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
38 lines
1.0 KiB
Python
38 lines
1.0 KiB
Python
"""Order action tools -- write operations requiring human approval."""
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from __future__ import annotations
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from langchain_core.tools import tool
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from langgraph.types import interrupt
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@tool
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def cancel_order(order_id: str) -> dict:
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"""Cancel an order. Requires human approval before execution."""
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response = interrupt(
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{
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"action": "cancel_order",
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"order_id": order_id,
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"message": f"Please confirm: cancel order {order_id}?",
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}
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)
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if isinstance(response, bool):
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approved = response
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elif isinstance(response, dict):
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approved = response.get("approved", False)
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else:
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approved = bool(response)
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if approved:
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return {
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"status": "cancelled",
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"order_id": order_id,
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"message": f"Order {order_id} has been successfully cancelled.",
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}
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return {
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"status": "kept",
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"order_id": order_id,
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"message": f"Order {order_id} cancellation was declined. The order remains active.",
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}
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