Refactor SRP : decoupage de main.py (Brain) en routers et du SettingsComponent (web)
Brain : main.py (1496 l.) reduit a l'assemblage (~95 l.) ; un router par responsabilite (generation, chat, tables, imports, notebooks, settings, models), factories DI dans api/deps.py, DTOs chat + mapping anti-corruption separes, auto-pull embeddings deplace en infrastructure. Chemins HTTP inchanges. Web : SettingsComponent (729 l.) recentre sur le formulaire (~330 l.) ; sous-composants standalone updates-section (MAJ + licence Patreon + switch canal) et ollama-model-manager (liste/pull/suppression de modeles). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
184
brain/app/api/routers/imports.py
Normal file
184
brain/app/api/routers/imports.py
Normal file
@@ -0,0 +1,184 @@
|
||||
"""Endpoints d'import/adaptation de PDF (règles, campagne) — REST + flux SSE."""
|
||||
import json
|
||||
import logging
|
||||
from typing import Annotated, AsyncIterator
|
||||
|
||||
from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.api.common import MAX_PDF_BYTES, pdf_upload_error, sse_event
|
||||
from app.api.deps import (
|
||||
get_adapt_campaign_use_case,
|
||||
get_import_campaign_use_case,
|
||||
get_import_rules_use_case,
|
||||
)
|
||||
from app.application.adapt_campaign import AdaptCampaignUseCase
|
||||
from app.application.import_campaign import ImportCampaignUseCase
|
||||
from app.application.import_rules import ImportRulesUseCase
|
||||
from app.domain.models import ChatMessage
|
||||
from app.domain.ports import LLMProviderError, PdfExtractionError
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
class RulesImportResponseDTO(BaseModel):
|
||||
"""Proposition de sections de règles extraites d'un PDF.
|
||||
|
||||
`sections` = {titre → contenu markdown}. C'est une PROPOSITION : le Core
|
||||
et l'UI laissent l'utilisateur réviser/éditer avant toute persistance.
|
||||
`ocr_page_count` permet d'indiquer si le PDF était un scan (OCR utilisé).
|
||||
"""
|
||||
|
||||
sections: dict[str, str]
|
||||
page_count: int
|
||||
ocr_page_count: int
|
||||
|
||||
|
||||
@router.post("/import/rules", response_model=RulesImportResponseDTO)
|
||||
async def import_rules(
|
||||
use_case: Annotated[ImportRulesUseCase, Depends(get_import_rules_use_case)],
|
||||
file: UploadFile = File(...),
|
||||
) -> RulesImportResponseDTO:
|
||||
"""Import d'un PDF de règles → sections markdown structurées (proposition).
|
||||
|
||||
Extrait le texte (couche texte + repli OCR par page pour les scans), découpe,
|
||||
et demande au LLM de répartir les règles en sections thématiques. Ne persiste
|
||||
rien : renvoie la proposition au Core, qui la présente pour révision.
|
||||
"""
|
||||
content = await file.read()
|
||||
if not content:
|
||||
raise HTTPException(status_code=422, detail="Fichier PDF vide.")
|
||||
if len(content) > MAX_PDF_BYTES:
|
||||
raise HTTPException(
|
||||
status_code=413,
|
||||
detail=f"PDF trop volumineux (> {MAX_PDF_BYTES // (1024 * 1024)} Mo).",
|
||||
)
|
||||
|
||||
try:
|
||||
result = await use_case.execute(content)
|
||||
except PdfExtractionError as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
except LLMProviderError as exc:
|
||||
raise HTTPException(status_code=502, detail=str(exc)) from exc
|
||||
|
||||
return RulesImportResponseDTO(
|
||||
sections=result.sections,
|
||||
page_count=result.page_count,
|
||||
ocr_page_count=result.ocr_page_count,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/import/rules/stream")
|
||||
async def import_rules_stream(
|
||||
use_case: Annotated[ImportRulesUseCase, Depends(get_import_rules_use_case)],
|
||||
file: UploadFile = File(...),
|
||||
) -> StreamingResponse:
|
||||
"""Import streamé : émet l'avancement (SSE) puis le résultat final.
