9a8e6ce1eb
AI coaching service (backend/app/services/ai_provider.py): - Two code paths: OpenAI-compatible (6 providers) + Anthropic (Claude) - Streaming SSE responses via httpx async - System prompt built from AGENT_GUIDE + live user context - Graceful error handling for all provider failures - Gemini adapter for Google's generateContent API Chat endpoint (backend/app/routers/ai_chat.py): - POST /api/ai/chat — SSE streaming response - GET /api/ai/status — check configured provider - History capped at 20 messages, content at 4K chars Provider registry expanded to 20 providers: - 9 device integrations (strava, polar, garmin, whoop, oura, coros, fitbit, withings, suunto) - 8 AI providers (openai, openrouter, huggingface, groq, ollama, claude, gemini, custom_ai) - 3 other (usda, nutritionix, telegram) - Categorized: device, ai_provider, nutrition, notifications - COROS: MCP bridge approach (no API integration needed) - Strava: AI/ML warning per their ToS Frontend ChatCoach.jsx to follow in next commit.
64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
"""AI coaching chat endpoint — SSE streaming responses."""
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from __future__ import annotations
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import json
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import logging
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from fastapi import APIRouter, Depends, Request
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from fastapi.responses import StreamingResponse
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.database import get_db
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from app.utils.auth import get_current_user
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from app.models.user import User
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from app.services import ai_provider
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/ai", tags=["AI Coaching"])
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@router.post("/chat")
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async def chat_with_ai(
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request: Request,
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user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Stream an AI coaching response via SSE.
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Body: {"message": "...", "history": [{"role": "user"|"assistant", "content": "..."}]}
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Response: text/event-stream with data chunks.
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"""
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body = await request.json()
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message = body.get("message", "").strip()
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history = body.get("history", [])
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if not message:
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return {"error": "Message cannot be empty"}
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# Validate history format
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clean_history = []
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for msg in history[-20:]: # Cap at last 20 messages
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if isinstance(msg, dict) and msg.get("role") in ("user", "assistant") and msg.get("content"):
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clean_history.append({"role": msg["role"], "content": msg["content"][:4000]})
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async def event_stream():
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async for chunk in ai_provider.chat(user.id, message, clean_history, db):
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yield f"data: {json.dumps({'text': chunk})}\n\n"
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yield "data: [DONE]\n\n"
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return StreamingResponse(event_stream(), media_type="text/event-stream")
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@router.get("/status")
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async def ai_status(
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user: User = Depends(get_current_user),
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db: AsyncSession = Depends(get_db),
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):
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"""Check which AI provider is configured."""
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provider = await ai_provider.get_active_ai_provider(db)
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if provider:
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return {
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"configured": True,
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"provider": provider["name"],
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"model": provider["model"],
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}
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return {"configured": False, "provider": None, "model": None}
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