Delete main_api.py

main_api.py

@@ -1,117 +0,0 @@
-# ============================
-# PATCH: main_api.py (FastAPI) – refine_narration via remote instruct when configured
-# ============================
-from __future__ import annotations
-from fastapi import FastAPI, UploadFile, File, Form
-from fastapi.responses import JSONResponse
-from fastapi.middleware.cors import CORSMiddleware
-from pathlib import Path
-import shutil
-import uvicorn
-import json
-
-from video_processing import process_video_pipeline
-from casting_loader import ensure_chroma, build_faces_index, build_voices_index
-from narration_system import NarrationSystem
-from llm_router import load_yaml, LLMRouter
-
-app = FastAPI(title="Veureu Engine API", version="0.2.0")
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-ROOT = Path("/tmp/veureu"); ROOT.mkdir(parents=True, exist_ok=True)
-
-
-@app.get("/")
-def root():
-    return {"ok": True, "service": "veureu-engine"}
-
-
-@app.post("/process_video")
-async def process_video(
-    video_file: UploadFile = File(...),
-    config_path: str = Form("config.yaml"),
-    out_root: str = Form("results"),
-    db_dir: str = Form("chroma_db"),
-):
-    tmp_video = ROOT / video_file.filename
-    with tmp_video.open("wb") as f:
-        shutil.copyfileobj(video_file.file, f)
-
-    result = process_video_pipeline(str(tmp_video), config_path=config_path, out_root=out_root, db_dir=db_dir)
-    return JSONResponse(result)
-
-
-@app.post("/load_casting")
-async def load_casting(
-    faces_dir: str = Form("identities/faces"),
-    voices_dir: str = Form("identities/voices"),
-    db_dir: str = Form("chroma_db"),
-    drop_collections: bool = Form(False),
-):
-    client = ensure_chroma(Path(db_dir))
-    n_faces = build_faces_index(Path(faces_dir), client, collection_name="index_faces", drop=drop_collections)
-    n_voices = build_voices_index(Path(voices_dir), client, collection_name="index_voices", drop=drop_collections)
-    return {"ok": True, "faces": n_faces, "voices": n_voices}
-
-
-@app.post("/refine_narration")
-async def refine_narration(
-    dialogues_srt: str = Form(...),
-    frame_descriptions_json: str = Form("[]"),
-    config_path: str = Form("config.yaml"),
-):
-    cfg = load_yaml(config_path)
-    frames = json.loads(frame_descriptions_json)
-
-    # Si el instruct está configurado como remoto, usamos el router; si no, caemos en NarrationSystem existente
-    model_name = cfg.get("narration", {}).get("model", "salamandra-instruct")
-    use_remote = model_name in (cfg.get("models", {}).get("routing", {}).get("use_remote_for", []))
-
-    if use_remote:
-        router = LLMRouter(cfg)
-        # Implementación simplificada de refinado usando el modelo instruct remoto.
-        # Mantén la lógica de prompts alineada con NarrationSystem si quieres 1:1.
-        system_msg = (
-            "Eres un sistema de audiodescripción que cumple UNE-153010. "
-            "Fusiona diálogos del SRT con descripciones concisas en los huecos, evitando redundancias. "
-            "Devuelve JSON con {narrative_text, srt_text}."
-        )
-        prompt = json.dumps({"dialogues_srt": dialogues_srt, "frames": frames, "rules": cfg.get("narration", {})}, ensure_ascii=False)
-        try:
-            txt = router.instruct(prompt=prompt, system=system_msg, model=model_name)
-            out = {}
-            try:
-                out = json.loads(txt)
-            except Exception:
-                out = {"narrative_text": txt, "srt_text": ""}
-            return {
-                "narrative_text": out.get("narrative_text", ""),
-                "srt_text": out.get("srt_text", ""),
-                "approved": True,
-                "critic_feedback": "",
-            }
-        except Exception as e:
-            # Fallback a NarrationSystem local si falla el remoto
-            ns = NarrationSystem(model_url=None, une_guidelines_path=cfg.get("narration", {}).get("une_guidelines_path", "UNE_153010.txt"))
-            res = ns.run(dialogues_srt, frames)
-            return {"narrative_text": res.narrative_text, "srt_text": res.srt_text, "approved": res.approved, "critic_feedback": res.critic_feedback}
-
-    # Camino local (usa tu NarrationSystem actual)
-    ns = NarrationSystem(model_url=None, une_guidelines_path=cfg.get("narration", {}).get("une_guidelines_path", "UNE_153010.txt"))
-    out = ns.run(dialogues_srt, frames)
-    return {
-        "narrative_text": out.narrative_text,
-        "srt_text": out.srt_text,
-        "approved": out.approved,
-        "critic_feedback": out.critic_feedback,
-    }
-
-
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)