["arm_id"]
target_device_id = params["target_device_id"]
arm_p = placement_map.get(arm_id)
target_p = placement_map.get(target_device_id)
missing_cost = _missing_reference_cost(
constraint, placement_map, arm_id, target_device_id,
)
if missing_cost is not None:
return missing_cost
arm_dev = device_map.get(arm_id)
target_dev = device_map.get(target_device_id)
# opening surface center → nearest point on arm OBB
if arm_dev and target_dev:
opening_pt = _opening_surface_center(target_dev, target_p)
arm_corners = obb_corners(
arm_p.x, arm_p.y, arm_dev.bbox[0], arm_dev.bbox[1], arm_p.theta,
)
nearest = nearest_point_on_obb(opening_pt[0], opening_pt[1], arm_corners)
dist = math.sqrt((opening_pt[0] - nearest[0])**2 + (opening_pt[1] - nearest[1])**2)
else:
opening_pt = (target_p.x, target_p.y)
nearest = (arm_p.x, arm_p.y)
dist = _device_distance_center(arm_p, target_p) or 0.0
# 交叉惩罚始终计算soft, 不依赖可达性结果)
crossing_cost = _crossing_penalty(
opening_pt, nearest,
arm_id, target_device_id,
device_map, placement_map,
)
arm_pose = {"x": arm_p.x, "y": arm_p.y, "theta": arm_p.theta}
target_point = {"x": target_p.x, "y": target_p.y, "z": 0.0}
target_point["_obb_dist"] = dist
if not reachability_checker.is_reachable(arm_id, arm_pose, target_point):
if is_hard and not graduated:
return math.inf
# Graduated: overshoot penalty + crossing cost
max_reach = reachability_checker.arm_reach.get(arm_id, 2.0)
overshoot = max(0.0, dist - max_reach)
w = effective_weight * (HARD_MULTIPLIER if is_hard else 1.0)
return w * overshoot * 10.0 + crossing_cost
return crossing_cost
if rule == "prefer_aligned":
alignment_cost = sum(
(1 - math.cos(4 * p.theta)) / 2 for p in placement_map.values()
)
if is_hard:
if not graduated:
return math.inf if alignment_cost > 1e-6 else 0.0
return HARD_MULTIPLIER * effective_weight * alignment_cost
return effective_weight * alignment_cost
if rule == "prefer_seeder_orientation":
target_thetas = params.get("target_thetas", {})
cost = 0.0
for dev_id, target in target_thetas.items():
p = placement_map.get(dev_id)
if p is None:
continue
# Circular distance: (1 - cos(diff)) / 2 gives 0..1 range
diff = p.theta - target
cost += (1 - math.cos(diff)) / 2
return effective_weight * cost
if rule == "prefer_orientation_mode":
mode = params.get("mode", "outward")
center_x = lab.width / 2
center_y = lab.depth / 2
cost = 0.0
for dev_id, p in placement_map.items():
dev = device_map.get(dev_id)
if dev is None:
continue
target = _desired_theta(
p.x, p.y, center_x, center_y, dev, mode,
)
if target is None:
continue
diff = p.theta - target
cost += (1 - math.cos(diff)) / 2
return effective_weight * cost
# 未知约束类型,忽略
return 0.0
def _desired_theta(
x: float, y: float,
center_x: float, center_y: float,
device: Device, mode: str,
) -> float | None:
"""Compute desired theta for outward/inward facing at the given position."""
dx = x - center_x
dy = y - center_y
if abs(dx) < 1e-9 and abs(dy) < 1e-9:
return None # At center, no preferred direction
angle_to_device = math.atan2(dy, dx)
front = device.openings[0].direction if device.openings else (0.0, -1.0)
front_angle = math.atan2(front[1], front[0])
if mode == "outward":
target = angle_to_device
elif mode == "inward":
target = angle_to_device + math.pi
else:
return None
return (target - front_angle) % (2 * math.pi)
def _device_distance_center(a: Placement | None, b: Placement | None) -> float | None:
"""计算两设备中心的欧几里得距离(后备方法)。"""
if a is None or b is None:
return None
return math.sqrt((a.x - b.x) ** 2 + (a.y - b.y) ** 2)
def _device_distance_obb(
device_a: Device, placement_a: Placement,
device_b: Device, placement_b: Placement,
) -> float:
"""Minimum edge-to-edge distance between two devices using OBB."""
corners_a = obb_corners(
placement_a.x, placement_a.y,
device_a.bbox[0], device_a.bbox[1],
placement_a.theta,
)
corners_b = obb_corners(
placement_b.x, placement_b.y,
device_b.bbox[0], device_b.bbox[1],
placement_b.theta,
)
return obb_min_distance(corners_a, corners_b)
def _to_checker_format(
devices: list[Device], placements: list[Placement]
) -> list[dict]:
"""转换为 CollisionChecker.check() 接受的格式。"""
device_map = {d.id: d for d in devices}
result = []
for p in placements:
dev = device_map.get(p.device_id)
if dev is None:
continue
result.append({"id": p.device_id, "bbox": dev.bbox, "pos": (p.x, p.y, p.theta)})
return result
def _to_checker_format_from_maps(
device_map: dict[str, Device], placement_map: dict[str, Placement]
) -> list[dict]:
"""从 map 转换为 CollisionChecker.check() 接受的格式。"""
result = []
for dev_id, p in placement_map.items():
dev = device_map.get(dev_id)
if dev is None:
continue
result.append({"id": dev_id, "bbox": dev.bbox, "pos": (p.x, p.y, p.theta)})
return result
def _opening_surface_center(
device: Device, placement: Placement,
) -> tuple[float, float]:
"""Return the world-space center of the device's opening surface.
Computes where the opening direction intersects the device's bbox boundary,
then transforms to world coordinates. For a device facing away from the arm,
this point is on the far side — making the distance to the arm larger,
which naturally penalizes wrong orientation.
"""
front = device.openings[0].direction if device.openings else (0.0, -1.0)
dx, dy = front
w, h = device.bbox
# Scale factor to reach bbox edge in the opening direction
scales = []
if abs(dx) > 1e-9:
scales.append((w / 2) / abs(dx))
if abs(dy) > 1e-9:
scales.append((h / 2) / abs(dy))
scale = min(scales) if scales else 0.0
# Opening center in local frame
local_x = dx * scale
local_y = dy * scale
# Rotate to world frame and translate
cos_t = math.cos(placement.theta)
sin_t = math.sin(placement.theta)
world_x = placement.x + local_x * cos_t - local_y * sin_t
world_y = placement.y + local_x * sin_t + local_y * cos_t
return (world_x, world_y)
def evaluate_default_hard_constraints_breakdown(
devices: list[Device],
placements: list[Placement],
lab: Lab,
collision_checker: CollisionChecker,
*,
collision_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER,
boundary_weight: float = DEFAULT_WEIGHT_DISTANCE * HARD_MULTIPLIER,
) -> dict[str, float]:
"""与 evaluate_default_hard_constraints 逻辑相同,但返回分项明细。"""
device_map = {d.id: d for d in devices}
collision_cost = 0.0
boundary_cost = 0.0
candidate_pairs = sweep_and_prune_pairs(devices, placements)
for i, j in candidate_pairs:
di, dj = device_map[placements[i].device_id], device_map[placements[j].device_id]
ci = obb_corners(placements[i].x, placements[i].y,
di.bbox[0], di.bbox[1], placements[i].theta)
cj = obb_corners(placements[j].x, placements[j].y,
dj.bbox[0], dj.bbox[1], placements[j].theta)
depth = obb_penetration_depth(ci, cj)
if depth > 0:
collision_cost += collision_weight * depth
for p in placements:
dev = device_map[p.device_id]
hw, hd = p.rotated_bbox(dev)
overshoot = 0.0
overshoot += max(0.0, hw - p.x)
overshoot += max(0.0, (p.x + hw) - lab.width)
overshoot += max(0.0, hd - p.y)
overshoot += max(0.0, (p.y + hd) - lab.depth)
boundary_cost += boundary_weight * overshoot
return {
"collision": collision_cost,
"boundary": boundary_cost,
"total": collision_cost + boundary_cost,
"collision_weight": collision_weight,
"boundary_weight": boundary_weight,
}
def evaluate_constraints_breakdown(
devices: list[Device],
placements: list[Placement],
lab: Lab,
constraints: list[Constraint],
collision_checker: CollisionChecker,
reachability_checker: ReachabilityChecker | None = None,
) -> list[dict[str, Any]]:
"""与 evaluate_constraints 逻辑相同,但返回每条约束的分项明细。"""
device_map = {d.id: d for d in devices}
placement_map = {p.device_id: p for p in placements}
results = []
for c in constraints:
cost = _evaluate_single(
c, device_map, placement_map, lab, collision_checker, reachability_checker,
graduated=True,
)
results.append({
"name": _constraint_display_name(c),
"rule": c.rule_name,
"type": c.type,
"cost": cost,
"weight": c.weight,
})
return results
def _missing_reference_cost(
constraint: Constraint,
placement_map: dict[str, Placement],
*device_ids: str,
) -> float | None:
"""当约束引用不存在的设备时返回对应 cost。"""
missing = sorted({device_id for device_id in device_ids if device_id not in placement_map})
if not missing:
return None
logger.warning(
"Constraint %s references missing device IDs: %s",
constraint.rule_name,
", ".join(missing),
)
if constraint.type == "hard":
return math.inf
return 0.0
def _constraint_display_name(c: Constraint) -> str:
"""为约束生成可读的显示名称。"""
params = c.params
if c.rule_name in (
"distance_less_than", "distance_greater_than",
"minimize_distance", "maximize_distance",
):
return f"{c.rule_name}({params.get('device_a', '?')}, {params.get('device_b', '?')})"
if c.rule_name == "reachability":
return f"reachability({params.get('arm_id', '?')}, {params.get('target_device_id', '?')})"
if c.rule_name == "min_spacing":
return f"min_spacing(gap={params.get('min_gap', '?')})"
if c.rule_name == "prefer_orientation_mode":
return f"prefer_orientation_mode({params.get('mode', '?')})"
return c.rule_name
def _crossing_penalty(
opening_pt: tuple[float, float],
arm_nearest_pt: tuple[float, float],
arm_id: str,
target_id: str,
device_map: dict[str, Device],
placement_map: dict[str, Placement],
) -> float:
"""交叉惩罚:其他设备 OBB 遮挡 opening→arm 路径的长度加权 penalty。
Soft penalty权重 = DEFAULT_WEIGHT_DISTANCE * 穿过各遮挡设备 OBB 的线段长度之和。
始终生效(不论可达性是否通过),为 DE 提供清晰的梯度信号。
"""
cost = 0.0
for dev_id, p in placement_map.items():
if dev_id == arm_id or dev_id == target_id:
continue
dev = device_map.get(dev_id)
if dev is None:
continue
corners = obb_corners(p.x, p.y, dev.bbox[0], dev.bbox[1], p.theta)
crossing_len = segment_obb_intersection_length(opening_pt, arm_nearest_pt, corners)
cost += DEFAULT_WEIGHT_DISTANCE * crossing_len
return cost

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"""双源设备目录:从 uni-lab-assets 和 Uni-Lab-OS registry 加载设备。
数据流:
footprints.json (离线提取) + data.json (资产树) + registry device_mesh dirs
→ merge → Device 列表
footprints.json 由 extract_footprints.py 生成,包含碰撞包围盒、开口方向等。
"""
from __future__ import annotations
from collections import Counter
import json
import logging
from pathlib import Path
from .models import Device, Opening
logger = logging.getLogger(__name__)
# 默认路径(相对于本文件)
_THIS_DIR = Path(__file__).resolve().parent
_DEFAULT_FOOTPRINTS = _THIS_DIR / "footprints.json"
# 手动后备尺寸trimesh 不可用时)
KNOWN_SIZES: dict[str, tuple[float, float]] = {
"elite_cs66_arm": (0.20, 0.20),
"elite_cs612_arm": (0.20, 0.20),
"ot2": (0.62, 0.50),
"agilent_bravo": (0.80, 0.65),
"thermo_orbitor_rs2": (0.45, 0.55),
"hplc_station": (0.60, 0.50),
"1_3m_hamilton_table": (1.30, 0.75),
}
DEFAULT_BBOX: tuple[float, float] = (0.6, 0.4)
# ---------- footprints.json 加载 ----------
_footprints_cache: dict[str, dict] | None = None
def load_footprints(path: str | Path = _DEFAULT_FOOTPRINTS) -> dict[str, dict]:
"""加载 footprints.json 并缓存。"""
global _footprints_cache
if _footprints_cache is not None:
return _footprints_cache
p = Path(path)
if not p.exists():
logger.warning("footprints.json not found at %s", p)
_footprints_cache = {}
return _footprints_cache
with open(p) as f:
_footprints_cache = json.load(f)
logger.info("Loaded %d footprints from %s", len(_footprints_cache), p)
return _footprints_cache
def reset_footprints_cache() -> None:
"""清除缓存(测试用)。"""
global _footprints_cache
_footprints_cache = None
# ---------- 从 footprints 构建 Device ----------
def _footprint_to_device(
device_id: str,
fp: dict,
name: str = "",
models_url_prefix: str = "/models",
) -> Device:
"""从 footprints.json 条目创建 Device。"""
bbox = tuple(fp.get("bbox", DEFAULT_BBOX))
openings = [
Opening(direction=tuple(o["direction"]), label=o.get("label", ""))
for o in fp.get("openings", [])
]
model_file = fp.get("model_file", "")
model_path = f"{models_url_prefix}/{device_id}/{model_file}" if model_file else ""
model_type = fp.get("model_type", "")
thumb_file = fp.get("thumbnail_file", "")
thumbnail_url = f"{models_url_prefix}/{device_id}/{thumb_file}" if thumb_file else ""
return Device(
id=device_id,
name=name or device_id.replace("_", " ").title(),
bbox=bbox,
device_type="articulation" if "robot" in device_id or "arm" in device_id or "flex" in device_id else "static",
height=fp.get("height", 0.4),
origin_offset=tuple(fp.get("origin_offset", [0.0, 0.0])),
openings=openings,
source=fp.get("source", "manual"),
model_path=model_path,
model_type=model_type,
thumbnail_url=thumbnail_url,
)
# ---------- 从 data.json 加载 ----------
def load_devices_from_assets(
data_json_path: str | Path,
footprints: dict[str, dict] | None = None,
models_url_prefix: str = "/models",
) -> list[Device]:
"""从 uni-lab-assets 的 data.json 加载设备列表。
如果设备在 footprints 中有条目,使用真实尺寸;否则使用默认值。
"""
path = Path(data_json_path)
if not path.exists():
logger.warning("data.json not found at %s, returning empty list", path)
return []
if footprints is None:
footprints = load_footprints()
with open(path) as f:
data = json.load(f)
devices: list[Device] = []
_flatten_tree(data, devices, footprints, models_url_prefix)
return devices
def _flatten_tree(
nodes: list[dict],
result: list[Device],
footprints: dict[str, dict],
models_url_prefix: str,
) -> None:
"""递归遍历树形结构,提取叶节点为 Device。"""
for node in nodes:
if "children" in node:
_flatten_tree(node["children"], result, footprints, models_url_prefix)
elif "id" in node:
device_id = node["id"]
name = node.get("label", device_id)
if device_id in footprints:
dev = _footprint_to_device(
device_id, footprints[device_id], name, models_url_prefix
)
else:
bbox = KNOWN_SIZES.get(device_id, DEFAULT_BBOX)
dev = Device(id=device_id, name=name, bbox=bbox, source="assets")
result.append(dev)
# ---------- 从 registry 加载 ----------
def load_devices_from_registry(
device_mesh_dir: str | Path,
footprints: dict[str, dict] | None = None,
models_url_prefix: str = "/models",
) -> list[Device]:
"""从 Uni-Lab-OS device_mesh/devices/ 加载 registry 设备。"""
d = Path(device_mesh_dir)
if not d.exists():
logger.warning("Registry dir not found at %s", d)
return []
if footprints is None:
footprints = load_footprints()
devices: list[Device] = []
for entry in sorted(d.iterdir()):
if not entry.is_dir():
continue
device_id = entry.name
if device_id in footprints:
dev = _footprint_to_device(
device_id, footprints[device_id], models_url_prefix=models_url_prefix
)
dev.source = "registry"
else:
bbox = KNOWN_SIZES.get(device_id, DEFAULT_BBOX)
dev = Device(id=device_id, name=device_id.replace("_", " ").title(), bbox=bbox, source="registry")
devices.append(dev)
return devices
# ---------- 合并与去重 ----------
def merge_device_lists(
registry_devices: list[Device],
asset_devices: list[Device],
) -> list[Device]:
"""合并双源设备列表registry 优先。
对于同时存在于两个源的设备,使用 registry 条目的元数据,
但优先使用 assets 的 3D 模型路径和缩略图。
"""
merged: dict[str, Device] = {}
for dev in asset_devices:
merged[dev.id] = dev
for dev in registry_devices:
if dev.id in merged:
# registry 元数据优先,但保留 assets 的模型/缩略图
asset_dev = merged[dev.id]
dev.model_path = dev.model_path or asset_dev.model_path
dev.model_type = dev.model_type or asset_dev.model_type
dev.thumbnail_url = dev.thumbnail_url or asset_dev.thumbnail_url
if dev.bbox == DEFAULT_BBOX and asset_dev.bbox != DEFAULT_BBOX:
dev.bbox = asset_dev.bbox
dev.height = asset_dev.height
dev.origin_offset = asset_dev.origin_offset
dev.openings = asset_dev.openings
dev.source = "registry"
merged[dev.id] = dev
return list(merged.values())
# ---------- 统一解析器 ----------
def resolve_device(
device_id: str,
footprints: dict[str, dict] | None = None,
models_url_prefix: str = "/models",
) -> Device | None:
"""按 ID 查找单个设备。先查 footprints再查 KNOWN_SIZES。"""
if footprints is None:
footprints = load_footprints()
if device_id in footprints:
return _footprint_to_device(
device_id, footprints[device_id], models_url_prefix=models_url_prefix
)
if device_id in KNOWN_SIZES:
bbox = KNOWN_SIZES[device_id]
return Device(id=device_id, name=device_id.replace("_", " ").title(), bbox=bbox, source="manual")
return None
# ---------- 向后兼容 ----------
def create_devices_from_list(
device_specs: list[dict],
) -> list[Device]:
"""从 API 请求中的设备列表创建 Device 对象(向后兼容)。
Args:
device_specs: [{"id": str, "name": str, "size": [w, d], "uuid": str}, ...]
size 可选,缺失时使用 footprints 或默认值。
"""
footprints = load_footprints()
devices = []
catalog_counts = Counter(spec["id"] for spec in device_specs)
catalog_seen: Counter[str] = Counter()
for spec in device_specs:
catalog_id = spec["id"]
catalog_seen[catalog_id] += 1
instance_idx = catalog_seen[catalog_id]
if catalog_counts[catalog_id] > 1 and instance_idx > 1:
dev_id = f"{catalog_id}#{instance_idx}"
else:
dev_id = catalog_id
size = spec.get("size")
if size:
bbox = (float(size[0]), float(size[1]))
elif catalog_id in footprints:
bbox = tuple(footprints[catalog_id].get("bbox", DEFAULT_BBOX))
else:
bbox = KNOWN_SIZES.get(catalog_id, DEFAULT_BBOX)
openings = []
if catalog_id in footprints:
openings = [
Opening(direction=tuple(o["direction"]), label=o.get("label", ""))
for o in footprints[catalog_id].get("openings", [])
]
devices.append(
Device(
id=dev_id,
name=spec.get("name", catalog_id),
bbox=bbox,
device_type=spec.get("device_type", "static"),
openings=openings,
uuid=spec.get("uuid", ""),
)
)
return devices

