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from fastapi import FastAPI, File, UploadFile, Form |
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from fastapi.responses import JSONResponse |
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from transformers import pipeline |
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from io import BytesIO |
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from PIL import Image |
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app = FastAPI() |
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pipe = pipeline("image-text-to-text", model="google/medgemma-27b-it") |
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@app.get("/") |
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def root(): |
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return {"message": "MedGemma Image-to-Text API running"} |
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@app.post("/analyze/") |
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async def analyze_image(prompt: str = Form(...), file: UploadFile = File(...)): |
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try: |
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image_data = await file.read() |
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image = Image.open(BytesIO(image_data)).convert("RGB") |
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response = pipe([ |
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{ |
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"role": "user", |
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"content": [ |
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{"type": "image", "image": image}, |
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{"type": "text", "text": prompt} |
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] |
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} |
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]) |
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return {"result": response[0]['generated_text']} |
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except Exception as e: |
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return JSONResponse(status_code=500, content={"error": str(e)}) |
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