Рабочий пайплайн: YouTube -> транскрипция -> выжимка -> Postgres

- новый api/: /pipeline/process (yt-dlp, субтитры или Vosk, LLM/экстрактивная
  суммаризация), /videos, /llm; старый код перенесён в api_legacy/
- web/: Flet UI (flet 0.28.3 + flet-web, порт 8550)
- Dockerfile.api: ffmpeg слоем из mwader/static-ffmpeg, pip с кэш-маунтом
- requirements/pyproject: убраны moviepy, imageio-ffmpeg, битый asyncio
- README с инструкцией запуска и загрузкой Vosk-модели

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

api/route/llm.py

@@ -0,0 +1,95 @@
+"""Endpoints for inspecting and testing the external LLM hookup.
+
+The LLM is not hosted here — the user supplies a base URL + model + key.
+"""
+from __future__ import annotations
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from api.lib.llm import (
+    LLMConfig,
+    LLMError,
+    chat_complete,
+    from_settings,
+    list_models,
+    ping,
+)
+
+
+router = APIRouter(prefix="/llm", tags=["llm"])
+
+
+class LLMConfigIn(BaseModel):
+    base_url: str
+    api_key: str = ""
+    # model is optional here so /llm/models can be called before a model is picked
+    model: str = ""
+    timeout: int = 120
+    max_tokens: int = 1000
+    temperature: float = 0.3
+    extra_headers: dict[str, str] = {}
+
+
+class LLMStatus(BaseModel):
+    configured: bool
+    base_url: str | None = None
+    model: str | None = None
+
+
+class ChatIn(BaseModel):
+    config: LLMConfigIn | None = None
+    messages: list[dict]
+
+
+@router.get("/config", response_model=LLMStatus)
+async def get_status():
+    cfg = from_settings()
+    if cfg is None:
+        return LLMStatus(configured=False)
+    return LLMStatus(configured=True, base_url=cfg.base_url, model=cfg.model)
+
+
+@router.post("/test")
+async def test_connection(cfg: LLMConfigIn | None = None):
+    """Send a tiny ping to verify the endpoint accepts our requests."""
+    config = LLMConfig(**cfg.model_dump()) if cfg else from_settings()
+    if config is None:
+        raise HTTPException(
+            status_code=400,
+            detail="No LLM config in body and none configured in environment",
+        )
+    try:
+        reply = ping(config)
+    except LLMError as e:
+        raise HTTPException(status_code=502, detail=str(e))
+    return {"ok": True, "model": config.model, "reply": reply}
+
+
+@router.post("/models")
+async def models(cfg: LLMConfigIn | None = None):
+    """List available models from the configured (or supplied) endpoint."""
+    config = LLMConfig(**cfg.model_dump()) if cfg else from_settings()
+    if config is None:
+        raise HTTPException(
+            status_code=400,
+            detail="No LLM config in body and none configured in environment",
+        )
+    try:
+        items = list_models(config)
+    except LLMError as e:
+        raise HTTPException(status_code=502, detail=str(e))
+    return {"models": items, "count": len(items)}
+
+
+@router.post("/chat")
+async def chat(body: ChatIn):
+    """Pass-through chat endpoint — useful for sanity-testing prompts."""
+    config = LLMConfig(**body.config.model_dump()) if body.config else from_settings()
+    if config is None:
+        raise HTTPException(status_code=400, detail="No LLM config supplied")
+    try:
+        reply = chat_complete(config, body.messages)
+    except LLMError as e:
+        raise HTTPException(status_code=502, detail=str(e))
+    return {"reply": reply, "model": config.model}