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"""从 STL/GLB 网格提取设备足迹(碰撞包围盒)。
运行方式:
conda activate phase3
python -m layout_optimizer.extract_footprints
输出 footprints.json 供 device_catalog.py 和 2D 规划器使用。
GLB root node rotation:
每个设备的 GLB 文件包含根节点旋转四元数,定义 STL 原生坐标到 glTF Y-up
约定的轴映射。extract_one_device() 读取 GLB JSON提取旋转矩阵
应用到 STL 包围盒后按 glTF 约定提取 2D 足迹 (X=width, Z=depth, Y=height)。
GLB scale 不应用——STL 文件已是米制坐标。
"""
from __future__ import annotations
import argparse
import json
import logging
import math
import os
import re
import struct
import xml.etree.ElementTree as ET
from pathlib import Path
logger = logging.getLogger(__name__)
# 测试设备的开口方向(手动标注)
# direction 为设备局部坐标系中的单位向量,[0, -1] 表示设备正前方
MANUAL_OPENINGS: dict[str, list[dict]] = {
"agilent_bravo": [{"direction": [0, -1], "label": "front_plate_slot"}],
"opentrons_liquid_handler": [{"direction": [0, -1], "label": "front_deck"}],
"opentrons_flex": [{"direction": [0, -1], "label": "front_deck"}],
"thermo_orbitor_rs2_hotel": [{"direction": [0, -1], "label": "front_door"}],
"hamilton_star": [{"direction": [0, -1], "label": "front_deck"}],
"tecan_spark_plate_reader": [{"direction": [0, -1], "label": "front_slot"}],
"highres_bio_plate_hotel_12": [{"direction": [0, -1], "label": "front_shelf"}],
"beckman_coulter_orbital_shaker_alp": [],
"liconic_str44_incubator": [{"direction": [0, -1], "label": "front_door"}],
"elite_robot": [], # 机械臂,无开口
}
# 手动尺寸后备trimesh 提取失败时使用)
FALLBACK_SIZES: dict[str, tuple[float, float, float]] = {
"elite_robot": (0.20, 0.20, 0.10),
"elite_cs66_arm": (0.20, 0.20, 0.10),
"elite_cs612_arm": (0.20, 0.20, 0.10),
}
def extract_openings_from_xacro(
xacro_path: Path,
bbox_center_xy: tuple[float, float],
bbox_size_xy: tuple[float, float],
) -> list[dict]:
"""从 XACRO 文件自动提取设备开口方向。
解析 fixed joint 中包含 "socket" 的关节,计算其 XY 质心,与包围盒中心比较,
映射到最近的基本方向。
Args:
xacro_path: modal.xacro 文件路径
bbox_center_xy: 包围盒 XY 中心 (cx, cy)
bbox_size_xy: 包围盒 XY 尺寸 (w, d)
Returns:
[{"direction": [dx, dy], "label": "auto_xacro"}] 或 []
"""
# --- 方法1: ElementTree 解析(忽略 xacro 命名空间) ---
socket_positions: list[tuple[float, float]] = []
try:
xacro_text = xacro_path.read_text(encoding="utf-8", errors="replace")
# 去掉 xacro 命名空间前缀,避免 ElementTree 解析失败
xacro_text_clean = re.sub(r'\bxacro:', '', xacro_text)
root = ET.fromstring(xacro_text_clean)
for joint in root.iter("joint"):
joint_name = joint.get("name", "")
joint_type = joint.get("type", "")
if "socket" not in joint_name.lower():
continue
if joint_type != "fixed":
continue
origin = joint.find("origin")
if origin is None:
continue
xyz_str = origin.get("xyz", "")
if not xyz_str:
continue
parts = xyz_str.split()
if len(parts) < 2:
continue
try:
x = float(parts[0])
y = float(parts[1])
socket_positions.append((x, y))
except ValueError:
continue
except ET.ParseError as e:
logger.debug("ElementTree parse error for %s: %s — falling back to regex", xacro_path, e)
# --- 方法2: 正则表达式后备(当 ElementTree 失败或无结果时) ---
if not socket_positions:
try:
xacro_text = xacro_path.read_text(encoding="utf-8", errors="replace")
# 匹配包含 "socket" 的 joint 块,提取 origin xyz
joint_blocks = re.findall(
r'<joint\s[^>]*name=["\'][^"\']*socket[^"\']*["\'][^>]*>.*?</joint>',
xacro_text,
flags=re.IGNORECASE | re.DOTALL,
)
for block in joint_blocks:
# 只处理 fixed 类型
if 'type="fixed"' not in block and "type='fixed'" not in block:
continue
xyz_match = re.search(r'<origin[^>]*xyz=["\']([^"\']+)["\']', block)
if not xyz_match:
continue
parts = xyz_match.group(1).split()
if len(parts) < 2:
continue
try:
x = float(parts[0])
y = float(parts[1])
socket_positions.append((x, y))
except ValueError:
continue
except Exception as e:
logger.debug("Regex fallback also failed for %s: %s", xacro_path, e)
if not socket_positions:
return []
# 计算 socket XY 质心
cx_sock = sum(p[0] for p in socket_positions) / len(socket_positions)
cy_sock = sum(p[1] for p in socket_positions) / len(socket_positions)
# 方向向量:从包围盒中心指向 socket 质心
dx = cx_sock - bbox_center_xy[0]
dy = cy_sock - bbox_center_xy[1]
# 如果 socket 质心非常靠近包围盒中心(<5% 尺寸),判断为顶部装载
threshold = 0.05 * max(bbox_size_xy[0], bbox_size_xy[1], 1e-6)
if math.hypot(dx, dy) < threshold:
logger.debug(
"%s: socket centroid too close to bbox center (dist=%.4f, threshold=%.4f) → top-loading",
xacro_path.parent.name,
math.hypot(dx, dy),
threshold,
)
return []
# 映射到最近基本方向
# socket 质心指示交互区在设备哪一侧,而 opening direction 是从该面
# 向外的法线方向(与质心偏移同向),这里的 dx/dy 已经是从包围盒中心
# 指向 socket 区域的方向,即 opening 朝外的方向
# 注意:在 uni-lab-assets 中,大多数设备 front 在 Y=0 而 body 在 -Y
# 所以 socket 集中在 +Y 侧(靠近 Y=0 前端bbox 中心在 -Y/2。
# 方向 center→socket = +Y但 "opening faces front" 在手动标注中
# 写作 [0, -1](法线向外=向操作者方向)。
# 因此需要取反opening direction = -(center→socket)
if abs(dx) >= abs(dy):
cardinal = [-1, 0] if dx > 0 else [1, 0]
else:
cardinal = [0, -1] if dy > 0 else [0, 1]
logger.debug(
"%s: %d socket joints → centroid=(%.3f, %.3f) dir=%s",
xacro_path.parent.name,
len(socket_positions),
cx_sock,
cy_sock,
cardinal,
)
return [{"direction": cardinal, "label": "auto_xacro"}]
def _find_mesh_files(device_dir: Path) -> list[Path]:
"""查找设备目录中的所有 STL/GLB 网格文件。"""
mesh_files: list[Path] = []
meshes_dir = device_dir / "meshes"
if not meshes_dir.exists():
return mesh_files
# uni-lab-assets 结构: meshes/*.stl, meshes/*.glb
for f in meshes_dir.iterdir():
if f.suffix.lower() in (".stl", ".glb"):
mesh_files.append(f)
# registry 结构: meshes/<variant>/collision/*.stl
if not mesh_files:
for variant_dir in meshes_dir.iterdir():
if variant_dir.is_dir():
collision_dir = variant_dir / "collision"
if collision_dir.exists():
for f in collision_dir.iterdir():
if f.suffix.lower() == ".stl":
mesh_files.append(f)
if mesh_files:
break # 使用找到的第一个变体
return sorted(mesh_files)
def _find_best_model_file(device_dir: Path) -> tuple[str, str]:
"""找到最佳可展示的模型文件。优先 GLB > STL。
Returns:
(relative_path, model_type) e.g. ("meshes/0_base.glb", "gltf")
"""
meshes_dir = device_dir / "meshes"
if not meshes_dir.exists():
return "", ""
glbs = sorted(meshes_dir.glob("*.glb"))
if glbs:
return f"meshes/{glbs[0].name}", "gltf"
stls = sorted(f for f in meshes_dir.glob("*.stl") if f.suffix == ".stl")
if not stls:
stls = sorted(f for f in meshes_dir.glob("*.STL"))
if stls:
return f"meshes/{stls[0].name}", "stl"
return "", ""
def _find_thumbnail(device_dir: Path) -> str:
"""查找设备目录中的第一个 PNG 缩略图。"""
pngs = sorted(device_dir.glob("*.png"))
if pngs:
return pngs[0].name
return ""
def _read_glb_json(glb_path: Path) -> dict | None:
"""Read the JSON chunk from a GLB (Binary glTF) file.
GLB structure: 12-byte header + chunks. Chunk 0 is JSON.
Returns parsed dict or None on failure.
"""
try:
with open(glb_path, "rb") as f:
header = f.read(12)
if len(header) < 12:
return None
magic, version, length = struct.unpack("<III", header)
if magic != 0x46546C67: # 'glTF'
return None
chunk_header = f.read(8)
if len(chunk_header) < 8:
return None
chunk_length, chunk_type = struct.unpack("<II", chunk_header)
if chunk_type != 0x4E4F534A: # 'JSON'
return None
json_bytes = f.read(chunk_length)
return json.loads(json_bytes)
except Exception as e:
logger.debug("Failed to read GLB JSON from %s: %s", glb_path, e)
return None
def _quat_to_matrix(q: list[float]) -> list[list[float]]:
"""Convert quaternion [x, y, z, w] to 3×3 rotation matrix."""
x, y, z, w = q
return [
[1 - 2*(y*y + z*z), 2*(x*y - z*w), 2*(x*z + y*w)],
[ 2*(x*y + z*w), 1 - 2*(x*x + z*z), 2*(y*z - x*w)],
[ 2*(x*z - y*w), 2*(y*z + x*w), 1 - 2*(x*x + y*y)],
]
def _get_glb_root_rotation(device_dir: Path) -> list[list[float]] | None:
"""Extract root node rotation matrix from the first GLB in device_dir/meshes/.
Only rotation is extracted — GLB scale is NOT applied because STL files
are already in meters while GLB scale converts GLB mesh units (often mm)
to scene units. Since we read STL directly, scale is irrelevant.
Returns 3×3 rotation matrix or None if no GLB or no rotation found.
"""
meshes_dir = device_dir / "meshes"
if not meshes_dir.exists():
return None
glbs = sorted(meshes_dir.glob("*.glb"))
if not glbs:
return None
gltf = _read_glb_json(glbs[0])
if gltf is None:
return None
nodes = gltf.get("nodes", [])
if not nodes:
return None
root = nodes[0]
rotation = root.get("rotation")
if rotation is None:
return None
# Skip identity quaternion [0,0,0,1]
x, y, z, w = rotation
if abs(x) < 1e-9 and abs(y) < 1e-9 and abs(z) < 1e-9 and abs(w - 1.0) < 1e-9:
return None
return _quat_to_matrix(rotation)
def _apply_rotation_to_bbox(
stl_min: list[float], stl_max: list[float],
rot: list[list[float]],
) -> tuple[list[float], list[float]]:
"""Apply rotation to an axis-aligned bounding box.
Transforms all 8 corners of the STL AABB through rotation,
then computes the new AABB in glTF space.
"""
corners = []
for x in (stl_min[0], stl_max[0]):
for y in (stl_min[1], stl_max[1]):
for z in (stl_min[2], stl_max[2]):
tx = rot[0][0]*x + rot[0][1]*y + rot[0][2]*z
ty = rot[1][0]*x + rot[1][1]*y + rot[1][2]*z
tz = rot[2][0]*x + rot[2][1]*y + rot[2][2]*z
corners.append((tx, ty, tz))
xs = [c[0] for c in corners]
ys = [c[1] for c in corners]
zs = [c[2] for c in corners]
return [min(xs), min(ys), min(zs)], [max(xs), max(ys), max(zs)]
def extract_one_device(device_dir: Path) -> dict | None:
"""提取单个设备的足迹信息。"""
try:
import trimesh
except ImportError:
logger.error("trimesh not installed. Run: pip install trimesh")
return None
mesh_files = _find_mesh_files(device_dir)
if not mesh_files:
return None
# 加载所有网格部件并计算联合包围盒
meshes = []
for f in mesh_files:
try:
m = trimesh.load(str(f), force="mesh")
if hasattr(m, "bounds") and m.bounds is not None:
meshes.append(m)
except Exception as e:
logger.warning("Failed to load %s: %s", f, e)
if not meshes:
return None
if len(meshes) == 1:
combined = meshes[0]
else:
combined = trimesh.util.concatenate(meshes)
bounds = combined.bounds
stl_min = [float(bounds[0][i]) for i in range(3)]
stl_max = [float(bounds[1][i]) for i in range(3)]
# 应用 GLB 根节点旋转到 STL 包围盒scale 不应用 — STL 已是米制)
# glTF 约定: X=right, Y=up, Z=forward → 2D 足迹取 X 和 Z, 高度取 Y
rot = _get_glb_root_rotation(device_dir)
if rot is not None:
t_min, t_max = _apply_rotation_to_bbox(stl_min, stl_max, rot)
t_size = [t_max[i] - t_min[i] for i in range(3)]
t_center = [(t_min[i] + t_max[i]) / 2 for i in range(3)]
# glTF Y-up: X=width, Z=depth, Y=height
bbox_w = round(t_size[0], 4)
bbox_d = round(t_size[2], 4)
height = round(t_size[1], 4)
origin_offset = [round(t_center[0], 4), round(t_center[2], 4)]
logger.debug(
"%s: GLB rotation applied → bbox=[%.3f, %.3f] height=%.3f",
device_dir.name, bbox_w, bbox_d, height,
)
else:
# 无 GLB 或 identity rotation → 沿用原始 STL 坐标 (X=width, Y=depth, Z=height)
size = [stl_max[i] - stl_min[i] for i in range(3)]
center = [(stl_min[i] + stl_max[i]) / 2 for i in range(3)]
bbox_w = round(size[0], 4)
bbox_d = round(size[1], 4)
height = round(size[2], 4)
origin_offset = [round(center[0], 4), round(center[1], 4)]
model_file, model_type = _find_best_model_file(device_dir)
thumbnail_file = _find_thumbnail(device_dir)
device_id = device_dir.name
# 确定 openings手动标注优先否则尝试从 XACRO 自动提取
# 注意XACRO socket 坐标是 STL 原生坐标系,这里传入变换后的 bbox
if device_id in MANUAL_OPENINGS:
openings = MANUAL_OPENINGS[device_id]
else:
xacro_path = device_dir / "modal.xacro"
if xacro_path.exists():
openings = extract_openings_from_xacro(
xacro_path,
bbox_center_xy=(origin_offset[0], origin_offset[1]),
bbox_size_xy=(bbox_w, bbox_d),
)
else:
openings = []
result: dict = {
"bbox": [bbox_w, bbox_d],
"height": height,
"origin_offset": origin_offset,
"model_file": model_file,
"model_type": model_type,
"thumbnail_file": thumbnail_file,
"openings": openings,
}
return result
def extract_all(
assets_dir: Path | None = None,
registry_dir: Path | None = None,
device_ids: list[str] | None = None,
) -> dict[str, dict]:
"""提取所有(或指定)设备的足迹。
Args:
assets_dir: uni-lab-assets/device_models/ 路径
registry_dir: Uni-Lab-OS/unilabos/device_mesh/devices/ 路径
device_ids: 仅提取指定设备None = 全部扫描)
Returns:
{device_id: footprint_dict}
"""
results: dict[str, dict] = {}
dirs_to_scan: list[tuple[Path, str]] = []
if assets_dir and assets_dir.exists():
for d in sorted(assets_dir.iterdir()):
if d.is_dir() and (device_ids is None or d.name in device_ids):
dirs_to_scan.append((d, "assets"))
if registry_dir and registry_dir.exists():
for d in sorted(registry_dir.iterdir()):
if d.is_dir() and (device_ids is None or d.name in device_ids):
if d.name not in results: # assets 已有的不重复扫描
dirs_to_scan.append((d, "registry"))
for device_dir, source in dirs_to_scan:
device_id = device_dir.name
if device_id in results:
continue
footprint = extract_one_device(device_dir)
if footprint:
footprint["source"] = source
results[device_id] = footprint
logger.info(
"Extracted %s: bbox=%s height=%.3f source=%s",
device_id,
footprint["bbox"],
footprint["height"],
source,
)
# 统计自动提取的 openings 数量
auto_xacro_count = sum(
1
for fp in results.values()
if any(o.get("label") == "auto_xacro" for o in fp.get("openings", []))
)
logger.info(
"Auto-extracted openings from XACRO for %d / %d devices",
auto_xacro_count,
len(results),
)
# 手动后备
for dev_id, (w, d, h) in FALLBACK_SIZES.items():
if dev_id not in results:
results[dev_id] = {
"bbox": [w, d],
"height": h,
"origin_offset": [0.0, 0.0],
"model_file": "",
"model_type": "",
"thumbnail_file": "",
"openings": MANUAL_OPENINGS.get(dev_id, []),
"source": "manual",
}
return results
def main() -> None:
parser = argparse.ArgumentParser(
description="Extract device footprints from STL/GLB meshes"
)
parser.add_argument(
"--assets-dir",
type=Path,
default=Path(__file__).resolve().parent.parent / "uni-lab-assets" / "device_models",
help="Path to uni-lab-assets/device_models/",
)
parser.add_argument(
"--registry-dir",
type=Path,
default=Path(__file__).resolve().parent / "Uni-Lab-OS" / "unilabos" / "device_mesh" / "devices",
help="Path to Uni-Lab-OS device_mesh/devices/",
)
parser.add_argument(
"--output",
type=Path,
default=Path(__file__).resolve().parent / "footprints.json",
help="Output JSON path",
)
parser.add_argument(
"--devices",
nargs="*",
default=None,
help="Only extract these device IDs (default: all)",
)
parser.add_argument("-v", "--verbose", action="store_true")
args = parser.parse_args()
logging.basicConfig(
level=logging.DEBUG if args.verbose else logging.INFO,
format="%(levelname)s: %(message)s",
)
logger.info("Assets dir: %s (exists=%s)", args.assets_dir, args.assets_dir.exists())
logger.info("Registry dir: %s (exists=%s)", args.registry_dir, args.registry_dir.exists())
results = extract_all(
assets_dir=args.assets_dir,
registry_dir=args.registry_dir,
device_ids=args.devices,
)
with open(args.output, "w") as f:
json.dump(results, f, indent=2, ensure_ascii=False)
logger.info("Wrote %d devices to %s", len(results), args.output)
if __name__ == "__main__":
main()

