bruno
2f2a5e9b4a
Introduce an admin portal (React + Nginx), WebSocket routing, and API versioning middleware with `/api/v1/` prefix deprecation. Add master API key authentication, new Prometheus metrics for AI token consumption and active WebSockets, and extend S3 config with a public endpoint URL. Update test paths and fixtures to align with the new routing structure.
116 lines
3.5 KiB
Python
116 lines
3.5 KiB
Python
"""
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Router — AI : résumé d'URL, rédaction de tâches
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Sécurisé : authentification par API Key + scope ai:use + rate limiting.
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"""
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from fastapi import APIRouter, Depends, HTTPException, Request
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from app.dependencies.auth import get_current_client, require_scope
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from app.models.client import APIClient
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from app.schemas import (
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SummarizeRequest, SummarizeResponse,
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DraftTaskRequest, DraftTaskResponse,
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)
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from app.services.scraper import fetch_page_content
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from app.services.ai_vision import summarize_url, draft_task
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from app.config import settings
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from app.middleware import limiter
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from app.metrics import hub_ai_tokens_consumed
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router = APIRouter(prefix="/ai", tags=["Intelligence Artificielle"])
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@router.post(
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"/summarize",
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response_model=SummarizeResponse,
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summary="Résumé AI d'une URL",
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description=(
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"Scrappe le contenu d'une URL et génère un résumé structuré + tags via AI. "
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"Utile pour enrichir les bookmarks Shaarli."
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),
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dependencies=[Depends(require_scope("ai:use"))],
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)
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@limiter.limit("1000/hour")
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async def summarize_link(
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request: Request,
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body: SummarizeRequest,
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client: APIClient = Depends(get_current_client),
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):
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if not settings.AI_ENABLED:
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raise HTTPException(status_code=503, detail="AI désactivée")
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# Scraping
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page = await fetch_page_content(body.url)
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if page.get("error"):
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raise HTTPException(
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status_code=422,
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detail=f"Impossible de récupérer la page : {page['error']}",
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)
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content = " ".join(filter(None, [
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page.get("title"),
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page.get("description"),
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page.get("text"),
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]))
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if not content.strip():
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raise HTTPException(status_code=422, detail="Aucun contenu texte trouvé sur cette page")
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# Résumé AI
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result = await summarize_url(
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url=body.url,
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content=content,
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language=body.language,
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)
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resp = SummarizeResponse(
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url=body.url,
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title=page.get("title"),
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summary=result["summary"],
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tags=result["tags"],
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model=result["model"],
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)
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# Metrics
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if result.get("prompt_tokens") or result.get("output_tokens"):
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total = (result.get("prompt_tokens") or 0) + (result.get("output_tokens") or 0)
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hub_ai_tokens_consumed.labels(client_id=client.id, model=result["model"]).inc(total)
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return resp
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@router.post(
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"/draft-task",
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response_model=DraftTaskResponse,
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summary="Rédaction AI d'une tâche",
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description=(
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"Génère une tâche structurée (titre, description, étapes, priorité) "
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"à partir d'une description libre."
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),
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dependencies=[Depends(require_scope("ai:use"))],
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)
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@limiter.limit("1000/hour")
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async def generate_task(
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request: Request,
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body: DraftTaskRequest,
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client: APIClient = Depends(get_current_client),
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):
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if not settings.AI_ENABLED:
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raise HTTPException(status_code=503, detail="AI désactivée")
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result = await draft_task(
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description=body.description,
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context=body.context,
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language=body.language,
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)
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if not result.get("title"):
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raise HTTPException(status_code=500, detail="Échec de la génération de la tâche")
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# Metrics
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if result.get("prompt_tokens") or result.get("output_tokens"):
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total = (result.get("prompt_tokens") or 0) + (result.get("output_tokens") or 0)
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hub_ai_tokens_consumed.labels(client_id=client.id, model=result.get("model", "unknown")).inc(total)
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return DraftTaskResponse(**result)
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