|
||||
|
||||
Évènements SSE :
|
||||
- `event: extracting` → data: {} (extraction en cours)
|
||||
- `event: start` → data: {page_count, ocr_page_count, total}
|
||||
- `event: progress` → data: {current, total, new_sections:[...]}
|
||||
- `event: done` → data: {sections, page_count, ocr_page_count}
|
||||
- `event: error` → data: {message}
|
||||
"""
|
||||
content = await file.read()
|
||||
|
||||
async def event_stream() -> AsyncIterator[str]:
|
||||
upload_error = pdf_upload_error(content)
|
||||
if upload_error:
|
||||
yield sse_event("error", {"message": upload_error})
|
||||
return
|
||||
try:
|
||||
async for ev in use_case.stream(content):
|
||||
event_type = ev.pop("type")
|
||||
yield sse_event(event_type, ev)
|
||||
except PdfExtractionError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
except LLMProviderError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
except Exception as exc: # noqa: BLE001 — filet : une erreur inattendue ne doit
|
||||
# PAS casser le flux SSE brutalement (sinon le Core n'a qu'un message générique
|
||||
# sans détail). On la transforme en évènement `error` propre + log avec trace.
|
||||
logger.exception("Import règles : erreur inattendue dans le flux.")
|
||||
yield sse_event("error", {"message": f"Erreur inattendue du Brain : {type(exc).__name__} : {exc}"})
|
||||
|
||||
return StreamingResponse(event_stream(), media_type="text/event-stream")
|
||||
|
||||
|
||||
@router.post("/import/campaign/stream")
|
||||
async def import_campaign_stream(
|
||||
use_case: Annotated[ImportCampaignUseCase, Depends(get_import_campaign_use_case)],
|
||||
file: UploadFile = File(...),
|
||||
) -> StreamingResponse:
|
||||
"""Import streamé d'un PDF de campagne → arbre arc→chapitre→scène (SSE).
|
||||
|
||||
Évènements : `extracting`, `start` {page_count, ocr_page_count, total},
|
||||
`progress` {current, total, arc_count, chapter_count, scene_count},
|
||||
`done` {arcs:[...], page_count, ocr_page_count}, `error` {message}.
|
||||
"""
|
||||
content = await file.read()
|
||||
|
||||
async def event_stream() -> AsyncIterator[str]:
|
||||
upload_error = pdf_upload_error(content)
|
||||
if upload_error:
|
||||
yield sse_event("error", {"message": upload_error})
|
||||
return
|
||||
try:
|
||||
async for ev in use_case.stream(content):
|
||||
event_type = ev.pop("type")
|
||||
yield sse_event(event_type, ev)
|
||||
except PdfExtractionError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
except LLMProviderError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
except Exception as exc: # noqa: BLE001 — voir import règles : on ne laisse pas
|
||||
# une erreur inattendue casser le flux sans détail.
|
||||
logger.exception("Import campagne : erreur inattendue dans le flux.")
|
||||
yield sse_event("error", {"message": f"Erreur inattendue du Brain : {type(exc).__name__} : {exc}"})
|
||||
|
||||
return StreamingResponse(event_stream(), media_type="text/event-stream")
|
||||
|
||||
|
||||
@router.post("/adapt/campaign/stream")
|
||||
async def adapt_campaign_stream(
|
||||
use_case: Annotated[AdaptCampaignUseCase, Depends(get_adapt_campaign_use_case)],
|
||||
file: UploadFile = File(...),
|
||||
brief: str = Form(""),
|
||||
messages: str = Form("[]"),
|
||||
) -> StreamingResponse:
|
||||
"""Adaptation CONVERSATIONNELLE d'un PDF à une campagne (SSE markdown).
|
||||
|
||||
`brief` = description de la campagne (Core). `messages` = JSON de l'échange
|
||||
([{role, content}, …]) ; vide au 1er tour. Évènements : `token`, `done`, `error`.
|
||||
"""
|
||||
content = await file.read()
|
||||
|
||||
try:
|
||||
raw_messages = json.loads(messages) if messages else []
|
||||
except json.JSONDecodeError:
|
||||
raw_messages = []
|
||||
convo = [
|
||||
ChatMessage(role=str(m.get("role", "user")), content=str(m.get("content", "")))
|
||||
for m in raw_messages
|
||||
if isinstance(m, dict) and str(m.get("content", "")).strip()
|
||||
]
|
||||
|
||||
async def event_stream() -> AsyncIterator[str]:
|
||||
upload_error = pdf_upload_error(content)
|
||||
if upload_error:
|
||||
yield sse_event("error", {"message": upload_error})
|
||||
return
|
||||
try:
|
||||
async for token in use_case.stream(content, brief, convo):
|
||||
yield sse_event("token", {"token": token})
|
||||
yield sse_event("done", {})
|
||||
except PdfExtractionError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
except LLMProviderError as exc:
|
||||
yield sse_event("error", {"message": str(exc)})
|
||||
|
||||
return StreamingResponse(event_stream(), media_type="text/event-stream")
|
||||
Reference in New Issue
Block a user