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"""
Generate a YAML registry file for all devices in uni-lab-assets that don't
already have a registry entry (identified by model.mesh value).
Output: Uni-Lab-OS/unilabos/registry/devices/asset_models.yaml
"""
import json
from pathlib import Path
import yaml
# ---------------------------------------------------------------------------
# Paths (resolved relative to this script's location)
# ---------------------------------------------------------------------------
REPO_ROOT = Path(__file__).parent.parent
ASSETS_DIR = REPO_ROOT.parent / "uni-lab-assets" / "device_models"
REGISTRY_DIR = REPO_ROOT / "Uni-Lab-OS" / "unilabos" / "registry" / "devices"
OUTPUT_FILE = REGISTRY_DIR / "asset_models.yaml"
OSS_BASE = (
"https://uni-lab.oss-cn-zhangjiakou.aliyuncs.com/uni-lab/devices"
)
CONTAINER_CLASS = (
"unilabos.devices.resource_container.container:HotelContainer"
)
# ---------------------------------------------------------------------------
# Step 1 — collect mesh names already present in the registry
# ---------------------------------------------------------------------------
def collect_registered_meshes() -> set[str]:
"""Return the set of mesh values found in all existing registry YAML files."""
registered: set[str] = set()
for yaml_file in REGISTRY_DIR.glob("*.yaml"):
# Skip the output file itself so the script is idempotent
if yaml_file == OUTPUT_FILE:
continue
try:
with yaml_file.open("r", encoding="utf-8") as fh:
data = yaml.safe_load(fh)
except Exception as exc:
print(f" [warn] Could not parse {yaml_file.name}: {exc}")
continue
if not isinstance(data, dict):
continue
for _key, entry in data.items():
if not isinstance(entry, dict):
continue
model = entry.get("model")
if isinstance(model, dict):
mesh = model.get("mesh")
if mesh:
registered.add(str(mesh))
return registered
# ---------------------------------------------------------------------------
# Step 2 — scan uni-lab-assets/device_models/
# ---------------------------------------------------------------------------
def scan_asset_devices() -> list[dict]:
"""
Return a list of device dicts for every subfolder that has a modal.xacro.
Each dict has keys: folder_name, description.
"""
devices = []
if not ASSETS_DIR.is_dir():
raise FileNotFoundError(f"Assets directory not found: {ASSETS_DIR}")
for device_dir in sorted(ASSETS_DIR.iterdir()):
if not device_dir.is_dir():
continue
folder_name = device_dir.name
# modal.xacro is required
if not (device_dir / "modal.xacro").exists():
continue
# Read optional meta.json
description = folder_name
meta_path = device_dir / "meta.json"
if meta_path.exists():
try:
with meta_path.open("r", encoding="utf-8") as fh:
meta = json.load(fh)
# Use name field if present; otherwise fall back to folder name
description = meta.get("name", folder_name)
except Exception as exc:
print(f" [warn] Could not parse {meta_path}: {exc}")
devices.append(
{
"folder_name": folder_name,
"description": description,
}
)
return devices
# ---------------------------------------------------------------------------
# Step 3 — build registry entry for a single device
# ---------------------------------------------------------------------------
def build_entry(folder_name: str, description: str) -> dict:
return {
"category": ["asset_model"],
"class": {
"action_value_mappings": {},
"module": CONTAINER_CLASS,
"status_types": {},
"type": "python",
},
"config_info": [],
"description": description,
"handles": [],
"icon": "",
"init_param_schema": {
"config": {
"properties": {},
"required": [],
"type": "object",
},
"data": {
"properties": {},
"required": [],
"type": "object",
},
},
"model": {
"mesh": folder_name,
"path": f"{OSS_BASE}/{folder_name}/macro_device.xacro",
"type": "device",
},
"version": "1.0.0",
}
# ---------------------------------------------------------------------------
# Main
# ---------------------------------------------------------------------------
def main() -> None:
print("Scanning existing registry for registered meshes...")
registered_meshes = collect_registered_meshes()
print(f" Found {len(registered_meshes)} already-registered mesh(es).")
print(f"\nScanning asset devices in: {ASSETS_DIR}")
all_devices = scan_asset_devices()
print(f" Found {len(all_devices)} device folder(s) with modal.xacro.")
registry: dict[str, dict] = {}
skipped = 0
generated = 0
for device in all_devices:
folder_name = device["folder_name"]
if folder_name in registered_meshes:
skipped += 1
continue
key = f"asset_model.{folder_name}"
registry[key] = build_entry(folder_name, device["description"])
generated += 1
print(f"\nWriting {generated} new entr(ies) to: {OUTPUT_FILE}")
OUTPUT_FILE.parent.mkdir(parents=True, exist_ok=True)
with OUTPUT_FILE.open("w", encoding="utf-8") as fh:
yaml.dump(
registry,
fh,
default_flow_style=False,
allow_unicode=True,
sort_keys=False,
)
print("\n--- Summary ---")
print(f" Total devices found (with modal.xacro): {len(all_devices)}")
print(f" Already registered (skipped): {skipped}")
print(f" Newly generated: {generated}")
if __name__ == "__main__":
main()

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"""意图解释器:将语义化意图翻译为 Constraint 列表。"""
from __future__ import annotations
import itertools
from collections.abc import Callable
from dataclasses import dataclass, field
from .constraints import PRIORITY_MULTIPLIERS
from .models import Constraint, Intent
# 优先级权重映射
_PRIORITY_WEIGHTS: dict[str, float] = {"low": 1.0, "medium": 3.0, "high": 8.0}
_DEFAULT_WEIGHT = _PRIORITY_WEIGHTS["medium"]
def _priority_key(priority: str) -> str:
"""将 intent priority 映射到 constraint 权重等级。"""
return "normal" if priority == "medium" else priority
def _final_weight(base_weight: float, priority: str) -> float:
"""在解释阶段直接烘焙优先级乘数。"""
return base_weight * PRIORITY_MULTIPLIERS.get(priority, 1.0)
@dataclass
class InterpretResult:
"""意图解释结果。"""
constraints: list[Constraint] = field(default_factory=list)
translations: list[dict] = field(default_factory=list)
errors: list[str] = field(default_factory=list)
workflow_edges: list[list[str]] = field(default_factory=list)
def _handle_reachable_by(intent: Intent, result: InterpretResult) -> None:
"""reachable_by机械臂必须能到达指定设备列表。"""
arm = intent.params.get("arm")
targets = intent.params.get("targets", [])
if arm is None:
result.errors.append(f"reachable_by: 缺少必要参数 'arm'")
return
if not targets:
result.errors.append(f"reachable_by: 参数 'targets' 不能为空")
return
generated: list[dict] = []
for target in targets:
c = Constraint(
type="hard",
rule_name="reachability",
params={"arm_id": arm, "target_device_id": target},
weight=_final_weight(1.0, "critical"),
)
result.constraints.append(c)
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": generated,
"explanation": f"机械臂 '{arm}' 需要能够到达 {len(targets)} 个目标设备",
})
def _handle_close_together(intent: Intent, result: InterpretResult) -> None:
"""close_together设备组内两两最小化距离。"""
devices: list[str] = intent.params.get("devices", [])
priority: str = intent.params.get("priority", "medium")
if len(devices) < 2:
result.errors.append(f"close_together: 参数 'devices' 至少需要 2 个设备,当前 {len(devices)}")
return
weight = _final_weight(
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
_priority_key(priority),
)
generated: list[dict] = []
for dev_a, dev_b in itertools.combinations(devices, 2):
c = Constraint(
type="soft",
rule_name="minimize_distance",
params={"device_a": dev_a, "device_b": dev_b},
weight=weight,
)
result.constraints.append(c)
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": generated,
"explanation": f"设备组 {devices} 应尽量靠近(优先级: {priority}",
})
def _handle_far_apart(intent: Intent, result: InterpretResult) -> None:
"""far_apart设备组内两两最大化距离。"""
devices: list[str] = intent.params.get("devices", [])
priority: str = intent.params.get("priority", "medium")
if len(devices) < 2:
result.errors.append(f"far_apart: 参数 'devices' 至少需要 2 个设备,当前 {len(devices)}")
return
weight = _final_weight(
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
_priority_key(priority),
)
generated: list[dict] = []
for dev_a, dev_b in itertools.combinations(devices, 2):
c = Constraint(
type="soft",
rule_name="maximize_distance",
params={"device_a": dev_a, "device_b": dev_b},
weight=weight,
)
result.constraints.append(c)
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": generated,
"explanation": f"设备组 {devices} 应尽量分散(优先级: {priority}",
})
def _handle_max_distance(intent: Intent, result: InterpretResult) -> None:
"""max_distance两设备间距不超过指定值。"""
device_a = intent.params.get("device_a")
device_b = intent.params.get("device_b")
distance = intent.params.get("distance")
if device_a is None or device_b is None or distance is None:
result.errors.append(
f"max_distance: 缺少必要参数,需要 'device_a''device_b''distance'"
f"当前: device_a={device_a}, device_b={device_b}, distance={distance}"
)
return
c = Constraint(
type="hard",
rule_name="distance_less_than",
params={"device_a": device_a, "device_b": device_b, "distance": distance},
weight=_final_weight(1.0, "normal"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": f"设备 '{device_a}''{device_b}' 之间的距离不得超过 {distance}",
})
def _handle_min_distance(intent: Intent, result: InterpretResult) -> None:
"""min_distance两设备间距不小于指定值。"""
device_a = intent.params.get("device_a")
device_b = intent.params.get("device_b")
distance = intent.params.get("distance")
if device_a is None or device_b is None or distance is None:
result.errors.append(
f"min_distance: 缺少必要参数,需要 'device_a''device_b''distance'"
f"当前: device_a={device_a}, device_b={device_b}, distance={distance}"
)
return
c = Constraint(
type="hard",
rule_name="distance_greater_than",
params={"device_a": device_a, "device_b": device_b, "distance": distance},
weight=_final_weight(1.0, "normal"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": f"设备 '{device_a}''{device_b}' 之间的距离不得小于 {distance}",
})
def _handle_min_spacing(intent: Intent, result: InterpretResult) -> None:
"""min_spacing所有设备之间的最小间隙。"""
min_gap: float = intent.params.get("min_gap", 0.3)
c = Constraint(
type="hard",
rule_name="min_spacing",
params={"min_gap": min_gap},
weight=_final_weight(1.0, "high"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": f"所有设备之间至少保持 {min_gap} 米的间隙",
})
def _handle_face_outward(intent: Intent, result: InterpretResult) -> None:
"""face_outward设备朝向偏好为向外。"""
c = Constraint(
type="soft",
rule_name="prefer_orientation_mode",
params={"mode": "outward"},
weight=_final_weight(1.0, "low"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": "设备开口偏好朝向实验室外侧",
})
def _handle_face_inward(intent: Intent, result: InterpretResult) -> None:
"""face_inward设备朝向偏好为向内。"""
c = Constraint(
type="soft",
rule_name="prefer_orientation_mode",
params={"mode": "inward"},
weight=_final_weight(1.0, "low"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": "设备开口偏好朝向实验室内侧",
})
def _handle_align_cardinal(intent: Intent, result: InterpretResult) -> None:
"""align_cardinal设备偏好对齐到主轴方向。"""
c = Constraint(
type="soft",
rule_name="prefer_aligned",
params={},
weight=_final_weight(1.0, "low"),
)
result.constraints.append(c)
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": [{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}],
"explanation": "设备偏好与实验室主轴对齐0°/90°/180°/270°",
})
def _handle_keep_adjacent(intent: Intent, result: InterpretResult) -> None:
"""keep_adjacent两个设备保持相邻同 close_together 逻辑,支持 priority 映射)。"""
devices: list[str] = intent.params.get("devices", [])
priority: str = intent.params.get("priority", "medium")
if len(devices) < 2:
result.errors.append(f"keep_adjacent: 参数 'devices' 至少需要 2 个设备,当前 {len(devices)}")
return
weight = _final_weight(
_PRIORITY_WEIGHTS.get(priority, _DEFAULT_WEIGHT),
_priority_key(priority),
)
generated: list[dict] = []
for dev_a, dev_b in itertools.combinations(devices, 2):
c = Constraint(
type="soft",
rule_name="minimize_distance",
params={"device_a": dev_a, "device_b": dev_b},
weight=weight,
)
result.constraints.append(c)
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": generated,
"explanation": f"设备组 {devices} 应保持相邻(优先级: {priority}",
})
def _handle_workflow_hint(intent: Intent, result: InterpretResult) -> None:
"""workflow_hint工作流顺序暗示相邻步骤设备靠近。"""
workflow: str = intent.params.get("workflow", "")
devices: list[str] = intent.params.get("devices", [])
if len(devices) < 2:
result.errors.append(
f"workflow_hint: 参数 'devices' 至少需要 2 个设备,当前 {len(devices)}"
)
return
generated: list[dict] = []
for dev_a, dev_b in zip(devices[:-1], devices[1:]):
c = Constraint(
type="soft",
rule_name="minimize_distance",
params={"device_a": dev_a, "device_b": dev_b},
weight=_final_weight(1.0, "normal"),
)
result.constraints.append(c)
generated.append({"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight})
result.workflow_edges.append([dev_a, dev_b])
result.translations.append({
"source_intent": intent.intent,
"source_description": intent.description,
"source_params": intent.params,
"generated_constraints": generated,
"explanation": f"工作流 '{workflow}' 中相邻步骤设备应靠近",
"confidence": "low",
})
# 意图处理器分发表
_HANDLERS: dict[str, Callable[[Intent, InterpretResult], None]] = {
"reachable_by": _handle_reachable_by,
"close_together": _handle_close_together,
"far_apart": _handle_far_apart,
"max_distance": _handle_max_distance,
"min_distance": _handle_min_distance,
"min_spacing": _handle_min_spacing,
"face_outward": _handle_face_outward,
"face_inward": _handle_face_inward,
"align_cardinal": _handle_align_cardinal,
"keep_adjacent": _handle_keep_adjacent,
"workflow_hint": _handle_workflow_hint,
}
def interpret_intents(intents: list[Intent]) -> InterpretResult:
"""将意图列表翻译为约束列表。
Args:
intents: 语义化意图列表(通常由 LLM 生成)
Returns:
InterpretResult包含约束、翻译记录、错误信息和工作流边
"""
result = InterpretResult()
for intent in intents:
handler = _HANDLERS.get(intent.intent)
if handler is None:
result.errors.append(f"未知意图类型: '{intent.intent}',跳过处理")
continue
handler(intent, result)
return result

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"""Protocol 接口定义,隔离 ROS 依赖。
开发阶段使用 mock_checkers.py 中的 Mock 实现,
集成阶段替换为 ros_checkers.py 中的 MoveIt2 / IKFast 实现。
"""
from __future__ import annotations
from typing import Protocol
class CollisionChecker(Protocol):
"""碰撞检测接口。"""
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
"""返回碰撞设备对列表。
Args:
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
Returns:
[("device_a", "device_b"), ...] 存在碰撞的设备对
"""
...
class ReachabilityChecker(Protocol):
"""可达性检测接口。"""
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
"""判断机械臂在给定位姿下能否到达目标点。
Args:
arm_id: 机械臂设备 ID
arm_pose: {"x": float, "y": float, "theta": float}
target: {"x": float, "y": float, "z": float}
Returns:
True 如果可达
"""
...

