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ThearchyHelios
4e901be0ec
environment.yml 只负责把解释器和依赖装进具名环境 agentlab，依赖清单仍以 backend/pyproject.toml 为准，不在两处各写一遍。dev.sh 通过 conda run 解析出 真实解释器路径再启动 uvicorn，环境不存在时自动按 environment.yml 创建。 uv.lock 一并删掉：留着会和 conda 装出来的环境慢慢漂移，两套锁反而更难查问题。
41 lines
1.1 KiB
TOML
41 lines
1.1 KiB
TOML
[project]
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name = "agentlab-backend"
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version = "0.1.0"
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description = "AgentLab — 可视化 Agent 编排实验台后端"
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requires-python = ">=3.12"
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dependencies = [
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"fastapi>=0.115",
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"uvicorn[standard]>=0.32",
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"pydantic>=2.9",
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"pydantic-settings>=2.6",
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"sqlalchemy[asyncio]>=2.0.36",
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"aiosqlite>=0.20",
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"greenlet>=3.1",
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"httpx>=0.28",
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"python-multipart>=0.0.17",
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"langgraph",
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"langgraph-checkpoint-sqlite",
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"langchain-core",
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"langchain-anthropic",
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"langchain-openai",
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"langchain-mcp-adapters",
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"mcp",
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"numpy>=2.0",
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"jsonschema>=4.23",
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"beautifulsoup4>=4.12",
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"cryptography>=43.0",
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]
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[project.optional-dependencies]
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# microVM 沙箱（独立 Linux 内核）。约 35MB wheel + 首次约 50MB 运行时下载，
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# 再加一次 OCI 镜像拉取（实测约 55s），所以不进默认安装。
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# environment.yml 里已经带上了；单独装用 `pip install 'agentlab-backend[microvm]'`。
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microvm = ["microsandbox>=0.6"]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["app"]
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