Update app.py

app.py

@@ -1,21 +1,26 @@
-from flask import Flask, request, jsonify, render_template
+from flask import Flask, request, jsonify, render_template, send_from_directory
 import base64
 import re
+import os
+from datetime import datetime
 import requests
 
 # OpenAI API Key
-api_key_1 = "sk-"
-api_key_2 = "Ts4M29N6u2rPPzsrCy2qT3BlbkFJu1z6otKVXaJAbaIvIesj"
-huggingface_api_key_1 = "hf_"
-huggingface_api_key_2 = "RIYBqKlSJQSvLeQuWuTXuohTuhzVMMWBZR"
 
-api_key = api_key_1 + api_key_2
-huggingface_api_key = huggingface_api_key_1 + huggingface_api_key_2
-
-huggingface_url = "https://huggingface.co/spaces/devlim/supernova/upload"
+# OpenAI API Key
+api_key = "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"
 
 app = Flask(__name__)
 
+# Ensure the directory exists
+uploads_dir = 'uploads'
+os.makedirs(uploads_dir, exist_ok=True)
+
+# Function to encode the image
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
 @app.route('/')
 def index():
     return render_template('index.html')
@@ -29,31 +34,25 @@ def save_image():
     image_data = re.sub('^data:image/.+;base64,', '', image_data)
     image_data = base64.b64decode(image_data)
     
-    # Save image to temporary file
-    temp_filename = "temp_image.png"
-    with open(temp_filename, "wb") as temp_file:
-        temp_file.write(image_data)
-    
-    # Upload image to Hugging Face
-    headers = {
-        "Authorization": f"Bearer {huggingface_api_key}"
-    }
-    files = {
-        'file': (temp_filename, open(temp_filename, 'rb'), 'image/png')
-    }
-    response = requests.post(huggingface_url, headers=headers, files=files)
-    
-    if response.status_code != 200:
-        return jsonify({'message': 'Error: 허깅페이스에 이미지를 업로드할 수 없습니다.'}), 500
+    # Create a unique file name
+    timestamp = datetime.now().strftime('%Y%m%d%H%M%S')
+    file_path = os.path.join(uploads_dir, f'captured_image_{timestamp}.png')
     
-    # Get uploaded image URL
-    uploaded_image_url = response.json()['url']
-    
-    # Prepare payload for OpenAI API
+    # Save the image to a file
+    with open(file_path, 'wb') as f:
+        f.write(image_data)
+
+    # Path to your image
+    image_path = file_path
+
+    # Getting the base64 string
+    base64_image = encode_image(image_path)
+
     headers = {
         "Content-Type": "application/json",
         "Authorization": f"Bearer {api_key}"
     }
+
     payload = {
         "model": "gpt-4",
         "messages": [
@@ -67,7 +66,7 @@ def save_image():
                     {
                         "type": "image_url",
                         "image_url": {
-                            "url": uploaded_image_url
+                            "url": f"data:image/jpeg;base64,{base64_image}"
                         }
                     }
                 ]
@@ -83,8 +82,12 @@ def save_image():
         analysis_result = result['choices'][0]['message']['content']
     else:
         analysis_result = "Error: 당류를 찾을 수 없습니다."
-    
-    return jsonify({'message': '분석이 완료되었습니다.', 'analysis_result': analysis_result})
+
+    return jsonify({'message': '분석이 완료되었습니다.', 'image_url': file_path, 'analysis_result': analysis_result})
+
+@app.route('/images/<filename>')
+def get_image(filename):
+    return send_from_directory('.', filename)
 
 if __name__ == '__main__':
     app.run(host='0.0.0.0', port=7860, debug=True)