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"""解析实验室平面图 JSON。
简单格式:
{
"width": 6.0,
"depth": 4.0,
"obstacles": [
{"x": 2.0, "y": 0.0, "width": 0.1, "depth": 1.0}
]
}
"""
from __future__ import annotations
import json
from pathlib import Path
from .models import Lab, Obstacle
def parse_lab(data: dict) -> Lab:
"""从字典解析实验室平面图。"""
obstacles = []
for obs in data.get("obstacles", []):
obstacles.append(
Obstacle(
x=float(obs["x"]),
y=float(obs["y"]),
width=float(obs["width"]),
depth=float(obs["depth"]),
)
)
return Lab(
width=float(data["width"]),
depth=float(data["depth"]),
obstacles=obstacles,
)
def load_lab_from_file(path: str | Path) -> Lab:
"""从 JSON 文件加载实验室平面图。"""
with open(path) as f:
data = json.load(f)
return parse_lab(data)
def create_simple_lab(width: float, depth: float) -> Lab:
"""创建一个无障碍物的简单矩形实验室。"""
return Lab(width=width, depth=depth)

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# Demo Agent — Lab Layout Orchestrator
You are a lab layout agent for a recorded demo. Your job is to take a natural language lab request, translate it into optimizer constraints, run the optimization, and push results to the 3D frontend — all while outputting only concise, readable status lines.
## CRITICAL OUTPUT RULES
- Output ONLY short status lines. No markdown fences. No raw JSON. No explanations.
- Every HTTP call uses `curl -s` (silent). Never show curl output to the user.
- Parse responses internally. Extract only the fields needed for your status lines.
- Server base URL: `http://localhost:8000`
## Pipeline
Execute these steps in order. Print the status line shown after each step.
### Step 1 — Retrieve devices
Run:
```
curl -s http://localhost:8000/devices
```
Filter to `is_standalone: true` entries. Count them. Build an id→name lookup.
Print:
```
retrieving devices... N standalone devices found
```
Then print an id mapping table showing the user-friendly name → device_id for devices relevant to the user's request:
```
id mapping:
plate hotel → thermo_orbitor_rs2_hotel
robot arm → arm_slider
liquid handler → opentrons_liquid_handler
plate sealer → agilent_plateloc
pcr machine → inheco_odtc_96xl
```
Only include devices that are relevant to the user's request, not the full catalog.
### Step 2 — Translate intent to constraints
Using the rules in `layout_intent_translator.md` (which you have already read), translate the user's natural language request into an intents JSON structure.
Do NOT print the JSON. Instead, print a human-readable constraint summary:
```
translating intent to constraints...
constraints:
hard: arm_slider must reach 4 devices
hard: min spacing 0.05m between all devices
soft: workflow order hotel → liquid handler → sealer → pcr
soft: all devices close together (high priority)
soft: align to cardinal directions
```
### Step 3 — Interpret intents
Send the intents JSON to the interpret endpoint:
```
curl -s -X POST http://localhost:8000/interpret \
-H "Content-Type: application/json" \
-d '{ "intents": [...] }'
```
Capture the `constraints` and `workflow_edges` arrays from the response. Do NOT print anything for this step — it's a silent validation.
If `errors` is non-empty, print:
```
warning: N intents failed to translate
```
### Step 3.5 — Read lab dimensions
```
curl -s http://localhost:8000/scene/lab
```
Returns `{"width": W, "depth": D}`. Use these values for the optimize request. Do NOT print anything for this step.
### Step 4 — Optimize layout
Build the optimize request using:
- `devices`: the relevant devices from Step 1 (id, name, device_type)
- `lab`: the `{"width": W, "depth": D}` from Step 3.5
- `constraints`: from Step 3 interpret response
- `workflow_edges`: from Step 3 interpret response
- `seeder`: `"compact_outward"` (default)
- `seeder_overrides`: generally not needed. Cardinal alignment is handled by the `align_cardinal` intent (generates `prefer_aligned` constraint). Do NOT use `align_weight` in seeder_overrides — it is deprecated.
- `snap_cardinal`: `false` (default). Set `true` only if user explicitly requests snapping to 0/90/180/270.
- `run_de`: `true`
- `maxiter`: `200`
- `seed`: `42`
Run:
```
curl -s -X POST http://localhost:8000/optimize \
-H "Content-Type: application/json" \
-d '{ ... }'
```
Print:
```
optimizing layout (DE, 200 iterations)...
optimization complete — cost: X.XX, success: true/false
```
If `success` is false, print:
```
error: optimization failed (cost: inf) — constraints may conflict
```
And stop.
### Step 5 — Apply placements
Take the `placements` array from the optimize response and POST them. Do NOT add a `location` field — the backend schema only accepts `device_id`, `uuid`, `position`, and `rotation`. Extra fields will cause validation errors.
```
curl -s -X POST http://localhost:8000/scene/placements \
-H "Content-Type: application/json" \
-d '{ "placements": [
{
"device_id": "...",
"uuid": "...",
"position": {"x": ..., "y": ..., "z": ...},
"rotation": {"x": ..., "y": ..., "z": ...}
}
] }'
```
**Important — version-based polling:** The frontend polls `GET /scene/placements` every 1 second and uses a version number to detect changes. On the **first poll**, it captures the current version as a baseline and does **not** apply placements. It only renders placements when the version **increases beyond** that baseline. This means if you POST placements before the frontend has polled once, the frontend will silently skip that update.
**Solution:** After the initial POST, send the **same request a second time** to bump the version. This guarantees the frontend sees a version increase after its baseline poll and applies the placements.
Print:
```
applying placements to scene...
layout applied — N devices positioned
```
## Follow-up Requests
If the user gives a follow-up request (e.g., "now move the sealer farther from the thermal cycler"):
1. Print a `---` separator
2. Keep the same device list (no need to re-fetch)
3. Translate the NEW request into intents — these REPLACE the previous constraints entirely
4. Run Steps 35 again with the new constraints
5. Same output format
## Error Handling
- Server unreachable: `error: server unreachable at localhost:8000`
- Optimize fails: `error: optimization failed (cost: inf) — constraints may conflict`
- After any error, stop and wait for user input.
## Device Name Resolution
You have `layout_intent_translator.md` loaded as context. Use its device name resolution rules to match user's informal names (e.g., "PCR machine", "the arm", "liquid handler") to exact device IDs from the catalog retrieved in Step 1.
## Example Full Output
For input: "Set up a PCR workflow — hotel, liquid handler, sealer, thermal cycler. The arm handles all transfers. Keep it compact."
```
retrieving devices... 47 standalone devices found
id mapping:
plate hotel → thermo_orbitor_rs2_hotel
robot arm → arm_slider
liquid handler → opentrons_liquid_handler
plate sealer → agilent_plateloc
pcr machine → inheco_odtc_96xl
translating intent to constraints...
constraints:
hard: arm_slider must reach 4 devices
soft: workflow order hotel → liquid handler → sealer → pcr
soft: all devices close together (high priority)
soft: align to cardinal directions
optimizing layout (DE, 200 iterations)...
optimization complete — cost: 0.00, success: true
applying placements to scene...
layout applied — 5 devices positioned
```

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# Layout Intent Translator — LLM Skill
You are a lab layout intent translator. Your job is to convert natural language descriptions of lab layout requirements into structured JSON intents that the layout optimizer can understand.
## Your Role
Users describe their lab needs in natural language. You must:
1. Identify devices by their IDs from the provided device list
2. Infer spatial relationships, workflow order, and physical constraints
3. Output structured intents (JSON) that map to the optimizer's intent schema
4. Provide clear `description` fields so users can verify the translation
## Output Format
You MUST output a JSON object with an `intents` array. Each intent has:
```json
{
"intents": [
{
"intent": "<intent_type>",
"params": { ... },
"description": "Human-readable explanation of what this intent means"
}
]
}
```
## Available Intent Types
### `reachable_by` — Robot arm must reach devices
```json
{
"intent": "reachable_by",
"params": {
"arm": "arm_device_id",
"targets": ["device_a", "device_b"]
},
"description": "Robot arm must be able to reach device A and device B"
}
```
**When to use:** Any time a robot arm transfers items between devices, all those devices must be reachable.
### `close_together` — Devices should be near each other
```json
{
"intent": "close_together",
"params": {
"devices": ["device_a", "device_b", "device_c"],
"priority": "high"
},
"description": "These devices are used frequently together and should be close"
}
```
**Priority:** `"low"` (nice-to-have), `"medium"` (default), `"high"` (critical for workflow speed)
Priority is only part of the intent input. The interpreter automatically bakes it into the emitted constraint `weight`; there is no separate constraint-level `priority` field in `/interpret` output or `/optimize` input.
### `far_apart` — Devices should be separated
```json
{
"intent": "far_apart",
"params": {
"devices": ["heat_source", "reagent_storage"],
"priority": "medium"
}
}
```
**When to use:** Thermal interference, contamination risk, safety separation.
### `keep_adjacent` — Devices should stay adjacent
```json
{
"intent": "keep_adjacent",
"params": {
"devices": ["device_a", "device_b"],
"priority": "high"
}
}
```
**When to use:** User explicitly asks for a pair or group to stay side-by-side / adjacent. This currently maps to the same optimizer behavior as `close_together`, but is semantically more precise.
### `max_distance` — Hard limit on maximum distance
```json
{
"intent": "max_distance",
"params": {
"device_a": "device_a_id",
"device_b": "device_b_id",
"distance": 1.5
}
}
```
**When to use:** Physical constraints like tube length, cable reach, arm range.
### `min_distance` — Hard limit on minimum distance
```json
{
"intent": "min_distance",
"params": {
"device_a": "device_a_id",
"device_b": "device_b_id",
"distance": 0.5
}
}
```
**When to use:** Safety clearance, thermal isolation, vibration separation.
### `min_spacing` — Global minimum gap between all devices
```json
{
"intent": "min_spacing",
"params": { "min_gap": 0.3 }
}
```
**When to use:** General accessibility, maintenance clearance.
### `workflow_hint` — Workflow step ordering
```json
{
"intent": "workflow_hint",
"params": {
"workflow": "pcr",
"devices": ["liquid_handler", "thermal_cycler", "plate_sealer", "storage"]
}
}
```
**When to use:** When user describes a sequential process. Devices are listed in workflow order. Consecutive devices will be placed near each other.
### `face_outward` / `face_inward` / `align_cardinal`
```json
{"intent": "face_outward"}
{"intent": "face_inward"}
{"intent": "align_cardinal"}
```
**When to use:** User mentions accessibility from outside, central robot, or neat alignment.
## Device Name Resolution
You will receive the current scene's device list as context. This is the **only** source of valid device IDs. Users will refer to devices using informal names — you must match them to exact IDs from this list.
### Input Context Format
Before each translation request, you receive the scene's device list:
```
Devices in scene:
- thermo_orbitor_rs2_hotel: Thermo Orbitor RS2 Hotel (type: static, bbox: 0.68×0.52m)
- arm_slider: Arm Slider (type: articulation, bbox: 1.20×0.30m)
- opentrons_liquid_handler: Opentrons Liquid Handler (type: static, bbox: 0.65×0.60m)
- agilent_plateloc: Agilent PlateLoc (type: static, bbox: 0.35×0.40m)
- inheco_odtc_96xl: Inheco ODTC 96XL (type: static, bbox: 0.30×0.35m)
```
### Matching Rules
1. **Exact match first**: If user says "arm_slider", match directly
2. **Name/brand match**: "opentrons" → `opentrons_liquid_handler`, "plateloc" → `agilent_plateloc`
3. **Function match**: "PCR machine" / "thermal cycler" → `inheco_odtc_96xl`; "liquid handler" / "pipetting robot" → `opentrons_liquid_handler`; "plate hotel" / "storage" → `thermo_orbitor_rs2_hotel`; "plate sealer" → `agilent_plateloc`
4. **Type match**: "robot arm" / "the arm" → look for `device_type: articulation`
5. **Ambiguous**: If multiple devices could match, list candidates in the `description` field and pick the most likely one. If truly ambiguous, return an error intent asking the user to clarify.
### Duplicate Device Convention
When the same catalog device appears multiple times in the scene:
- first instance keeps the bare catalog ID, e.g. `plate_reader`
- second and later instances use `#N`, e.g. `plate_reader#2`, `plate_reader#3`
- a bare ID in an intent fans out to all instances
- a suffixed ID applies only to that specific instance
Examples:
- `{"devices": ["plate_reader", "storage_hotel"]}` applies to every `plate_reader` instance
- `{"devices": ["plate_reader#2", "storage_hotel"]}` applies only to the second instance
### Example Resolution
User says: "the robot should reach the PCR machine and the liquid handler"
Scene devices: `arm_slider` (articulation), `inheco_odtc_96xl`, `opentrons_liquid_handler`, ...
Resolution:
- "the robot" → `arm_slider` (only articulation-type device)
- "PCR machine" → `inheco_odtc_96xl` (thermal cycler = PCR)
- "liquid handler" → `opentrons_liquid_handler`
## Translation Rules
### 1. Robot Arm Inference
If any robot arm is in the device list and the workflow involves plate/sample transfer between devices, ALL devices that exchange plates/samples with each other via the arm must be in `reachable_by.targets`.
### 2. Workflow Order
When a user describes a process (e.g., "prepare samples, then run PCR, then seal"), extract the device order and create a `workflow_hint`. The device order follows the sample processing path.
### 3. Implicit Constraints
- If devices frequently exchange items → `close_together` (high priority)
- If user explicitly says "keep these adjacent", "side by side", or "next to each other" → `keep_adjacent`
- If a robot arm is mentioned "in between" → `reachable_by` for all involved devices
- If user says "short transit" or "fast transfer" → `close_together` with `"priority": "high"`
- If user says "keep X away from Y" → `far_apart` or `min_distance`
### 4. Don't Over-Constrain
- Only add constraints the user's description implies
- When unsure about priority, use `"medium"`
- For workflow_hint, confidence is inherently `"low"` — the optimizer notes this
## Example: PCR Workflow
**User input:**
> "Take plate from hotel, prepare sample in opentrons, seal plate then pcr cycle, arm_slider handles all transfers"
**Device list provided:**
- `thermo_orbitor_rs2_hotel` (plate hotel/storage)
- `arm_slider` (robot arm on linear rail)
- `opentrons_liquid_handler` (liquid handling/pipetting)
- `agilent_plateloc` (plate sealer)
- `inheco_odtc_96xl` (thermal cycler for PCR)
**Your output:**
```json
{
"intents": [
{
"intent": "reachable_by",
"params": {
"arm": "arm_slider",
"targets": [
"thermo_orbitor_rs2_hotel",
"opentrons_liquid_handler",
"agilent_plateloc",
"inheco_odtc_96xl"
]
},
"description": "arm_slider must reach all devices since it handles all plate transfers"
},
{
"intent": "workflow_hint",
"params": {
"workflow": "pcr",
"devices": [
"thermo_orbitor_rs2_hotel",
"opentrons_liquid_handler",
"agilent_plateloc",
"inheco_odtc_96xl"
]
},
"description": "PCR workflow order: hotel → liquid handler → plate sealer → thermal cycler"
},
{
"intent": "close_together",
"params": {
"devices": ["opentrons_liquid_handler", "agilent_plateloc"],
"priority": "high"
},
"description": "Sealing happens immediately after sample prep — minimize transit time"
}
]
}
```
**Reasoning:**
- The arm handles ALL transfers → all 4 devices in reachable_by targets
- User described a clear sequence → workflow_hint in that order
- "seal plate then pcr" implies sealing is immediately after prep → close_together for the pair with high priority
## Example: Simple Proximity Request
**User input:**
> "Keep the thermal cycler close to the plate sealer, at most 1 meter apart"
**Your output:**
```json
{
"intents": [
{
"intent": "max_distance",
"params": {
"device_a": "inheco_odtc_96xl",
"device_b": "agilent_plateloc",
"distance": 1.0
},
"description": "Thermal cycler and plate sealer must be within 1 meter"
}
]
}
```
## API Integration
### Discovery
Call `GET /interpret/schema` to get the current list of available intent types and their parameter specifications. Always check this before translating, as new intent types may be added.
### Translation
Send your output to `POST /interpret`:
```
POST /interpret
Content-Type: application/json
{
"intents": [ ... your translated intents ... ]
}
```
### Response
The endpoint returns:
- `constraints` — ready to pass to `/optimize`
- `translations` — human-readable mapping of each intent to generated constraints
- `workflow_edges` — extracted workflow connections
- `errors` — any intents that failed to translate
### Optimization
After user confirms the translation, pass `constraints` and `workflow_edges` to `POST /optimize` along with the device list and lab dimensions.

