Update app.py
Browse files
app.py
CHANGED
@@ -1,20 +1,20 @@
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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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import
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hf_token = os.environ.get("HF_TOKEN")
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app = FastAPI()
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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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@@ -22,17 +22,28 @@ async def analyze_image(prompt: str = Form(...), file: UploadFile = File(...)):
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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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except Exception as e:
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return JSONResponse(status_code=500, content={"error": str(e)})
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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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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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