851ed65f45
camel-oasis (transitively via sentence-transformers) hard-imports torch in
oasis/social_platform/recsys.py, so torch cannot be removed while OASIS
simulation is a feature. On linux-x86_64 the default PyPI torch wheel is the
CUDA build, which dragged ~several GB of nvidia-* packages into the image
even though this server has no GPU and all LLM + embedding calls go through
an API (generate_post_vector_openai).
Fix: force torch to resolve from PyTorch's CPU-only index via [tool.uv]:
- override-dependencies torch==2.13.0, [[tool.uv.index]] pytorch-cpu, and
[tool.uv.sources] torch={index=pytorch-cpu}.
Result after re-lock: all nvidia-* + triton packages removed (0 remaining in
uv.lock), torch 2.9.1 -> 2.13.0+cpu. Verified: torch/sentence_transformers/
oasis/from app import create_app all import fine with CPU torch
(cuda: False); backend suite 201 passed. Dockerfile keeps an import-time
verify after uv sync instead of the now-unneeded nvidia uninstall step.
73 lines
1.7 KiB
TOML
73 lines
1.7 KiB
TOML
[project]
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name = "crowdsight-backend"
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version = "0.1.0"
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description = "CrowdSight - 简洁通用的群体智能引擎，预测万物"
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requires-python = ">=3.11,<3.13"
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license = { text = "AGPL-3.0" }
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authors = [
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{ name = "CrowdSight Team" }
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]
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dependencies = [
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# 核心框架
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"flask>=3.0.0",
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"flask-cors>=6.0.0",
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# LLM 相关
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"openai>=1.0.0",
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# Zep Cloud
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"zep-cloud==3.13.0",
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# OASIS 社交媒体模拟
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"camel-oasis==0.2.5",
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"camel-ai==0.2.78",
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# 文件处理
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"PyMuPDF>=1.24.0",
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# 编码检测（支持非UTF-8编码的文本文件）
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"charset-normalizer>=3.0.0",
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"chardet>=5.0.0",
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# 工具库
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"python-dotenv>=1.0.0",
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"pydantic>=2.0.0",
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"sqlalchemy>=2.0,<3",
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"gunicorn>=21.2.0",
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"alembic>=1.13,<2",
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"argon2-cffi>=23.1",
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"psycopg[binary]>=3.2",
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"cryptography>=41.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=8.0.0",
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"pytest-asyncio>=0.23.0",
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"pipreqs>=0.5.0",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[dependency-groups]
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dev = [
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"pytest>=8.0.0",
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"pytest-asyncio>=0.23.0",
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]
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[tool.hatch.build.targets.wheel]
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packages = ["app"]
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# Force torch (transitively pulled by camel-oasis -> sentence-transformers) to
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# resolve from PyTorch's CPU-only index. The server has no GPU and all LLM and
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# embedding calls go through an API, so the CUDA build (which drags several GB
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# of nvidia-* packages) is pure waste. torch keeps working as a CPU runtime;
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# recsys.py's `import torch` / `import sentence_transformers` still succeed.
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[tool.uv]
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override-dependencies = ["torch==2.13.0"]
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[[tool.uv.index]]
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name = "pytorch-cpu"
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url = "https://download.pytorch.org/whl/cpu"
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explicit = true
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[tool.uv.sources]
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torch = { index = "pytorch-cpu" }
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