Create app.py

app.py

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+import os
+import io
+import base64
+import logging
+from typing import Dict, Any
+
+from dotenv import load_dotenv
+from flask import Flask, request, jsonify
+from huggingface_hub import login
+import requests
+from PIL import Image
+from werkzeug.utils import secure_filename
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Load environment variables
+load_dotenv()
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Hugging Face and Groq API configuration
+HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
+GROQ_API_URL = "https://api.groq.com/openai/v1/chat/completions"
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+
+# Login to Hugging Face
+if HUGGINGFACE_TOKEN:
+    login(HUGGINGFACE_TOKEN)
+else:
+    logger.warning("HUGGINGFACE_TOKEN not set. Some features may be limited.")
+
+# Define allowed file extensions
+ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg'}
+
+def allowed_file(filename: str) -> bool:
+    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+def groq_process(image: Image.Image) -> Dict[str, Any]:
+    """
+    Process the image using Groq's API for medical image analysis.
+    """
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    
+    # Convert image to base64
+    buffered = io.BytesIO()
+    image.save(buffered, format="PNG")
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+    
+    payload = {
+        "model": "mixtral-8x7b-32768",
+        "messages": [
+            {"role": "system", "content": "You are an AI trained to analyze medical images. Provide a detailed analysis of the image, noting any abnormalities or potential areas of concern. Remember to state that this is an AI analysis and should be reviewed by a medical professional."},
+            {"role": "user", "content": f"Analyze this medical image in detail: data:image/png;base64,{img_str}"}
+        ],
+        "max_tokens": 500
+    }
+    
+    try:
+        response = requests.post(GROQ_API_URL, headers=headers, json=payload, timeout=30)
+        response.raise_for_status()
+        return {"success": True, "analysis": response.json()['choices'][0]['message']['content']}
+    except requests.exceptions.RequestException as e:
+        logger.error(f"Error in Groq API request: {str(e)}")
+        return {"success": False, "error": "Error in processing the image"}
+
+def analyze_medical_image(image_file) -> Dict[str, Any]:
+    """
+    Analyze a medical image file.
+    """
+    try:
+        image = Image.open(image_file)
+        analysis_result = groq_process(image)
+        return analysis_result
+    except Exception as e:
+        logger.error(f"Error in image analysis: {str(e)}")
+        return {"success": False, "error": "Error in analyzing the image"}
+
+@app.route('/analyze-medical-image', methods=['POST'])
+def analyze_route():
+    """
+    Route to handle medical image analysis requests.
+    """
+    if 'image' not in request.files:
+        return jsonify({"error": "No image file provided"}), 400
+    
+    file = request.files['image']
+    if file.filename == '':
+        return jsonify({"error": "No selected file"}), 400
+    
+    if file and allowed_file(file.filename):
+        filename = secure_filename(file.filename)
+        analysis_result = analyze_medical_image(file)
+        
+        if analysis_result['success']:
+            return jsonify({
+                "filename": filename,
+                "analysis": analysis_result['analysis'],
+                "disclaimer": "This analysis is provided by an AI system and should be reviewed by a qualified medical professional. It is not a substitute for professional medical advice, diagnosis, or treatment."
+            })
+        else:
+            return jsonify({"error": analysis_result['error']}), 500
+    else:
+        return jsonify({"error": "Invalid file type. Allowed types are png, jpg, jpeg"}), 400
+
+@app.route('/', methods=['GET'])
+def index():
+    return "Medical Image Analysis Tool - For research and educational purposes only. Not for clinical use."
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)