Update app.py

app.py

@@ -1,11 +1,24 @@
+import os
 from typing import List, Tuple
+import openai  # Assuming you're using OpenAI's API (make sure to install the OpenAI package)
+from flask import Flask, request, jsonify
 
+# Initialize Flask app
+app = Flask(__name__)
+
+# Set the OpenAI API key
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+# Define a system message
+SYSTEM_MESSAGE = "You are a helpful assistant."
+
+# Function to generate AI response
 def generate_response(
     user_input: str, 
     history: List[Tuple[str, str]], 
-    max_tokens: int, 
-    temperature: float, 
-    top_p: float
+    max_tokens: int = 150, 
+    temperature: float = 0.7, 
+    top_p: float = 1.0
 ) -> str:
     """
     Generates a response from the AI model.
@@ -33,12 +46,13 @@ def generate_response(
 
         # Generate response from the model
         response = ""
-        for msg in client.chat_completion(
-            messages,
+        for msg in openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",  # You can use any model you prefer
+            messages=messages,
             max_tokens=max_tokens,
-            stream=True,
             temperature=temperature,
             top_p=top_p,
+            stream=True
         ):
             # Check if 'choices' is present and non-empty
             if msg and 'choices' in msg and msg['choices']:
@@ -56,3 +70,27 @@ def generate_response(
         # Log the error for debugging purposes
         print(f"An error occurred: {e}")
         return "Error: An unexpected error occurred while processing your request."
+
+# Route to handle user input and generate responses
+@app.route("/chat", methods=["POST"])
+def chat():
+    try:
+        # Get user input from the request
+        user_input = request.json.get("user_input", "")
+        history = request.json.get("history", [])
+        
+        # Generate the AI response
+        response = generate_response(
+            user_input=user_input, 
+            history=history
+        )
+        
+        # Return the response as JSON
+        return jsonify({"response": response})
+
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+if __name__ == "__main__":
+    # Run the app
+    app.run(debug=True, host="0.0.0.0", port=5000)