108 lines
3.8 KiB
Python
108 lines
3.8 KiB
Python
from fastapi import APIRouter, UploadFile, File, Depends, Query, Body, HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.ConvertModel import ConvertResponse, HealthResponse, ConversionRecord
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from app.services import MarkitdownService as markitdown_service
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from app.database import get_db
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from pydantic import BaseModel
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class CleanupRequest(BaseModel):
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text: str
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prompt: str | None = None
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model: str | None = None
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class CleanupResponse(BaseModel):
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text: str
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class SettingsRequest(BaseModel):
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ollama_base_url: str | None = None
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ollama_model: str = "llava"
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cleanup_model: str | None = None
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class SettingsResponse(BaseModel):
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llm_enabled: bool
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ollama_base_url: str | None
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ollama_model: str
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cleanup_model: str | None = None
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default_prompt: str | None = None
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router = APIRouter()
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@router.get("/health", response_model=HealthResponse)
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def health():
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return HealthResponse(
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status="ok",
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llm_enabled=markitdown_service.LLM_ACTIVE,
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llm_model=markitdown_service.OLLAMA_MODEL if markitdown_service.LLM_ACTIVE else None,
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)
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@router.post("/convert", response_model=ConvertResponse)
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async def convert(
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file: UploadFile = File(...),
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use_llm: bool = Query(default=True, description="Use LLM vision for image understanding"),
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llm_prompt: str | None = Query(default=None, description="Custom prompt for LLM vision"),
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db: AsyncSession = Depends(get_db),
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):
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record = await markitdown_service.convert_file(file, db, use_llm=use_llm, llm_prompt=llm_prompt)
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return record
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@router.get("/models")
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def list_models():
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if not markitdown_service.OLLAMA_BASE_URL:
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return {"models": []}
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try:
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import httpx, re
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base = re.sub(r"/v1/?$", "", markitdown_service.OLLAMA_BASE_URL.rstrip("/"))
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resp = httpx.get(f"{base}/api/tags", timeout=5)
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resp.raise_for_status()
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names = [m["name"] for m in resp.json().get("models", [])]
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return {"models": sorted(names)}
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except Exception as e:
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return {"models": [], "error": str(e)}
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@router.get("/settings", response_model=SettingsResponse)
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def get_settings():
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return SettingsResponse(
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llm_enabled=markitdown_service.LLM_ACTIVE,
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ollama_base_url=markitdown_service.OLLAMA_BASE_URL,
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ollama_model=markitdown_service.OLLAMA_MODEL,
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cleanup_model=markitdown_service.CLEANUP_MODEL or None,
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default_prompt=markitdown_service.DEFAULT_CLEANUP_PROMPT,
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)
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@router.post("/settings", response_model=SettingsResponse)
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def update_settings(req: SettingsRequest):
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markitdown_service._init_llm(req.ollama_base_url or None, req.ollama_model)
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markitdown_service.CLEANUP_MODEL = req.cleanup_model or ""
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return SettingsResponse(
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llm_enabled=markitdown_service.LLM_ACTIVE,
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ollama_base_url=markitdown_service.OLLAMA_BASE_URL,
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ollama_model=markitdown_service.OLLAMA_MODEL,
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cleanup_model=markitdown_service.CLEANUP_MODEL or None,
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default_prompt=markitdown_service.DEFAULT_CLEANUP_PROMPT,
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)
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@router.post("/cleanup", response_model=CleanupResponse)
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async def cleanup(req: CleanupRequest):
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if not markitdown_service.LLM_ACTIVE:
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raise HTTPException(status_code=503, detail="LLM not configured")
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cleaned = markitdown_service.llm_cleanup(req.text, req.prompt, req.model)
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return CleanupResponse(text=cleaned)
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@router.get("/history", response_model=list[ConversionRecord])
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async def history(limit: int = 20, db: AsyncSession = Depends(get_db)):
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records = await markitdown_service.get_history(db, limit)
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return [
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ConversionRecord(
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id=r.id,
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filename=r.filename,
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file_type=r.file_type,
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llm_enabled=r.llm_enabled,
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created_at=str(r.created_at),
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)
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for r in records
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]
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