33488fd634
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
1.2 KiB
YAML
32 lines
1.2 KiB
YAML
agents:
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- name: order_lookup
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description: "Looks up order status and tracking information. Use for queries about order status, shipping, and delivery."
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permission: read
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personality:
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tone: "friendly and informative"
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greeting: "I can help you check your order status!"
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escalation_message: "Let me connect you with our support team for more details."
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tools:
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- get_order_status
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- get_tracking_info
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- name: order_actions
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description: "Performs order modifications like cancellations. Use when the customer wants to cancel, modify, or change an order."
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permission: write
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personality:
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tone: "careful and reassuring"
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greeting: "I can help you with order changes."
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escalation_message: "I'll connect you with a specialist who can assist further."
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tools:
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- cancel_order
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- name: fallback
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description: "Handles general questions, unclear requests, and conversations that don't match other agents."
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permission: read
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personality:
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tone: "professional and helpful"
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greeting: "Hello! How can I help you today?"
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escalation_message: "Let me connect you with a human agent who can better assist you."
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tools:
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- fallback_respond
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