0ef7e5475c
- Add Python FastAPI backend with Pydantic validation - Port WhiskClient and MetaAIClient to Python - Create API routers for all endpoints - Add Swagger/ReDoc documentation at /docs - Update Dockerfile for multi-service container - Add lib/api.ts frontend client - Update README for V3
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
"""
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Meta AI Router - Meta AI image and video generation
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"""
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from fastapi import APIRouter, HTTPException
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from models.requests import MetaGenerateRequest, MetaVideoRequest
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from models.responses import MetaGenerateResponse, MetaImageResult, MetaVideoResponse, MetaVideoResult, ErrorResponse
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from services.meta_client import MetaAIClient
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import json
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router = APIRouter(prefix="/meta", tags=["Meta AI"])
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@router.post(
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"/generate",
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response_model=MetaGenerateResponse,
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responses={
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400: {"model": ErrorResponse},
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401: {"model": ErrorResponse},
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422: {"model": ErrorResponse}
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}
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)
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async def meta_generate(request: MetaGenerateRequest):
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"""
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Generate images using Meta AI's Imagine model.
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- **prompt**: Text description of the image to generate
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- **cookies**: Meta AI cookies (optional if using free wrapper)
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- **imageCount**: Number of images to generate (1-4)
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- **aspectRatio**: portrait, landscape, or square
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- **useMetaFreeWrapper**: Use free API wrapper instead of direct Meta AI
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- **metaFreeWrapperUrl**: URL of the free wrapper service
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"""
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# Only check for cookies if NOT using free wrapper
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if not request.useMetaFreeWrapper and not request.cookies:
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raise HTTPException(
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status_code=401,
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detail="Meta AI cookies required. Configure in Settings or use Free Wrapper."
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)
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print(f"[Meta AI Route] Generating images for: \"{request.prompt[:30]}...\" ({request.aspectRatio})")
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# Diagnostic: Check cookie count
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if request.cookies:
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try:
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cookies = request.cookies.strip()
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if cookies.startswith('['):
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parsed = json.loads(cookies)
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count = len(parsed) if isinstance(parsed, list) else 0
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else:
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count = len(cookies.split(';'))
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print(f"[Meta AI Route] Received {count} cookies (Free Wrapper: {request.useMetaFreeWrapper})")
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except:
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print(f"[Meta AI Route] Cookie format: {type(request.cookies)}")
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try:
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client = MetaAIClient(
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cookies=request.cookies or "",
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use_free_wrapper=request.useMetaFreeWrapper,
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free_wrapper_url=request.metaFreeWrapperUrl or "http://localhost:8000"
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)
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results = await client.generate(
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request.prompt,
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request.imageCount,
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request.aspectRatio
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)
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# Download images as base64 for storage
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images = []
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for img in results:
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base64_data = img.data
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if not base64_data and img.url:
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try:
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base64_data = await client.download_as_base64(img.url)
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except Exception as e:
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print(f"[Meta AI Route] Failed to download image: {e}")
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images.append(MetaImageResult(
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data=base64_data or "",
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url=img.url,
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prompt=img.prompt,
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model=img.model,
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aspectRatio="1:1"
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))
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valid_images = [img for img in images if img.data or img.url]
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if not valid_images:
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raise HTTPException(status_code=422, detail="No valid images generated")
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return MetaGenerateResponse(success=True, images=valid_images)
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except Exception as e:
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print(f"[Meta AI Route] Error: {e}")
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raise HTTPException(status_code=422, detail=str(e))
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@router.post(
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"/video",
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response_model=MetaVideoResponse,
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responses={
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400: {"model": ErrorResponse},
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401: {"model": ErrorResponse},
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500: {"model": ErrorResponse}
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}
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)
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async def meta_video(request: MetaVideoRequest):
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"""
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Generate video from text prompt using Meta AI's Kadabra engine.
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- **prompt**: Text description for video generation
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- **cookies**: Meta AI cookies
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- **aspectRatio**: portrait, landscape, or square
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"""
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# Note: Meta AI video generation via GraphQL is complex
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# This is a placeholder - the full implementation would require
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# porting the entire meta/video/route.ts logic
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raise HTTPException(
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status_code=501,
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detail="Meta AI video generation not yet implemented in FastAPI backend"
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)
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