Update app.py

app.py

@@ -1,4 +1,3 @@
-import streamlit as st
 from flask import Flask, request, jsonify
 from flask_cors import CORS
 from transformers import AutoModelForImageClassification, AutoProcessor
@@ -6,12 +5,8 @@ from PIL import Image
 import io
 import fitz
 import torch
-import threading
-import requests
 import os
 
-HF_SPACE_URL = os.environ.get("HF_SPACE_URL")
-
 app = Flask(__name__)
 CORS(app)
 
@@ -36,9 +31,8 @@ def pdf_to_images_pymupdf(pdf_data):
 @app.route('/classify', methods=['POST', 'OPTIONS'])
 def classify_file():
     if request.method == 'OPTIONS':
-        # Respond to preflight request
         response = jsonify()
-        response.headers.add('Access-Control-Allow-Origin', '*')  # Adjust origin as needed
+        response.headers.add('Access-Control-Allow-Origin', '*')
         response.headers.add('Access-Control-Allow-Methods', 'POST, OPTIONS')
         response.headers.add('Access-Control-Allow-Headers', 'Content-Type')
         return response
@@ -64,7 +58,6 @@ def classify_file():
         elif file_type == 'pdf':
             pdf_data = uploaded_file.read()
             images = pdf_to_images_pymupdf(pdf_data)
-
             if images:
                 image = Image.open(io.BytesIO(images[0])).convert("RGB")
                 inputs = processor(images=image, return_tensors="pt")
@@ -76,41 +69,11 @@ def classify_file():
                 return jsonify({'result': result})
             else:
                 return jsonify({'error': 'PDF conversion failed.'}), 500
-
         else:
             return jsonify({'error': 'Unsupported file type'}), 400
 
     except Exception as e:
         return jsonify({'error': f'An error occurred: {e}'}), 500
 
-def run_flask_app():
-    app.run(host='0.0.0.0', port=5000, debug=False, use_reloader=False)
-
-def main():
-    st.title("RetinApp Backend Tester")
-    st.write("Upload an image or PDF to test the /classify endpoint.")
-
-    uploaded_file = st.file_uploader("Choose a file...", type=["jpg", "jpeg", "png", "gif", "pdf"])
-
-    if uploaded_file is not None:
-        st.write("Uploaded File:", uploaded_file.name)
-
-        if st.button("Classify"):
-            files = {"file": uploaded_file}
-            try:
-                api_url = f"{HF_SPACE_URL}/classify"
-                response = requests.post(api_url, files=files)
-                response.raise_for_status()
-                result = response.json()
-                st.success(f"Classification Result: {result['result']}")
-            except requests.exceptions.RequestException as e:
-                st.error(f"Error during classification: {e}")
-            except Exception as e:
-                st.error(f"Error processing response: {e}")
-
-    flask_thread = threading.Thread(target=run_flask_app)
-    flask_thread.daemon = True
-    flask_thread.start()
-
 if __name__ == '__main__':
-    main()
+    app.run(host='0.0.0.0', port=7860)