Upload 3 files

Dockerfile

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+FROM python:3.11-slim-buster
+
+RUN apt update -y && apt install awscli -y
+
+WORKDIR /app
+
+COPY . /app
+
+RUN pip install -r requirements.txt
+ 
+EXPOSE 8000
+ 
+CMD [ "uvicorn", "--host", "0.0.0.0", "main:app" ]

main.py

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+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.responses import JSONResponse
+from typing import Any
+import google.generativeai as genai
+from dotenv import load_dotenv
+import io
+from PIL import Image
+
+app = FastAPI()
+
+def get_gemini_response(image: bytes) -> Any:
+    image_stream = io.BytesIO(image)
+    image = Image.open(image_stream)
+    model = genai.GenerativeModel('gemini-1.5-flash',
+                                  generation_config={"response_mime_type": "application/json"})
+    inputtext = '''System: You are a dietitian, Please check below image and share calorific value of each dish in metric system. Also explain how
+                   much you should eat at one time for healthy diet. Response should be as per below json format for each dish separately.
+                   {"Dish_Name": , 
+                   "calorific_value": , 
+                   "Healthy serving_size": }.
+                   If unable to identify the dish then respond with {"Dish_Name": Unable to identify the dish}.'''
+    response = model.generate_content([inputtext, image])
+    return response.text
+
+@app.post("/analyze-dish")
+async def analyze_dish(image: UploadFile = File(...)):
+    try:
+        image_bytes = await image.read()
+        result = get_gemini_response(image_bytes)
+        return JSONResponse(content=result)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv
+pandas
+json
+fastapi
+uvicorn
+requests
+ipykernel