feat: complete phase 1 -- core framework with chat loop, agents, and React UI
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
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39
docker-compose.yml
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39
docker-compose.yml
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services:
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postgres:
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image: postgres:16
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environment:
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POSTGRES_DB: smart_support
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POSTGRES_USER: smart_support
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POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-dev_password}
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ports:
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- "5432:5432"
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volumes:
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- pgdata:/var/lib/postgresql/data
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U smart_support -d smart_support"]
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interval: 5s
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timeout: 3s
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retries: 5
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backend:
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build:
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context: ./backend
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dockerfile: Dockerfile
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ports:
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- "8000:8000"
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environment:
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DATABASE_URL: postgresql://smart_support:${POSTGRES_PASSWORD:-dev_password}@postgres:5432/smart_support
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LLM_PROVIDER: ${LLM_PROVIDER:-anthropic}
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LLM_MODEL: ${LLM_MODEL:-claude-sonnet-4-6}
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ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-}
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OPENAI_API_KEY: ${OPENAI_API_KEY:-}
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GOOGLE_API_KEY: ${GOOGLE_API_KEY:-}
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depends_on:
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postgres:
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condition: service_healthy
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volumes:
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- ./backend:/app
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command: uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
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volumes:
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pgdata:
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