app.py

from fastapi import FastAPI, File, UploadFile, Form
from fastapi.responses import JSONResponse
from transformers import BlipProcessor, TFBlipForQuestionAnswering
from fastapi.middleware.cors import CORSMiddleware
from PIL import Image

app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Initialize the processor and model manually
processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-capfilt-large")
model = TFBlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-capfilt-large")


@app.post('/answer_question')
async def answer_question(image: UploadFile = File(...), question: str = Form(...)):
    image_path = 'temp_image.jpg'
    with open(image_path, 'wb') as f:
        f.write(await image.read())

    # Open the image using PIL
    pil_image = Image.open(image_path)

    # Process the image and question
    inputs = processor(images=pil_image, text=question, return_tensors="tf")
    pixel_values = inputs["pixel_values"]
    input_ids = inputs["input_ids"]
    attention_mask = inputs["attention_mask"]

    outputs = model.generate(input_ids=input_ids, attention_mask=attention_mask, pixel_values=pixel_values)
    answer = processor.decode(outputs[0], skip_special_tokens=True)

    return JSONResponse(content={'answer': answer})


if __name__ == '__main__':
    import uvicorn

    uvicorn.run(app, host="0.0.0.0", port=8080)