Backend: - FastAPI WebSocket /ws endpoint with streaming via LangGraph astream - LangGraph Supervisor connecting 3 mock agents (order_lookup, order_actions, fallback) - YAML Agent Registry with Pydantic validation and immutable configs - PostgresSaver checkpoint persistence via langgraph-checkpoint-postgres - Session TTL with 30-min sliding window and interrupt extension - LLM provider abstraction (Anthropic/OpenAI/Google) - Token usage + cost tracking callback handler - Input validation: message size cap, thread_id format, content length - Security: no hardcoded defaults, startup API key validation, no input reflection Frontend: - React 19 + TypeScript + Vite chat UI - WebSocket hook with reconnect + exponential backoff - Streaming token display with agent attribution - Interrupt approval/reject UI for write operations - Collapsible tool call viewer Testing: - 87 unit tests, 87% coverage (exceeds 80% requirement) - Ruff lint + format clean Infrastructure: - Docker Compose (PostgreSQL 16 + backend) - pyproject.toml with full dependency management
32 lines
243 B
Plaintext
32 lines
243 B
Plaintext
# Python
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__pycache__/
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*.py[cod]
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*.egg-info/
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dist/
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build/
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.venv/
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venv/
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.env
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.pytest_cache/
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.coverage
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htmlcov/
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.ruff_cache/
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# Node
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node_modules/
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.next/
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frontend/dist/
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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# OS
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.DS_Store
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Thumbs.db
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# Docker
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*.log
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