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
This commit is contained in:
Yaojia Wang
2026-03-30 00:54:21 +02:00
parent e4f08576a9
commit 33488fd634
51 changed files with 4701 additions and 1 deletions

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"""Agent tools registry -- maps tool name strings to actual tool functions."""
from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from langchain_core.tools import BaseTool
from app.agents.fallback import fallback_respond
from app.agents.order_actions import cancel_order
from app.agents.order_lookup import get_order_status, get_tracking_info
_TOOL_MAP: dict[str, BaseTool] = {
"get_order_status": get_order_status,
"get_tracking_info": get_tracking_info,
"cancel_order": cancel_order,
"fallback_respond": fallback_respond,
}
def get_tools_by_names(tool_names: list[str]) -> list[BaseTool]:
"""Resolve tool name strings from YAML config to actual tool objects."""
tools = []
for name in tool_names:
if name not in _TOOL_MAP:
available = ", ".join(sorted(_TOOL_MAP.keys()))
raise ValueError(f"Unknown tool '{name}'. Available tools: {available}")
tools.append(_TOOL_MAP[name])
return tools

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"""Fallback agent tools -- handles unmatched intents."""
from __future__ import annotations
from langchain_core.tools import tool
@tool
def fallback_respond(query: str) -> str:
"""Provide a helpful response when the user's intent doesn't match a specific agent."""
return (
"I'm here to help with order inquiries and actions. "
"Here's what I can do:\n"
"- Check order status (e.g., 'What is the status of order 1042?')\n"
"- Get tracking information (e.g., 'Track order 1042')\n"
"- Cancel an order (e.g., 'Cancel order 1042')\n\n"
"Could you please rephrase your request?"
)

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

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"""Order lookup tools -- read-only operations."""
from __future__ import annotations
from types import MappingProxyType
from langchain_core.tools import tool
MOCK_ORDERS: MappingProxyType[str, dict] = MappingProxyType(
{
"1042": {
"order_id": "1042",
"status": "shipped",
"items": ["Wireless Headphones", "USB-C Cable"],
"total": 89.99,
"placed_at": "2026-03-25",
},
"1043": {
"order_id": "1043",
"status": "processing",
"items": ["Laptop Stand"],
"total": 49.99,
"placed_at": "2026-03-28",
},
"1044": {
"order_id": "1044",
"status": "delivered",
"items": ["Mechanical Keyboard", "Mouse Pad"],
"total": 159.99,
"placed_at": "2026-03-20",
},
}
)
MOCK_TRACKING: MappingProxyType[str, dict] = MappingProxyType(
{
"1042": {
"order_id": "1042",
"carrier": "FedEx",
"tracking_number": "FX-9876543210",
"estimated_delivery": "2026-04-01",
"current_location": "Distribution Center, Chicago IL",
},
"1044": {
"order_id": "1044",
"carrier": "UPS",
"tracking_number": "1Z-5678901234",
"estimated_delivery": "2026-03-22",
"current_location": "Delivered",
},
}
)
@tool
def get_order_status(order_id: str) -> dict:
"""Look up the current status of an order by order ID."""
if order_id in MOCK_ORDERS:
return dict(MOCK_ORDERS[order_id])
return {"error": f"Order {order_id} not found", "order_id": order_id}
@tool
def get_tracking_info(order_id: str) -> dict:
"""Get shipping and tracking information for an order."""
if order_id in MOCK_TRACKING:
return dict(MOCK_TRACKING[order_id])
return {"error": f"No tracking information for order {order_id}", "order_id": order_id}