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"""Mock 检测器:无 ROS 依赖的简化碰撞与可达性检测。
碰撞检测基于 OBB SATO(n²) 两两比较)。
可达性检测基于最大臂展半径的欧几里得距离判断。
集成阶段由 ros_checkers.py 中的 MoveItCollisionChecker / IKFastReachabilityChecker 替代。
"""
from __future__ import annotations
import math
from .obb import obb_corners, obb_overlap
class MockCollisionChecker:
"""基于 OBB SAT 的碰撞检测。
输入格式与 CollisionChecker Protocol 一致:
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
"""
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
"""返回所有碰撞的设备对。"""
collisions: list[tuple[str, str]] = []
n = len(placements)
for i in range(n):
for j in range(i + 1, n):
a, b = placements[i], placements[j]
corners_a = obb_corners(
a["pos"][0], a["pos"][1],
a["bbox"][0], a["bbox"][1],
a["pos"][2] if len(a["pos"]) > 2 else 0.0,
)
corners_b = obb_corners(
b["pos"][0], b["pos"][1],
b["bbox"][0], b["bbox"][1],
b["pos"][2] if len(b["pos"]) > 2 else 0.0,
)
if obb_overlap(corners_a, corners_b):
collisions.append((a["id"], b["id"]))
return collisions
def check_bounds(
self, placements: list[dict], lab_width: float, lab_depth: float
) -> list[str]:
"""返回超出实验室边界的设备 ID 列表。"""
out_of_bounds: list[str] = []
for p in placements:
hw, hd = self._rotated_half_extents(p)
x, y = p["pos"][:2]
if x - hw < 0 or x + hw > lab_width or y - hd < 0 or y + hd > lab_depth:
out_of_bounds.append(p["id"])
return out_of_bounds
@staticmethod
def _rotated_half_extents(p: dict) -> tuple[float, float]:
"""计算旋转后 AABB 的半宽和半深。"""
w, d = p["bbox"]
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
cos_t = abs(math.cos(theta))
sin_t = abs(math.sin(theta))
half_w = (w * cos_t + d * sin_t) / 2
half_d = (w * sin_t + d * cos_t) / 2
return half_w, half_d
class MockReachabilityChecker:
"""基于最大臂展半径的简化可达性判断。
内置常见 Elite CS 系列机械臂的臂展参数。
自定义臂展可通过构造参数传入。
"""
# 默认臂展参数(单位:米)
DEFAULT_ARM_REACH: dict[str, float] = {
"elite_cs63": 0.624,
"elite_cs66": 0.914,
"elite_cs612": 1.304,
"elite_cs620": 1.800,
"arm_slider": 0.3, # 线性导轨臂1.07 body 2.14m × 0.35mreach ≈ half length
}
# 未知型号回退臂展realistic default for lab-scale arms
DEFAULT_FALLBACK_REACH: float = 0.4
def __init__(self, arm_reach: dict[str, float] | None = None):
self.arm_reach = {**self.DEFAULT_ARM_REACH, **(arm_reach or {})}
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
"""判断目标点是否在机械臂最大臂展半径内。
Uses OBB edge-to-edge distance when available (passed as _obb_dist),
otherwise falls back to center-to-center Euclidean distance.
Args:
arm_id: 机械臂型号 ID用于查臂展
arm_pose: {"x": float, "y": float, "theta": float}
target: {"x": float, "y": float, "z": float, "_obb_dist": float (optional)}
Returns:
True 如果目标在臂展半径内
"""
max_reach = self.arm_reach.get(arm_id, self.DEFAULT_FALLBACK_REACH)
if "_obb_dist" in target:
return target["_obb_dist"] <= max_reach
dx = target["x"] - arm_pose["x"]
dy = target["y"] - arm_pose["y"]
dist_sq = dx**2 + dy**2
return dist_sq <= max_reach**2

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"""数据模型定义Device, Lab, Placement, Constraint 及 API 请求/响应。"""
from __future__ import annotations
import math
from dataclasses import dataclass, field
from typing import Literal
@dataclass
class Opening:
"""设备的访问开口(用于方向约束)。"""
# 设备局部坐标系中的方向单位向量,如 (0, -1) = 正前方
direction: tuple[float, float] = (0.0, -1.0)
label: str = ""
@dataclass
class Device:
"""设备描述。"""
id: str
name: str
# 碰撞包围盒 (width along X, depth along Y),单位:米
bbox: tuple[float, float] = (0.6, 0.4)
device_type: Literal["static", "articulation", "rigid"] = "static"
# 以下为可选扩展字段(向后兼容)
height: float = 0.4
origin_offset: tuple[float, float] = (0.0, 0.0)
openings: list[Opening] = field(default_factory=list)
source: Literal["registry", "assets", "manual"] = "manual"
model_path: str = ""
model_type: str = ""
thumbnail_url: str = ""
uuid: str = ""
@dataclass
class Obstacle:
"""实验室内固定障碍物(矩形)。"""
x: float
y: float
width: float
depth: float
@dataclass
class Lab:
"""实验室平面图。"""
width: float # X 方向,单位:米
depth: float # Y 方向,单位:米
obstacles: list[Obstacle] = field(default_factory=list)
@dataclass
class Placement:
"""单个设备的布局位姿。"""
device_id: str
x: float
y: float
theta: float # 旋转角,弧度
uuid: str = "" # 前端分配的唯一标识,透传不生成
def rotated_bbox(self, device: Device) -> tuple[float, float]:
"""返回旋转后的 AABB 尺寸 (half_w, half_h)。"""
w, d = device.bbox
cos_t = abs(math.cos(self.theta))
sin_t = abs(math.sin(self.theta))
half_w = (w * cos_t + d * sin_t) / 2
half_h = (w * sin_t + d * cos_t) / 2
return half_w, half_h
@dataclass
class Constraint:
"""约束规则。"""
type: Literal["hard", "soft"]
rule_name: str
# 规则参数,含义因 rule_name 而异
params: dict = field(default_factory=dict)
# 仅 soft 约束使用
weight: float = 1.0
@dataclass
class Intent:
"""LLM 可生成的语义化意图,由 interpreter 翻译为 Constraint 列表。"""
intent: str # 意图类型,如 "reachable_by", "close_together"
params: dict = field(default_factory=dict)
description: str = "" # 可选的自然语言描述(用于审计/调试)

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"""OBB (Oriented Bounding Box) geometry: corners, overlap (SAT), minimum distance."""
from __future__ import annotations
import math
def obb_corners(
cx: float, cy: float, w: float, h: float, theta: float
) -> list[tuple[float, float]]:
"""Return 4 corners of the OBB as (x, y) tuples.
Args:
cx, cy: center position
w, h: full width and height (not half-extents)
theta: rotation angle in radians
"""
hw, hh = w / 2, h / 2
cos_t, sin_t = math.cos(theta), math.sin(theta)
dx_w, dy_w = hw * cos_t, hw * sin_t # half-width vector
dx_h, dy_h = -hh * sin_t, hh * cos_t # half-height vector
return [
(cx + dx_w + dx_h, cy + dy_w + dy_h),
(cx - dx_w + dx_h, cy - dy_w + dy_h),
(cx - dx_w - dx_h, cy - dy_w - dy_h),
(cx + dx_w - dx_h, cy + dy_w - dy_h),
]
def _get_axes(corners: list[tuple[float, float]]) -> list[tuple[float, float]]:
"""Return 2 edge-normal axes for a rectangle (4 corners)."""
axes = []
for i in range(2): # Only need 2 axes for a rectangle
edge_x = corners[i + 1][0] - corners[i][0]
edge_y = corners[i + 1][1] - corners[i][1]
length = math.sqrt(edge_x**2 + edge_y**2)
if length > 0:
axes.append((-edge_y / length, edge_x / length))
return axes
def _project(corners: list[tuple[float, float]], axis: tuple[float, float]) -> tuple[float, float]:
"""Project all corners onto axis, return (min, max) scalar projections."""
dots = [c[0] * axis[0] + c[1] * axis[1] for c in corners]
return min(dots), max(dots)
def obb_overlap(corners_a: list[tuple[float, float]], corners_b: list[tuple[float, float]]) -> bool:
"""Return True if two OBBs overlap using Separating Axis Theorem.
Uses strict inequality (touching edges = no overlap).
"""
for axis in _get_axes(corners_a) + _get_axes(corners_b):
min_a, max_a = _project(corners_a, axis)
min_b, max_b = _project(corners_b, axis)
if max_a <= min_b or max_b <= min_a:
return False
return True
def _point_to_segment_dist_sq(
px: float, py: float,
ax: float, ay: float,
bx: float, by: float,
) -> float:
"""Squared distance from point (px,py) to line segment (ax,ay)-(bx,by)."""
dx, dy = bx - ax, by - ay
len_sq = dx * dx + dy * dy
if len_sq == 0:
return (px - ax) ** 2 + (py - ay) ** 2
t = max(0.0, min(1.0, ((px - ax) * dx + (py - ay) * dy) / len_sq))
proj_x, proj_y = ax + t * dx, ay + t * dy
return (px - proj_x) ** 2 + (py - proj_y) ** 2
def obb_penetration_depth(
corners_a: list[tuple[float, float]],
corners_b: list[tuple[float, float]],
) -> float:
"""Minimum penetration depth between two OBBs (SAT-based).
Returns 0.0 if not overlapping. Otherwise returns the minimum overlap
along any separating axis — the smallest push needed to separate them.
"""
min_overlap = float("inf")
for axis in _get_axes(corners_a) + _get_axes(corners_b):
min_a, max_a = _project(corners_a, axis)
min_b, max_b = _project(corners_b, axis)
overlap = min(max_a - min_b, max_b - min_a)
if overlap <= 0:
return 0.0 # Separated on this axis
if overlap < min_overlap:
min_overlap = overlap
return min_overlap
def nearest_point_on_obb(
px: float, py: float,
corners: list[tuple[float, float]],
) -> tuple[float, float]:
"""Return the nearest point on an OBB's boundary to point (px, py).
If the point is inside the OBB, returns the nearest edge point.
"""
best_x, best_y = corners[0]
best_dist_sq = float("inf")
n = len(corners)
for i in range(n):
ax, ay = corners[i]
bx, by = corners[(i + 1) % n]
dx, dy = bx - ax, by - ay
len_sq = dx * dx + dy * dy
if len_sq == 0:
proj_x, proj_y = ax, ay
else:
t = max(0.0, min(1.0, ((px - ax) * dx + (py - ay) * dy) / len_sq))
proj_x, proj_y = ax + t * dx, ay + t * dy
d_sq = (px - proj_x) ** 2 + (py - proj_y) ** 2
if d_sq < best_dist_sq:
best_dist_sq = d_sq
best_x, best_y = proj_x, proj_y
return best_x, best_y
def segment_intersects_obb(
p1: tuple[float, float],
p2: tuple[float, float],
corners: list[tuple[float, float]],
) -> bool:
"""Return True if line segment p1-p2 intersects the OBB (convex polygon).
Uses separating axis theorem on the Minkowski difference:
test segment against each edge of the polygon + segment normal.
"""
# Quick: test each edge of the OBB against the segment
n = len(corners)
for i in range(n):
ax, ay = corners[i]
bx, by = corners[(i + 1) % n]
if _segments_intersect(p1[0], p1[1], p2[0], p2[1], ax, ay, bx, by):
return True
# Also check if segment is fully inside the OBB
if _point_in_convex(p1, corners) or _point_in_convex(p2, corners):
return True
return False
def _segments_intersect(
ax: float, ay: float, bx: float, by: float,
cx: float, cy: float, dx: float, dy: float,
) -> bool:
"""Return True if segment AB intersects segment CD (proper or endpoint)."""
def cross(ox: float, oy: float, px: float, py: float, qx: float, qy: float) -> float:
return (px - ox) * (qy - oy) - (py - oy) * (qx - ox)
d1 = cross(cx, cy, dx, dy, ax, ay)
d2 = cross(cx, cy, dx, dy, bx, by)
d3 = cross(ax, ay, bx, by, cx, cy)
d4 = cross(ax, ay, bx, by, dx, dy)
if ((d1 > 0 and d2 < 0) or (d1 < 0 and d2 > 0)) and \
((d3 > 0 and d4 < 0) or (d3 < 0 and d4 > 0)):
return True
# Collinear cases — skip for simplicity (near-zero probability in DE)
return False
def _point_in_convex(
p: tuple[float, float], corners: list[tuple[float, float]]
) -> bool:
"""Return True if point is inside a convex polygon (corners in order)."""
n = len(corners)
sign = None
for i in range(n):
ax, ay = corners[i]
bx, by = corners[(i + 1) % n]
cross = (bx - ax) * (p[1] - ay) - (by - ay) * (p[0] - ax)
if abs(cross) < 1e-12:
continue
s = cross > 0
if sign is None:
sign = s
elif s != sign:
return False
return True
def segment_obb_intersection_length(
p1: tuple[float, float],
p2: tuple[float, float],
corners: list[tuple[float, float]],
) -> float:
"""线段 p1-p2 与 OBB凸多边形的交集长度。
Cyrus-Beck 线段裁剪算法。corners 假定为 CCW 顺序obb_corners 生成)。
无交集返回 0.0。
"""
dx = p2[0] - p1[0]
dy = p2[1] - p1[1]
seg_len_sq = dx * dx + dy * dy
if seg_len_sq < 1e-24:
return 0.0
t_enter = 0.0
t_exit = 1.0
n = len(corners)
for i in range(n):
ax, ay = corners[i]
bx, by = corners[(i + 1) % n]
# CCW 多边形边的外法线: (ey, -ex), e = b - a
ex, ey = bx - ax, by - ay
nx, ny = ey, -ex
denom = nx * dx + ny * dy
numer = nx * (p1[0] - ax) + ny * (p1[1] - ay)
if abs(denom) < 1e-12:
if numer > 0:
return 0.0 # 在此边外侧且平行
continue
t = -numer / denom
if denom < 0:
t_enter = max(t_enter, t) # 进入
else:
t_exit = min(t_exit, t) # 退出
if t_enter > t_exit:
return 0.0
if t_enter >= t_exit:
return 0.0
return (t_exit - t_enter) * math.sqrt(seg_len_sq)
def obb_min_distance(
corners_a: list[tuple[float, float]],
corners_b: list[tuple[float, float]],
) -> float:
"""Minimum distance between two OBBs (convex polygons).
Returns 0.0 if overlapping or touching.
"""
if obb_overlap(corners_a, corners_b):
return 0.0
min_dist_sq = float("inf")
for poly, other in [(corners_a, corners_b), (corners_b, corners_a)]:
n = len(other)
for px, py in poly:
for i in range(n):
ax, ay = other[i]
bx, by = other[(i + 1) % n]
d_sq = _point_to_segment_dist_sq(px, py, ax, ay, bx, by)
if d_sq < min_dist_sq:
min_dist_sq = d_sq
return math.sqrt(min_dist_sq)

