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import os |
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import requests |
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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 PIL import Image |
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from io import BytesIO |
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import base64 |
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app = FastAPI() |
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HF_API_URL = "https://api-inference.huggingface.co/models/google/medgemma-27b-it" |
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HF_TOKEN = os.getenv("HF_TOKEN") |
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headers = { |
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"Authorization": f"Bearer {HF_TOKEN}", |
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"Content-Type": "application/json" |
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} |
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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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buffered = BytesIO() |
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image.save(buffered, format="JPEG") |
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img_str = base64.b64encode(buffered.getvalue()).decode() |
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payload = { |
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"inputs": [ |
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{ |
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"role": "user", |
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"content": [ |
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{"type": "image", "image": img_str}, |
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{"type": "text", "text": prompt} |
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] |
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} |
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] |
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} |
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response = requests.post(HF_API_URL, headers=headers, json=payload) |
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if response.status_code != 200: |
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return JSONResponse(status_code=response.status_code, content=response.json()) |
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return {"result": response.json()[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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