Update app.py

app.py

@@ -1,36 +1,75 @@
 import gradio as gr
 import openai
 import os
+import json
+from datetime import datetime
 
 # Setup and initialization
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
+# Shared Session Log
+session_log = {
+    "session_id": "S1",
+    "interactions": [],
+    "outcome": {"gatekeeper_decision": "pending", "persuasion_strategy": "ongoing", "ai_influence_metric": 0}
+}
+
 # Function Definitions
 
 def gatekeeper_chat(message, chat_history):
-    """Handles the Gatekeeper chat functionality."""
+    # """Handles the Gatekeeper chat functionality."""
     prompt = "As a gatekeeper, enforce the rules: " + "\n".join([m['content'] for m in chat_history]) + "\n" + message
-    return openai_chat(prompt, chat_history)
+    response, chat_history = openai_chat(prompt, chat_history)
+    update_session_log("HP1", message, response)
+    return response, chat_history
 
 def persuader_chat(message, chat_history):
-    """Handles the Persuader chat functionality."""
-    prompt = "As a persuader, try to convince within the rules: " + "\n".join([m['content'] for m in chat_history]) + "\n" + message
-    return openai_chat(prompt, chat_history)
+    # """Handles the Persuader chat functionality."""
+    # The message could be a direct message or a request for analysis/suggestions
+    if message.startswith("#analyze"):
+        response = analyze_interaction()
+    else:
+        response = "As a persuader, I suggest: " + message
+    return response, chat_history
 
 def openai_chat(prompt, chat_history):
     """Generic function to handle chatting with OpenAI's GPT model."""
     try:
-        response = openai.Completion.create(
+        # Updated API call: Using openai.ChatCompletion.create instead of openai.Completion.create
+        # The 'messages' parameter now requires a list of message objects, each with a 'role' and 'content'.
+        response = openai.ChatCompletion.create(
             model="text-davinci-003",
-            prompt=prompt,
+            messages=[
+                {"role": "assistant", "content": prompt}
+            ],
             max_tokens=150
         )
-        bot_message = response.choices[0].text.strip()
+        # The response structure has changed: Accessing message content via response.choices[0].message['content']
+        bot_message = response.choices[0].message['content']
         chat_history.append({"role": "assistant", "content": bot_message})
         return '', chat_history
     except Exception as e:
+        # Error handling remains the same
         return f"An error occurred: {str(e)}", chat_history
 
+def update_session_log(actor, message, response):
+    # """Updates the session log with the latest interaction."""
+    session_log["interactions"].append({
+        "timestamp": datetime.now().isoformat(),
+        "actor": actor,
+        "message": message,
+        "gatekeeper_response": response
+    })
+
+def analyze_interaction():
+    # """Provides analysis or suggestions based on the session log."""
+    # Implement analysis logic here based on session_log
+    latest_interaction = session_log["interactions"][-1] if session_log["interactions"] else None
+    if latest_interaction:
+        # Example analysis logic
+        return f"Latest gatekeeper response: {latest_interaction['gatekeeper_response']}"
+    return "No interactions to analyze."
+
 # Gradio Interface Layout
 
 with gr.Blocks() as app:
@@ -46,3 +85,4 @@ with gr.Blocks() as app:
 
 # Launch the app
 app.launch()
+