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"""初始布局生成Pencil MCP 接口 + 行列式回退。
策略:
1. 尝试调用 Pencil AI MCP 生成初始布局
2. 若 Pencil 不可用或失败,回退到行列式放置算法
行列式回退逻辑:
- 设备按面积从大到小排序
- 沿 X 轴逐个放置,行满(超出 lab.width则换行
- 设备间保留 margin 间距
- 所有设备 θ=0朝向不变
"""
from __future__ import annotations
import logging
from .models import Device, Lab, Placement
logger = logging.getLogger(__name__)
# 设备间最小间距(米)
DEFAULT_MARGIN = 0.3
def generate_initial_layout(
devices: list[Device],
lab: Lab,
margin: float = DEFAULT_MARGIN,
) -> list[Placement]:
"""生成初始布局方案。
优先尝试 Pencil MCP失败则回退到行列式放置。
Args:
devices: 待放置的设备列表
lab: 实验室平面图
margin: 设备间最小间距
Returns:
初始布局 Placement 列表
"""
# 尝试 Pencil MCP
pencil_result = _try_pencil(devices, lab)
if pencil_result is not None:
logger.info("Using Pencil AI generated layout")
return pencil_result
# 回退到行列式
logger.info("Pencil unavailable, using row-based fallback layout")
return generate_fallback(devices, lab, margin)
def _try_pencil(
devices: list[Device],
lab: Lab,
) -> list[Placement] | None:
"""尝试通过 Pencil AI MCP 生成布局。
当前 Pencil MCP 不可用,返回 None 触发回退。
未来集成时,此函数应:
1. 将设备 2D 投影 + 实验室平面图序列化为 Pencil 输入格式
2. 调用 mcp__pencil_* 工具
3. 解析返回的布局方案为 Placement 列表
预留接口参数:
- devices: 设备列表id, bbox
- lab: 实验室尺寸
"""
# TODO: 当 Pencil MCP 可用时实现
# 预期调用方式:
# pencil_input = {
# "floor_plan": {"width": lab.width, "depth": lab.depth},
# "items": [{"id": d.id, "width": d.bbox[0], "depth": d.bbox[1]} for d in devices],
# }
# result = mcp__pencil_layout(pencil_input)
# return [Placement(device_id=r["id"], x=r["x"], y=r["y"], theta=r["theta"]) for r in result]
return None
def generate_fallback(
devices: list[Device],
lab: Lab,
margin: float = DEFAULT_MARGIN,
) -> list[Placement]:
"""行列式回退布局:按面积从大到小排序,逐行放置。
放置规则:
- 设备中心坐标,从左上角开始
- 每行从 margin + half_width 开始
- 行满(下一个设备右边缘超出 lab.width - margin则换行
- 行高取该行最大设备深度
Args:
devices: 待放置的设备列表
lab: 实验室平面图
margin: 设备间最小间距
Returns:
Placement 列表。若实验室空间不足,剩余设备堆叠在右下角并记录警告。
"""
if not devices:
return []
# 按面积从大到小排序
sorted_devices = sorted(devices, key=lambda d: d.bbox[0] * d.bbox[1], reverse=True)
placements: list[Placement] = []
cursor_x = margin
cursor_y = margin
row_height = 0.0
for dev in sorted_devices:
w, d = dev.bbox
half_w = w / 2
half_d = d / 2
# 检查当前行是否放得下
if cursor_x + half_w + margin > lab.width and placements:
# 换行
cursor_x = margin
cursor_y += row_height + margin
row_height = 0.0
# 设备中心位置
cx = cursor_x + half_w
cy = cursor_y + half_d
# 检查是否超出实验室深度
if cy + half_d + margin > lab.depth:
logger.warning(
"Lab space insufficient for device '%s' (%s), "
"placing at overflow position",
dev.id,
dev.bbox,
)
placements.append(Placement(device_id=dev.id, x=cx, y=cy, theta=0.0))
# 更新游标
cursor_x = cx + half_w + margin
row_height = max(row_height, d)
return placements

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[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "layout-optimizer"
version = "0.1.0"
description = "AI laboratory layout optimizer for Uni-Lab Phase 3"
requires-python = ">=3.10"
dependencies = [
"scipy>=1.10",
"numpy>=1.24",
"fastapi>=0.100",
"uvicorn>=0.20",
"pydantic>=2.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0",
"httpx>=0.24",
]
[tool.setuptools.packages.find]
where = ["."]
include = ["layout_optimizer*"]
[tool.pytest.ini_options]
testpaths = ["tests"]

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"""ROS2/MoveIt2 碰撞检测与 IKFast 可达性检测适配器。
集成阶段替换 mock_checkers.py 中的 Mock 实现,
依赖 Uni-Lab-OS 的 moveit2.py 提供的 MoveIt2 Python 接口。
用法:
from .ros_checkers import MoveItCollisionChecker, IKFastReachabilityChecker
# 碰撞检测
checker = MoveItCollisionChecker(moveit2_instance)
collisions = checker.check(placements)
# 可达性检测(体素图 O(1) 查询 + 实时 IK 回退)
reachability = IKFastReachabilityChecker(moveit2_instance, voxel_dir="/path/to/voxels")
reachable = reachability.is_reachable("elite_cs66", arm_pose, target)
环境变量:
LAYOUT_CHECKER_MODE: "mock" | "moveit" — 选择检测器实现(默认 "mock"
LAYOUT_VOXEL_DIR: 预计算体素图目录路径(.npz 文件)
前置条件:
- ROS2 + MoveIt2 运行中
- moveit2.py 中的 MoveIt2 实例已初始化
- 命名规范:碰撞对象使用 {device_id}_ 前缀
"""
from __future__ import annotations
import logging
import math
import os
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
from .obb import obb_corners, obb_overlap
if TYPE_CHECKING:
pass
logger = logging.getLogger(__name__)
# ---------- 坐标变换辅助 ----------
def _yaw_to_quat(theta: float) -> tuple[float, float, float, float]:
"""将 2D 旋转角(绕 Z 轴弧度)转换为四元数 (x, y, z, w)。"""
return (0.0, 0.0, math.sin(theta / 2), math.cos(theta / 2))
def _transform_to_arm_frame(
arm_pose: dict, target: dict,
) -> tuple[float, float, float]:
"""将目标点从世界坐标系变换到机械臂基坐标系。
Args:
arm_pose: {"x": float, "y": float, "theta": float}
target: {"x": float, "y": float, "z": float}
Returns:
(local_x, local_y, local_z) 在臂基坐标系中的位置
"""
dx = target["x"] - arm_pose["x"]
dy = target["y"] - arm_pose["y"]
theta = arm_pose.get("theta", 0.0)
cos_t = math.cos(-theta)
sin_t = math.sin(-theta)
local_x = dx * cos_t - dy * sin_t
local_y = dx * sin_t + dy * cos_t
local_z = target.get("z", 0.0)
return (local_x, local_y, local_z)
# ---------- MoveItCollisionChecker ----------
class MoveItCollisionChecker:
"""通过 MoveIt2 PlanningScene 进行碰撞检测。
工作流程:
1. 将所有设备同步为 MoveIt2 碰撞盒({device_id}_ 前缀)
2. 使用 python-fcl 进行精确两两碰撞检测(若可用)
3. 若 FCL 不可用,回退到 OBB SAT 检测
同步到 MoveIt2 确保机器人运动规划也能感知设备布局。
"""
def __init__(
self,
moveit2: Any,
*,
default_height: float = 0.4,
sync_to_scene: bool = True,
):
"""
Args:
moveit2: Uni-Lab-OS moveit2.py 中的 MoveIt2 实例
default_height: 碰撞盒默认高度(米)
sync_to_scene: 是否同步碰撞对象到 MoveIt2 规划场景
"""
self._moveit2 = moveit2
self._default_height = default_height
self._sync_to_scene = sync_to_scene
self._fcl_available = self._check_fcl()
@staticmethod
def _check_fcl() -> bool:
"""检查 python-fcl 是否可用。"""
try:
import fcl # noqa: F401
return True
except ImportError:
return False
def check(self, placements: list[dict]) -> list[tuple[str, str]]:
"""返回碰撞设备对列表。
Args:
placements: [{"id": str, "bbox": (w, d), "pos": (x, y, θ)}, ...]
Returns:
[("device_a", "device_b"), ...] 存在碰撞的设备对
"""
# 同步到 MoveIt2 规划场景
if self._sync_to_scene:
self._sync_collision_objects(placements)
# 碰撞检测
if self._fcl_available:
return self._check_with_fcl(placements)
return self._check_with_obb(placements)
def check_bounds(
self, placements: list[dict], lab_width: float, lab_depth: float,
) -> list[str]:
"""返回超出实验室边界的设备 ID 列表。"""
out_of_bounds: list[str] = []
for p in placements:
hw, hd = self._rotated_half_extents(p)
x, y = p["pos"][:2]
if x - hw < 0 or x + hw > lab_width or y - hd < 0 or y + hd > lab_depth:
out_of_bounds.append(p["id"])
return out_of_bounds
def _sync_collision_objects(self, placements: list[dict]) -> None:
"""将设备布局同步到 MoveIt2 规划场景。
使用 {device_id}_ 前缀命名碰撞对象。
"""
for p in placements:
obj_id = f"{p['id']}_"
w, d = p["bbox"]
x, y = p["pos"][:2]
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
h = self._default_height
try:
self._moveit2.add_collision_box(
id=obj_id,
size=(w, d, h),
position=(x, y, h / 2),
quat_xyzw=_yaw_to_quat(theta),
)
except Exception:
logger.warning("Failed to sync collision object %s", obj_id, exc_info=True)
def _check_with_fcl(self, placements: list[dict]) -> list[tuple[str, str]]:
"""使用 python-fcl 进行精确碰撞检测。"""
import fcl
objects: list[tuple[str, Any]] = []
for p in placements:
w, d = p["bbox"]
h = self._default_height
x, y = p["pos"][:2]
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
geom = fcl.Box(w, d, h)
tf = fcl.Transform(
_yaw_to_rotation_matrix(theta),
np.array([x, y, h / 2]),
)
obj = fcl.CollisionObject(geom, tf)
objects.append((p["id"], obj))
collisions: list[tuple[str, str]] = []
n = len(objects)
for i in range(n):
for j in range(i + 1, n):
id_a, obj_a = objects[i]
id_b, obj_b = objects[j]
request = fcl.CollisionRequest()
result = fcl.CollisionResult()
ret = fcl.collide(obj_a, obj_b, request, result)
if ret > 0:
collisions.append((id_a, id_b))
return collisions
def _check_with_obb(self, placements: list[dict]) -> list[tuple[str, str]]:
"""OBB SAT 回退检测(与 MockCollisionChecker 相同算法)。"""
collisions: list[tuple[str, str]] = []
n = len(placements)
for i in range(n):
for j in range(i + 1, n):
a, b = placements[i], placements[j]
corners_a = obb_corners(
a["pos"][0], a["pos"][1],
a["bbox"][0], a["bbox"][1],
a["pos"][2] if len(a["pos"]) > 2 else 0.0,
)
corners_b = obb_corners(
b["pos"][0], b["pos"][1],
b["bbox"][0], b["bbox"][1],
b["pos"][2] if len(b["pos"]) > 2 else 0.0,
)
if obb_overlap(corners_a, corners_b):
collisions.append((a["id"], b["id"]))
return collisions
@staticmethod
def _rotated_half_extents(p: dict) -> tuple[float, float]:
"""计算旋转后 AABB 的半宽和半深。"""
w, d = p["bbox"]
theta = p["pos"][2] if len(p["pos"]) > 2 else 0.0
cos_t = abs(math.cos(theta))
sin_t = abs(math.sin(theta))
half_w = (w * cos_t + d * sin_t) / 2
half_d = (w * sin_t + d * cos_t) / 2
return half_w, half_d
# ---------- IKFastReachabilityChecker ----------
class IKFastReachabilityChecker:
"""基于 MoveIt2 compute_ik 和预计算体素图的可达性检测。
双模式:
1. 体素图模式O(1)):从 .npz 文件加载预计算可达性网格,
将目标点变换到臂基坐标系后直接查表。
2. 实时 IK 模式(~5ms/call调用 MoveIt2.compute_ik()
支持约束感知的精确可达性判断。
优先使用体素图,无匹配时回退到实时 IK。
"""
def __init__(
self,
moveit2: Any = None,
*,
voxel_dir: str | Path | None = None,
voxel_resolution: float = 0.01,
):
"""
Args:
moveit2: MoveIt2 实例(用于实时 IK 回退)
voxel_dir: 预计算体素图目录(.npz 文件,文件名 = arm_id
voxel_resolution: 体素分辨率(米),用于坐标 → 索引转换
"""
self._moveit2 = moveit2
self._voxel_resolution = voxel_resolution
self._voxel_maps: dict[str, _VoxelMap] = {}
if voxel_dir is not None:
self._load_voxel_maps(Path(voxel_dir))
def is_reachable(self, arm_id: str, arm_pose: dict, target: dict) -> bool:
"""判断机械臂在给定位姿下能否到达目标点。
Args:
arm_id: 机械臂设备 ID
arm_pose: {"x": float, "y": float, "theta": float}
target: {"x": float, "y": float, "z": float}
Returns:
True 如果可达
"""
local = _transform_to_arm_frame(arm_pose, target)
# 1. 体素图查询O(1)
if arm_id in self._voxel_maps:
return self._check_voxel(arm_id, local)
# 2. 实时 IK 回退
if self._moveit2 is not None:
return self._check_live_ik(local)
# 无可用检测方式,乐观返回(记录警告)
logger.warning(
"No reachability checker available for arm %s, returning True", arm_id,
)
return True
def _load_voxel_maps(self, voxel_dir: Path) -> None:
"""加载目录下所有 .npz 体素图文件。
文件格式:{arm_id}.npz包含
- "grid": bool ndarray (nx, ny, nz) — True 表示可达
- "origin": float ndarray (3,) — 网格原点(臂基坐标系)
- "resolution": float — 体素分辨率(米)
"""
if not voxel_dir.exists():
logger.warning("Voxel directory does not exist: %s", voxel_dir)
return
for npz_file in voxel_dir.glob("*.npz"):
arm_id = npz_file.stem
try:
data = np.load(str(npz_file))
grid = data["grid"].astype(bool)
origin = data["origin"].astype(float)
resolution = float(data.get("resolution", self._voxel_resolution))
self._voxel_maps[arm_id] = _VoxelMap(
grid=grid, origin=origin, resolution=resolution,
)
logger.info(
"Loaded voxel map for %s: shape=%s, resolution=%.3f",
arm_id, grid.shape, resolution,
)
except Exception:
logger.warning("Failed to load voxel map %s", npz_file, exc_info=True)
def _check_voxel(self, arm_id: str, local: tuple[float, float, float]) -> bool:
"""通过体素网格查询可达性。"""
vm = self._voxel_maps[arm_id]
ix = int(round((local[0] - vm.origin[0]) / vm.resolution))
iy = int(round((local[1] - vm.origin[1]) / vm.resolution))
iz = int(round((local[2] - vm.origin[2]) / vm.resolution))
if (
0 <= ix < vm.grid.shape[0]
and 0 <= iy < vm.grid.shape[1]
and 0 <= iz < vm.grid.shape[2]
):
return bool(vm.grid[ix, iy, iz])
# 超出体素图范围 → 不可达
return False
def _check_live_ik(self, local: tuple[float, float, float]) -> bool:
"""调用 MoveIt2.compute_ik() 进行实时可达性检测。
compute_ik 返回 JointState成功或 None不可达
使用默认朝下姿态(四元数 0, 1, 0, 0 即绕 X 轴旋转 180°
"""
# 目标姿态:末端执行器朝下
quat_xyzw = (0.0, 1.0, 0.0, 0.0)
try:
result = self._moveit2.compute_ik(
position=local,
quat_xyzw=quat_xyzw,
)
return result is not None
except Exception:
logger.warning("compute_ik call failed", exc_info=True)
return False
# ---------- 体素图数据类 ----------
class _VoxelMap:
"""预计算可达性体素网格。"""
__slots__ = ("grid", "origin", "resolution")
def __init__(
self,
grid: np.ndarray,
origin: np.ndarray,
resolution: float,
):
self.grid = grid
self.origin = origin
self.resolution = resolution
# ---------- FCL 辅助 ----------
def _yaw_to_rotation_matrix(theta: float) -> np.ndarray:
"""绕 Z 轴旋转矩阵3×3"""
c, s = math.cos(theta), math.sin(theta)
return np.array([
[c, -s, 0.0],
[s, c, 0.0],
[0.0, 0.0, 1.0],
])
# ---------- 工厂函数 ----------
def create_checkers(
moveit2: Any = None,
*,
mode: str | None = None,
voxel_dir: str | None = None,
) -> tuple[Any, Any]:
"""根据环境变量或参数创建检测器实例。
Args:
moveit2: MoveIt2 实例moveit 模式必需)
mode: "mock" | "moveit"(默认从 LAYOUT_CHECKER_MODE 环境变量读取)
voxel_dir: 体素图目录(默认从 LAYOUT_VOXEL_DIR 环境变量读取)
Returns:
(collision_checker, reachability_checker)
"""
if mode is None:
mode = os.getenv("LAYOUT_CHECKER_MODE", "mock")
if mode == "moveit":
if moveit2 is None:
raise ValueError("MoveIt2 instance required for 'moveit' checker mode")
if voxel_dir is None:
voxel_dir = os.getenv("LAYOUT_VOXEL_DIR")
collision = MoveItCollisionChecker(moveit2)
reachability = IKFastReachabilityChecker(
moveit2, voxel_dir=voxel_dir,
)
logger.info("Using MoveIt2 checkers (voxel_dir=%s)", voxel_dir)
return collision, reachability
# 默认mock 模式
from .mock_checkers import MockCollisionChecker, MockReachabilityChecker
logger.info("Using mock checkers")
return MockCollisionChecker(), MockReachabilityChecker()

