JiuContinent
71ca804764
feat: 添加公司AI管理平台基础架构 添加了完整的FastAPI后端项目结构，包括： - 环境配置文件(.env.example)和项目说明文档(README.md、AGENTS.md) - Dockerfile用于容器化部署 - 核心基础设施：配置管理、数据库连接、调度器、安全认证 - 模块化设计：AI代理、审批流程、审计日志、业务台账等功能模块 - 支持多数据库连接(主库和遗留系统只读库) - AI适配器支持OpenClaw、Hermes、OpenAI兼容接口 - 飞书集成、报表生成、风险监控等企业级功能 - 完整的依赖管理和测试指南 ```
42 lines
3.0 KiB
Markdown
42 lines
3.0 KiB
Markdown
# Repository Guidelines
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## Project Structure & Module Organization
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This is a FastAPI modular monolith for company AI management workflows. Source lives in `app/`. Shared infrastructure is under `app/core/`; `app/api/router.py` wires modules under `/api/v1`. Business capabilities live in `app/modules/`: `business`, `legacy_mysql`, `feishu`, `ai_agent`, `reports`, `risk`, `approvals`, and `audit`. Database tools are in `app/tools/`. Tests live in `tests/`, scripts in `scripts/`, and notes in `docs/`.
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## Modular Design & Technology Direction
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All new work must start with modular design: define boundaries, services, schemas, and adapters before coding. Prefer modern, maintained patterns and tech aligned with FastAPI, SQLAlchemy 2, Pydantic Settings, and async-ready integrations. Use service layer, adapter, dependency injection, and ports/adapters for external systems. Add dependencies only with clear benefit.
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## Build, Test, and Development Commands
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Common commands:
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```powershell
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conda env create -f environment.yml
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conda env update -f environment.yml --prune
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conda run -n company-ai-platform python -m app.tools.init_db
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conda run -n company-ai-platform uvicorn app.main:app --reload --host 0.0.0.0 --port 8010
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conda run -n company-ai-platform python -m compileall app tests scripts
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conda run -n company-ai-platform python scripts\verify_smoke.py
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conda run -n company-ai-platform pytest -q
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```
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## Coding Style & Naming Conventions
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Use Python 3.11, 4-space indentation, type hints, and concise service classes. Follow `models.py`, `schemas.py`, `service.py`, and `routes.py`. Keep routes thin and put business logic in services. Use snake_case for functions, variables, filenames; use PascalCase for SQLAlchemy models and Pydantic schemas. Ruff uses line length `100`.
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Follow the Google Python Style Guide: group imports as standard library, third-party, local; write docstrings for non-trivial public APIs; prefer explicit exceptions and early returns; and keep functions focused. Use type annotations instead of type comments.
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## Testing Guidelines
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Tests use `pytest` and FastAPI `TestClient`. Name files `test_*.py` and functions `test_*`. Prefer temporary SQLite databases, as in `tests/test_smoke.py`, so tests do not require MySQL, Feishu, or external AI providers. Cover approval gates, audit-sensitive flows, and API responses for high-risk modules.
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## Commit & Pull Request Guidelines
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No Git history is available. Use short, imperative commits such as `Add approval audit test`. Pull requests should describe the change, list verification, mention config or migration impacts, and link related issues. Include screenshots only for API docs or visible UI changes.
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## Security & Configuration Tips
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Do not commit real `.env` files or secrets. Start from `.env.example`. Keep `LEGACY_DATABASE_URL` read-only, set `API_KEY` outside local-only testing, and configure Feishu verification tokens before exposing webhooks. High-risk `fund-accounts` and `performance-metrics` updates must require approved tickets.
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