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"""Force-directed seeder engine with named parameter presets.
Produces initial device placements for the layout optimizer.
Different layout strategies (compact, spread, workflow-aware) are
parameter configurations of the same force-directed simulation engine.
"""
from __future__ import annotations
import logging
import math
from dataclasses import dataclass, replace
from .models import Device, Lab, Placement
from .obb import obb_corners, obb_overlap, obb_min_distance
logger = logging.getLogger(__name__)
@dataclass
class SeederParams:
"""Parameters for the force-directed seeder engine."""
boundary_attraction: float = 0.0 # >0 push to walls, <0 push to center
mutual_repulsion: float = 1.0 # inter-device repulsion strength
edge_attraction: float = 0.0 # workflow edge attraction (Stage 2)
orientation_mode: str = "none" # "outward" | "inward" | "none"
PRESETS: dict[str, SeederParams | None] = {
"compact_outward": SeederParams(
boundary_attraction=-1.0, mutual_repulsion=0.5, orientation_mode="outward",
),
"spread_inward": SeederParams(
boundary_attraction=1.0, mutual_repulsion=1.0, orientation_mode="inward",
),
"workflow_cluster": SeederParams(
boundary_attraction=-0.5, mutual_repulsion=0.5,
edge_attraction=1.0, orientation_mode="outward",
),
"row_fallback": None, # Delegates to generate_fallback()
}
def resolve_seeder_params(
preset_name: str, overrides: dict | None = None,
) -> SeederParams | None:
"""Look up preset by name and apply overrides."""
if preset_name not in PRESETS:
raise ValueError(
f"Unknown seeder preset '{preset_name}'. "
f"Available: {list(PRESETS.keys())}"
)
params = PRESETS[preset_name]
if params is None or not overrides:
return params
return replace(params, **{k: v for k, v in overrides.items() if hasattr(params, k)})
def seed_layout(
devices: list[Device],
lab: Lab,
params: SeederParams | None,
edges: list[list[str]] | None = None,
) -> list[Placement]:
"""Generate initial device placements using force-directed simulation.
Args:
devices: devices to place
lab: lab dimensions
params: seeder parameters (None = row_fallback)
edges: workflow edges as [device_a_id, device_b_id] pairs (Stage 2)
Returns:
list of Placement objects, one per device
"""
if not devices:
return []
if params is None:
from .pencil_integration import generate_fallback
return generate_fallback(devices, lab)
return _force_simulation(devices, lab, params, edges)
def _force_simulation(
devices: list[Device],
lab: Lab,
params: SeederParams,
edges: list[list[str]] | None = None,
max_iter: int = 80,
dt: float = 0.05,
damping: float = 0.8,
) -> list[Placement]:
"""Run force-directed simulation to produce initial placements."""
n = len(devices)
center_x, center_y = lab.width / 2, lab.depth / 2
# Initialize positions: grid layout within lab bounds
cols = max(1, int(math.ceil(math.sqrt(n))))
rows_count = max(1, math.ceil(n / cols))
positions = [] # (x, y) per device
for i, dev in enumerate(devices):
row, col = divmod(i, cols)
margin = 0.3
x = margin + (col + 0.5) * (lab.width - 2 * margin) / cols
y = margin + (row + 0.5) * (lab.depth - 2 * margin) / rows_count
x = min(max(x, dev.bbox[0] / 2), lab.width - dev.bbox[0] / 2)
y = min(max(y, dev.bbox[1] / 2), lab.depth - dev.bbox[1] / 2)
positions.append([x, y])
# Initialize orientations
thetas = [0.0] * n
# Build edge lookup for Stage 2
edge_set: set[tuple[int, int]] = set()
if edges and params.edge_attraction > 0:
id_to_idx = {d.id: i for i, d in enumerate(devices)}
for e in edges:
if len(e) == 2 and e[0] in id_to_idx and e[1] in id_to_idx:
edge_set.add((id_to_idx[e[0]], id_to_idx[e[1]]))
converged = False
for iteration in range(max_iter):
forces = [[0.0, 0.0] for _ in range(n)]
total_force = 0.0
# 1. Boundary force
for i in range(n):
dx = positions[i][0] - center_x
dy = positions[i][1] - center_y
dist_to_center = math.sqrt(dx * dx + dy * dy) + 1e-9
f = params.boundary_attraction
forces[i][0] += f * dx / dist_to_center
forces[i][1] += f * dy / dist_to_center
# 2. Mutual repulsion (OBB edge-to-edge)
for i in range(n):
for j in range(i + 1, n):
ci = obb_corners(
positions[i][0], positions[i][1],
devices[i].bbox[0], devices[i].bbox[1], thetas[i],
)
cj = obb_corners(
positions[j][0], positions[j][1],
devices[j].bbox[0], devices[j].bbox[1], thetas[j],
)
dist = obb_min_distance(ci, cj)
if dist < 1e-9:
dist = 0.01 # Prevent division by zero for overlapping
dx = positions[i][0] - positions[j][0]
dy = positions[i][1] - positions[j][1]
d_center = math.sqrt(dx * dx + dy * dy) + 1e-9
repulsion = params.mutual_repulsion / (dist * dist + 0.1)
fx = repulsion * dx / d_center
fy = repulsion * dy / d_center
forces[i][0] += fx
forces[i][1] += fy
forces[j][0] -= fx
forces[j][1] -= fy
# 3. Edge attraction (Stage 2)
if params.edge_attraction > 0:
for i_idx, j_idx in edge_set:
dx = positions[j_idx][0] - positions[i_idx][0]
dy = positions[j_idx][1] - positions[i_idx][1]
dist = math.sqrt(dx * dx + dy * dy) + 1e-9
f = params.edge_attraction * dist * 0.1
forces[i_idx][0] += f * dx / dist
forces[i_idx][1] += f * dy / dist
forces[j_idx][0] -= f * dx / dist
forces[j_idx][1] -= f * dy / dist
# 4. Update positions (Euler + damping)
for i in range(n):
positions[i][0] += forces[i][0] * dt * damping
positions[i][1] += forces[i][1] * dt * damping
total_force += math.sqrt(forces[i][0]**2 + forces[i][1]**2)
# 5. Update orientations
if params.orientation_mode != "none":
for i in range(n):
thetas[i] = _compute_orientation(
positions[i][0], positions[i][1],
center_x, center_y,
devices[i], params.orientation_mode,
)
# 6. Clamp to lab bounds
for i in range(n):
hw, hh = devices[i].bbox[0] / 2, devices[i].bbox[1] / 2
positions[i][0] = max(hw, min(lab.width - hw, positions[i][0]))
positions[i][1] = max(hh, min(lab.depth - hh, positions[i][1]))
if total_force < 0.01 * n:
converged = True
logger.info("Force simulation converged at iteration %d", iteration)
break
if not converged:
logger.info("Force simulation reached max iterations (%d)", max_iter)
placements = [
Placement(device_id=devices[i].id, x=positions[i][0], y=positions[i][1], theta=thetas[i])
for i in range(n)
]
# Log initial collision count
initial_collisions = _count_collisions(devices, placements)
logger.info("Seeder: %d initial collision pairs before resolution", initial_collisions)
# Collision resolution pass
placements = _resolve_collisions(devices, placements, lab, max_passes=5)
# Log diagnostics
final_collisions = _count_collisions(devices, placements)
no_openings = sum(1 for d in devices if not d.openings)
logger.info(
"Seeder complete: %d devices, %d without openings, %d collision pairs remaining",
n, no_openings, final_collisions,
)
return placements
def _compute_orientation(
x: float, y: float,
center_x: float, center_y: float,
device: Device,
mode: str,
) -> float:
"""Compute theta so the device's front faces outward or inward."""
dx = x - center_x
dy = y - center_y
if abs(dx) < 1e-9 and abs(dy) < 1e-9:
return 0.0
angle_to_device = math.atan2(dy, dx)
if device.openings:
front = device.openings[0].direction
else:
front = (0.0, -1.0) # Default: -Y is front
front_angle = math.atan2(front[1], front[0])
if mode == "outward":
target = angle_to_device
elif mode == "inward":
target = angle_to_device + math.pi
else:
return 0.0
return (target - front_angle) % (2 * math.pi)
def _count_collisions(devices: list[Device], placements: list[Placement]) -> int:
"""Count OBB collision pairs (for diagnostics logging)."""
n = len(devices)
count = 0
for i in range(n):
for j in range(i + 1, n):
ci = obb_corners(placements[i].x, placements[i].y,
devices[i].bbox[0], devices[i].bbox[1], placements[i].theta)
cj = obb_corners(placements[j].x, placements[j].y,
devices[j].bbox[0], devices[j].bbox[1], placements[j].theta)
if obb_overlap(ci, cj):
count += 1
return count
def _resolve_collisions(
devices: list[Device],
placements: list[Placement],
lab: Lab,
max_passes: int = 5,
) -> list[Placement]:
"""Push overlapping devices apart. Returns new placement list."""
positions = [[p.x, p.y] for p in placements]
thetas = [p.theta for p in placements]
n = len(devices)
for pass_num in range(max_passes):
has_collision = False
for i in range(n):
for j in range(i + 1, n):
ci = obb_corners(
positions[i][0], positions[i][1],
devices[i].bbox[0], devices[i].bbox[1], thetas[i],
)
cj = obb_corners(
positions[j][0], positions[j][1],
devices[j].bbox[0], devices[j].bbox[1], thetas[j],
)
if obb_overlap(ci, cj):
has_collision = True
dx = positions[i][0] - positions[j][0]
dy = positions[i][1] - positions[j][1]
dist = math.sqrt(dx * dx + dy * dy) + 1e-9
push = 0.5 * (
max(devices[i].bbox[0], devices[i].bbox[1])
+ max(devices[j].bbox[0], devices[j].bbox[1])
) / 4
positions[i][0] += push * dx / dist
positions[i][1] += push * dy / dist
positions[j][0] -= push * dx / dist
positions[j][1] -= push * dy / dist
# Clamp to bounds (rotation-aware AABB half-extents)
for i in range(n):
cos_t = abs(math.cos(thetas[i]))
sin_t = abs(math.sin(thetas[i]))
hw = (devices[i].bbox[0] * cos_t + devices[i].bbox[1] * sin_t) / 2
hh = (devices[i].bbox[0] * sin_t + devices[i].bbox[1] * cos_t) / 2
positions[i][0] = max(hw, min(lab.width - hw, positions[i][0]))
positions[i][1] = max(hh, min(lab.depth - hh, positions[i][1]))
if not has_collision:
logger.info("Collision resolution complete after %d passes", pass_num + 1)
break
else:
logger.warning(
"Collision resolution: %d passes exhausted, collisions may remain",
max_passes,
)
return [
Placement(device_id=placements[i].device_id,
x=positions[i][0], y=positions[i][1],
theta=thetas[i], uuid=placements[i].uuid)
for i in range(n)
]

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"""FastAPI 开发服务器。
开发阶段独立运行于 localhost:8000前端通过 CORS 调用。
集成阶段合并到 Uni-Lab-OS 的 FastAPI 服务中。
运行方式:
uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
调试模式(启用 DEBUG 日志,含优化器逐代 cost 明细):
LAYOUT_DEBUG=1 uvicorn unilabos.layout_optimizer.server:app --host 0.0.0.0 --port 8000 --reload
日志文件:
自动写入 layout_optimizer/logs/{YYYYMMDD_HHMMSS}.log始终 DEBUG 级别)。
前端 1s 轮询的 GET /scene/placements 200 行不写入日志文件。
前端访问:
http://localhost:8000/
"""
from __future__ import annotations
from collections import defaultdict
import itertools
import logging
import logging.handlers
import math
import os
from datetime import datetime
from pathlib import Path
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse, RedirectResponse
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel
from .constraints import DEFAULT_WEIGHT_ANGLE # noqa: F401 — kept for external use
from .device_catalog import (
create_devices_from_list,
load_devices_from_assets,
load_devices_from_registry,
load_footprints,
merge_device_lists,
)
from .lab_parser import parse_lab
from .intent_interpreter import InterpretResult, interpret_intents
from .models import Constraint, Intent
from .optimizer import optimize
_console_level = logging.DEBUG if os.getenv("LAYOUT_DEBUG") else logging.INFO
# root logger must be DEBUG so the file handler receives all records;
# console output level is controlled separately via its handler.
logging.basicConfig(level=logging.DEBUG)
# basicConfig creates a default StreamHandler — set its level to the console level
for _h in logging.getLogger().handlers:
if isinstance(_h, logging.StreamHandler):
_h.setLevel(_console_level)
logger = logging.getLogger(__name__)
# --- 文件日志:实时写入 logs/ 目录,按启动时间命名 ---
_LOG_DIR = Path(__file__).parent / "logs"
_LOG_DIR.mkdir(exist_ok=True)
_log_file = _LOG_DIR / f"{datetime.now():%Y%m%d_%H%M%S}.log"
class _PollingFilter(logging.Filter):
"""过滤掉前端 1s 轮询产生的 GET /scene/placements 日志行。"""
def filter(self, record: logging.LogRecord) -> bool:
msg = record.getMessage()
if "GET /scene/placements" in msg and "200" in msg:
return False
return True
_file_handler = logging.FileHandler(_log_file, encoding="utf-8")
_file_handler.setLevel(logging.DEBUG)
_file_handler.setFormatter(
logging.Formatter("%(asctime)s %(levelname)-5s [%(name)s] %(message)s")
)
_file_handler.addFilter(_PollingFilter())
logging.getLogger().addHandler(_file_handler)
STATIC_DIR = Path(__file__).parent / "static"
# 可配置路径
# __file__ -> Uni-Lab-OS/unilabos/layout_optimizer/server.py
_UNILABOS_DIR = Path(__file__).resolve().parent.parent # .../Uni-Lab-OS/unilabos/
UNI_LAB_ASSETS_DIR = Path(
os.getenv("UNI_LAB_ASSETS_DIR", str(_UNILABOS_DIR.parent.parent.parent / "uni-lab-assets"))
)
UNI_LAB_ASSETS_MODELS_DIR = UNI_LAB_ASSETS_DIR / "device_models"
UNI_LAB_ASSETS_DATA_JSON = UNI_LAB_ASSETS_DIR / "data.json"
UNI_LAB_OS_DEVICE_MESH_DIR = Path(
os.getenv(
"UNI_LAB_OS_DEVICE_MESH_DIR",
str(_UNILABOS_DIR / "device_mesh" / "devices"),
)
)
app = FastAPI(title="Layout Optimizer", version="0.2.0")
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # 开发阶段允许所有来源
allow_methods=["*"],
allow_headers=["*"],
)
# 挂载静态文件目录
app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")
# 挂载 3D 模型和缩略图
if UNI_LAB_ASSETS_MODELS_DIR.exists():
app.mount("/models", StaticFiles(directory=str(UNI_LAB_ASSETS_MODELS_DIR)), name="models")
logger.info("Mounted /models from %s", UNI_LAB_ASSETS_MODELS_DIR)
else:
logger.warning("uni-lab-assets models dir not found: %s", UNI_LAB_ASSETS_MODELS_DIR)
# ---------- 设备目录缓存 ----------
_device_cache: list[dict] | None = None
_DEVICE_PARAM_KEYS = {"device_a", "device_b", "arm_id", "target_device_id", "device"}
# 消耗品/配件关键词(不独立放置于实验台)
_CONSUMABLE_KEYWORDS = {
"plate", "well", "tube", "tip", "reservoir", "carrier", "nest",
"adapter", "trough", "magnet_module", "magnet_plate", "rack", "lid",
"seal", "cap", "vial", "flask", "dish", "block", "strip", "insert",
"gasket", "pad", "grid_segment", "spacer", "diti_tray",
}
# 但包含这些关键词的是独立设备,不是消耗品
_DEVICE_KEYWORDS = {
"reader", "handler", "hotel", "washer", "stacker", "sealer", "labeler",
"centrifuge", "incubator", "shaker", "robot", "arm", "flex", "dispenser",
"printer", "scanner", "analyzer", "fluorometer", "spectrophotometer",
"thermocycler", "module",
}
def _is_standalone_device(device_id: str, bbox: tuple[float, float]) -> bool:
"""判断设备是否独立放置于实验台(非消耗品/配件)。"""
mx = max(bbox[0], bbox[1])
mn = min(bbox[0], bbox[1])
if mx >= 0.30:
return True # 大于 30cm 一定是独立设备
if mx < 0.05:
return False # 小于 5cm 一定是消耗品
lower = device_id.lower()
# 非常扁平(一维 < 3cm的几乎都是配件/载具,即使名称匹配设备关键词
if mn < 0.03:
return False
# 先检查消耗品关键词(如果匹配,再看是否有设备关键词覆盖)
is_consumable_name = any(kw in lower for kw in _CONSUMABLE_KEYWORDS)
is_device_name = any(kw in lower for kw in _DEVICE_KEYWORDS)
if is_consumable_name and not is_device_name:
return False
if is_device_name:
return True
# 默认:>= 15cm 视为设备
return mx >= 0.15
def _build_device_list() -> list[dict]:
"""构建合并后的设备列表(缓存)。"""
global _device_cache
if _device_cache is not None:
return _device_cache
footprints = load_footprints()
registry = load_devices_from_registry(UNI_LAB_OS_DEVICE_MESH_DIR, footprints)
assets = load_devices_from_assets(UNI_LAB_ASSETS_DATA_JSON, footprints)
merged = merge_device_lists(registry, assets)
_device_cache = [
{
"id": d.id,
"name": d.name,
"device_type": d.device_type,
"source": d.source,
"bbox": list(d.bbox),
"height": d.height,
"origin_offset": list(d.origin_offset),
"openings": [
{"direction": list(o.direction), "label": o.label}
for o in d.openings
],
"model_path": d.model_path,
"model_type": d.model_type,
"thumbnail_url": d.thumbnail_url,
"is_standalone": _is_standalone_device(d.id, d.bbox),
}
for d in merged
]
standalone = sum(1 for d in _device_cache if d["is_standalone"])
logger.info("Built device catalog: %d devices (%d standalone)", len(_device_cache), standalone)
return _device_cache
def _catalog_id_from_internal(device_id: str) -> str:
"""内部实例 ID → catalog ID。"""
return device_id.split("#", 1)[0]
def _expand_constraints_for_duplicates(
constraints: list[Constraint], devices: list,
) -> list[Constraint]:
"""将引用 bare catalog ID 的约束扩展到所有重复实例。"""
catalog_instances: dict[str, list[str]] = defaultdict(list)
for dev in devices:
catalog_instances[_catalog_id_from_internal(dev.id)].append(dev.id)
expanded_constraints: list[Constraint] = []
for constraint in constraints:
fan_out_keys: list[str] = []
fan_out_values: list[list[str]] = []
for key in _DEVICE_PARAM_KEYS:
if key not in constraint.params:
continue
ref_id = constraint.params[key]
if "#" in ref_id:
continue
instances = catalog_instances.get(ref_id, [])
if len(instances) > 1:
fan_out_keys.append(key)
fan_out_values.append(instances)
logger.info(
"Fan-out: %s %s=%s -> %d instances",
constraint.rule_name, key, ref_id, len(instances),
)
if not fan_out_keys:
expanded_constraints.append(constraint)
continue
for combo in itertools.product(*fan_out_values):
new_params = dict(constraint.params)
for key, internal_id in zip(fan_out_keys, combo):
new_params[key] = internal_id
expanded_constraints.append(
Constraint(
type=constraint.type,
rule_name=constraint.rule_name,
params=new_params,
weight=constraint.weight,
)
)
return expanded_constraints
def _maybe_add_prefer_aligned_constraint(
constraints: list[Constraint], align_weight: float,
) -> list[Constraint]:
"""仅在用户未显式提供 prefer_aligned 时注入对齐约束。"""
if align_weight <= 0:
return constraints
if any(c.rule_name == "prefer_aligned" for c in constraints):
logger.info("Skipping auto-injected prefer_aligned because one already exists")
return constraints
constraints.append(
Constraint(
type="soft",
rule_name="prefer_aligned",
weight=align_weight,
)
)
return constraints
# ---------- 路由 ----------
@app.get("/", include_in_schema=False)
async def root():
return RedirectResponse(url="/lab3d")
@app.get("/lab3d", include_in_schema=False)
async def lab3d_ui():
return FileResponse(STATIC_DIR / "lab3d.html")
@app.get("/devices")
async def list_devices(source: str = "all"):
"""返回合并后的设备目录。?source=registry|assets|all"""
devices = _build_device_list()
if source != "all":
devices = [d for d in devices if d["source"] == source]
return devices
@app.get("/health")
async def health():
return {"status": "ok"}
# ---------- 意图解释 API ----------
class IntentSpec(BaseModel):
intent: str
params: dict = {}
description: str = ""
class TranslationEntry(BaseModel):
source_intent: str
source_description: str
source_params: dict
generated_constraints: list[dict]
explanation: str
confidence: str = "high"
class InterpretRequest(BaseModel):
intents: list[IntentSpec]
class InterpretResponse(BaseModel):
constraints: list[dict]
translations: list[TranslationEntry]
workflow_edges: list[list[str]]
errors: list[str]
@app.post("/interpret", response_model=InterpretResponse)
async def run_interpret(request: InterpretRequest):
"""将语义化意图翻译为约束列表,供用户确认后传入 /optimize。"""
logger.info("Interpret request: %d intents", len(request.intents))
intents = [
Intent(
intent=i.intent,
params=i.params,
description=i.description,
)
for i in request.intents
]
result: InterpretResult = interpret_intents(intents)
return InterpretResponse(
constraints=[
{"type": c.type, "rule_name": c.rule_name, "params": c.params, "weight": c.weight}
for c in result.constraints
],
translations=[
TranslationEntry(
source_intent=t["source_intent"],
source_description=t.get("source_description", ""),
source_params=t.get("source_params", {}),
generated_constraints=t["generated_constraints"],
explanation=t["explanation"],
confidence=t.get("confidence", "high"),
)
for t in result.translations
],
workflow_edges=result.workflow_edges,
errors=result.errors,
)
@app.get("/interpret/schema")
async def interpret_schema():
"""返回可用意图类型及其参数规范,供 LLM agent 发现和使用。"""
return {
"description": "Layout optimizer intent schema. LLM agents should translate user requests into these intents.",
"intents": {
"reachable_by": {
"description": "Robot arm must be able to reach all target devices",
"params": {
"arm": {"type": "string", "required": True, "description": "Device ID of robot arm"},
"targets": {"type": "list[string]", "required": True, "description": "Device IDs the arm must reach"},
},
"generates": "hard reachability constraint per target",
},
"close_together": {
"description": "Group of devices should be placed near each other",
"params": {
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
},
"generates": "soft minimize_distance for each pair",
},
"far_apart": {
"description": "Devices should be placed far from each other",
"params": {
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
},
"generates": "soft maximize_distance for each pair",
},
"keep_adjacent": {
"description": "Devices should stay adjacent, similar to close_together",
"params": {
"devices": {"type": "list[string]", "required": True, "description": "Device IDs (min 2)"},
"priority": {"type": "string", "required": False, "default": "medium", "enum": ["low", "medium", "high"]},
},
"generates": "soft minimize_distance for each pair",
},
"max_distance": {
"description": "Two devices must be within a maximum distance",
"params": {
"device_a": {"type": "string", "required": True},
"device_b": {"type": "string", "required": True},
"distance": {"type": "float", "required": True, "description": "Max edge-to-edge distance in meters"},
},
"generates": "hard distance_less_than",
},
"min_distance": {
"description": "Two devices must be at least a minimum distance apart",
"params": {
"device_a": {"type": "string", "required": True},
"device_b": {"type": "string", "required": True},
"distance": {"type": "float", "required": True, "description": "Min edge-to-edge distance in meters"},
},
"generates": "hard distance_greater_than",
},
"min_spacing": {
"description": "Minimum gap between all device pairs",
"params": {
"min_gap": {"type": "float", "required": False, "default": 0.3, "description": "Minimum gap in meters"},
},
"generates": "hard min_spacing",
},
"workflow_hint": {
"description": "Workflow step order — consecutive devices should be near each other",
"params": {
"workflow": {"type": "string", "required": False, "description": "Workflow name (e.g. 'pcr')"},
"devices": {"type": "list[string]", "required": True, "description": "Ordered device IDs following workflow steps"},
},
"generates": "soft minimize_distance for consecutive pairs + workflow_edges",
},
"face_outward": {
"description": "Devices should face outward from lab center",
"params": {},
"generates": "soft prefer_orientation_mode outward",
},
"face_inward": {
"description": "Devices should face inward toward lab center",
"params": {},
"generates": "soft prefer_orientation_mode inward",
},
"align_cardinal": {
"description": "Devices should align to cardinal directions (0/90/180/270 degrees)",
"params": {},
"generates": "soft prefer_aligned",
},
},
}
# ---------- 优化 API ----------
class DeviceSpec(BaseModel):
id: str
name: str = ""
size: list[float] | None = None
device_type: str = "static"
uuid: str = ""
class ConstraintSpec(BaseModel):
type: str # "hard" or "soft"
rule_name: str
params: dict = {}
weight: float = 1.0
class LabSpec(BaseModel):
width: float
depth: float
obstacles: list[dict] = []
class OptimizeRequest(BaseModel):
devices: list[DeviceSpec]
lab: LabSpec
constraints: list[ConstraintSpec] = []
seeder: str = "compact_outward"
seeder_overrides: dict = {}
run_de: bool = True
workflow_edges: list[list[str]] = []
maxiter: int = 200
seed: int | None = None
snap_cardinal: bool = False
angle_granularity: int | None = None
arm_reach: dict[str, float] = {}
# DE 超参数
strategy: str = "currenttobest1bin"
angle_mode: str = "joint"
mutation: list[float] = [0.5, 1.0]
theta_mutation: list[float] | None = None
recombination: float = 0.7
crossover_mode: str = "device"
class PositionXYZ(BaseModel):
x: float
y: float
z: float
class PlacementResult(BaseModel):
device_id: str
uuid: str
position: PositionXYZ
rotation: PositionXYZ
class OptimizeResponse(BaseModel):
placements: list[PlacementResult]
cost: float
success: bool
seeder_used: str = ""
de_ran: bool = True
@app.post("/optimize", response_model=OptimizeResponse)
async def run_optimize(request: OptimizeRequest):
"""接收设备列表+约束,返回最优布局方案。"""
from fastapi import HTTPException
from .constraints import evaluate_default_hard_constraints, evaluate_constraints
from .mock_checkers import MockCollisionChecker, MockReachabilityChecker
from .optimizer import optimize, snap_theta, snap_theta_safe
from .seeders import resolve_seeder_params, seed_layout
logger.info(
"Optimize request: %d devices, lab %.1f×%.1f, %d constraints, seeder=%s, run_de=%s, angle_granularity=%s",
len(request.devices),
request.lab.width,
request.lab.depth,
len(request.constraints),
request.seeder,
request.run_de,
request.angle_granularity,
)
if request.angle_granularity not in (None, 4, 8, 12, 24):
raise HTTPException(
status_code=400,
detail="angle_granularity must be one of: 4, 8, 12, 24",
)
# 转换输入
devices = create_devices_from_list(
[d.model_dump() for d in request.devices]
)
id_to_catalog = {dev.id: _catalog_id_from_internal(dev.id) for dev in devices}
id_to_uuid = {dev.id: (dev.uuid or dev.id) for dev in devices}
lab = parse_lab(request.lab.model_dump())
constraints = [
Constraint(
type=c.type,
rule_name=c.rule_name,
params=c.params,
weight=c.weight,
)
for c in request.constraints
]
constraints = _expand_constraints_for_duplicates(constraints, devices)
# 1. Resolve seeder
try:
params = resolve_seeder_params(request.seeder, request.seeder_overrides or None)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
# 2. Seed
seed_placements = seed_layout(
devices, lab, params,
request.workflow_edges or None,
)
# 3. Auto-inject alignment soft constraint (opt-in via seeder_overrides)
if request.run_de and seed_placements:
# prefer_aligned: penalize non-cardinal angles默认关闭用户可通过 align_cardinal intent 或 seeder_overrides 开启)
constraints = _maybe_add_prefer_aligned_constraint(
constraints,
request.seeder_overrides.get("align_weight", 0),
)
# 4. Validate DE hyperparameters
if request.strategy not in {"currenttobest1bin", "best1bin", "rand1bin"}:
raise HTTPException(
status_code=400,
detail=f"strategy must be one of: currenttobest1bin, best1bin, rand1bin (got {request.strategy!r})",
)
if request.angle_mode not in {"joint", "hybrid"}:
raise HTTPException(
status_code=400,
detail=f"angle_mode must be one of: joint, hybrid (got {request.angle_mode!r})",
)
if request.crossover_mode not in {"device", "dimension"}:
raise HTTPException(
status_code=400,
detail=f"crossover_mode must be one of: device, dimension (got {request.crossover_mode!r})",
)
if len(request.mutation) != 2 or request.mutation[0] > request.mutation[1]:
raise HTTPException(status_code=400, detail="mutation must be [F_min, F_max] with F_min <= F_max")
if request.mutation[0] < 0 or request.mutation[1] > 2.0:
raise HTTPException(status_code=400, detail="mutation values must be in [0, 2.0]")
if request.theta_mutation is not None:
if len(request.theta_mutation) != 2 or request.theta_mutation[0] > request.theta_mutation[1]:
raise HTTPException(status_code=400, detail="theta_mutation must be [F_min, F_max] with F_min <= F_max")
if request.theta_mutation[0] < 0 or request.theta_mutation[1] > 2.0:
raise HTTPException(status_code=400, detail="theta_mutation values must be in [0, 2.0]")
if not (0 <= request.recombination <= 1.0):
raise HTTPException(status_code=400, detail="recombination must be in [0, 1.0]")
# 5. Conditional Differential Evolution
de_ran = False
checker = MockCollisionChecker()
reachability_checker = MockReachabilityChecker(request.arm_reach or None)
if request.run_de:
result_placements = optimize(
devices=devices,
lab=lab,
constraints=constraints,
collision_checker=checker,
reachability_checker=reachability_checker,
seed_placements=seed_placements,
maxiter=request.maxiter,
seed=request.seed,
strategy=request.strategy,
workflow_edges=request.workflow_edges or None,
angle_granularity=request.angle_granularity,
angle_mode=request.angle_mode,
mutation=tuple(request.mutation),
theta_mutation=tuple(request.theta_mutation) if request.theta_mutation else None,
recombination=request.recombination,
crossover_mode=request.crossover_mode,
)
de_ran = True
else:
result_placements = seed_placements
# 5. θ snap post-processingopt-in默认关闭
if request.snap_cardinal and request.angle_granularity is None:
result_placements = snap_theta_safe(result_placements, devices, lab, checker)
elif request.snap_cardinal and request.angle_granularity is not None:
logger.info(
"snap_cardinal ignored because angle_granularity=%s already constrains theta",
request.angle_granularity,
)
# 6. Evaluate final cost (binary mode for pass/fail reporting)
final_cost = evaluate_default_hard_constraints(
devices, result_placements, lab, checker, graduated=False,
)
# 也检查用户硬约束binary 模式)
if constraints and not math.isinf(final_cost):
user_hard_cost = evaluate_constraints(
devices, result_placements, lab, constraints, checker, reachability_checker,
graduated=False,
)
if math.isinf(user_hard_cost):
final_cost = math.inf
return OptimizeResponse(
placements=[
PlacementResult(
device_id=id_to_catalog.get(p.device_id, p.device_id),
uuid=id_to_uuid.get(p.device_id, p.device_id),
position=PositionXYZ(x=round(p.x, 4), y=round(p.y, 4), z=0.0),
rotation=PositionXYZ(x=0.0, y=0.0, z=round(p.theta, 4)),
)
for p in result_placements
],
cost=final_cost,
success=not math.isinf(final_cost),
seeder_used=request.seeder,
de_ran=de_ran,
)
# ---------- 场景状态 API演示用 ----------
_scene_state: dict = {"version": 0, "placements": []}
_lab_state: dict = {"width": 4.0, "depth": 4.0}
class LabDimensions(BaseModel):
width: float
depth: float
@app.get("/scene/lab")
async def get_lab_dimensions():
"""返回当前实验室尺寸前端推送agent 读取)。"""
return _lab_state
@app.post("/scene/lab")
async def set_lab_dimensions(dims: LabDimensions):
"""前端在加载和尺寸变更时推送。"""
_lab_state["width"] = dims.width
_lab_state["depth"] = dims.depth
return _lab_state
class ScenePlacementsRequest(BaseModel):
placements: list[PlacementResult]
@app.post("/scene/placements")
async def set_scene_placements(request: ScenePlacementsRequest):
"""Agent 写入布局结果,前端轮询读取。"""
_scene_state["version"] += 1
_scene_state["placements"] = [p.model_dump() for p in request.placements]
logger.info(
"Scene placements updated: version=%d, count=%d",
_scene_state["version"],
len(request.placements),
)
return {"version": _scene_state["version"], "count": len(request.placements)}
@app.get("/scene/placements")
async def get_scene_placements():
"""前端轮询此端点,检测 version 变化后应用布局。"""
return _scene_state
@app.delete("/scene/placements")
async def clear_scene_placements():
"""重置场景状态(重录时使用)。"""
_scene_state["version"] = 0
_scene_state["placements"] = []
return {"version": 0, "placements": []}

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[
{"id": "arm_1", "name": "Elite CS66 Arm", "size": [0.20, 0.20], "device_type": "articulation"},
{"id": "liquid_handler", "name": "Agilent Bravo", "size": [0.80, 0.65], "device_type": "static"},
{"id": "centrifuge", "name": "Centrifuge", "size": [0.50, 0.50], "device_type": "static"},
{"id": "plate_hotel", "name": "Thermo Orbitor RS2", "size": [0.45, 0.55], "device_type": "static"},
{"id": "hplc", "name": "HPLC Station", "size": [0.60, 0.50], "device_type": "static"}
]

View File

@@ -0,0 +1,7 @@
{
"width": 5.0,
"depth": 4.0,
"obstacles": [
{"x": 2.5, "y": 0.0, "width": 0.1, "depth": 0.5}
]
}

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