app.py chnaged

app.py

@@ -15,32 +15,111 @@ class InterviewSession:
             "warnings": []
         }
 
-    def run(self, user_input=None):
+    def run(self, user_input, history):
+        """
+        Main chat function that handles the interview flow
+        """
+        # If this is the very first interaction, start the interview
         if self.state["interview_status"] == 0:
+            print("Starting interview...")
             self.state = graph.invoke(self.state)
-        elif self.state["interview_status"] == 1 and user_input:
+            # Convert state history to gradio format
+            return self._convert_history_to_gradio()
+        
+        # If we have user input, process it
+        if user_input and user_input.strip():
+            print(f"Processing user input: {user_input}")
+            
+            # Add user input to state history
             self.state["interview_history"].append(("user", user_input))
+            
+            # Process the user response through the graph
             self.state = graph.invoke(self.state)
+            
+            # Convert and return the updated history
+            return self._convert_history_to_gradio()
+        
+        # If no input, just return current state
+        return self._convert_history_to_gradio()
 
-        messages = []
-        for role, text in self.state["interview_history"]:
-            messages.append({"role": role, "content": text})
+    def _convert_history_to_gradio(self):
+        """
+        Convert the internal state history to Gradio's expected format
+        """
+        gradio_history = []
+        
+        for role, content in self.state["interview_history"]:
+            if role == "user":
+                gradio_history.append({"role": "user", "content": content})
+            elif role == "ai" or role == "assistant":
+                gradio_history.append({"role": "assistant", "content": content})
+        
+        return gradio_history
 
-        if self.state["interview_status"] == 2:
-            messages.append({"role": "assistant", "content": "✅ Interview complete."})
-
-        return messages, ""
+    def reset_interview(self):
+        """
+        Reset the interview session to start over
+        """
+        print("Resetting interview session...")
+        self.__init__()
+        return []
 
+# Create a single global session instance
 session = InterviewSession()
 
+def chat_fn(message, history):
+    """
+    Chat function for Gradio ChatInterface
+    """
+    return session.run(message, history)
+
+def clear_fn():
+    """
+    Clear function to reset the interview
+    """
+    return session.reset_interview()
+
+# Create the ChatInterface with proper configuration
 demo = gr.ChatInterface(
-    fn=session.run,
+    fn=chat_fn,
     title="🤖 AI-Powered Excel Interviewer (Phi-3 Mini)",
-    chatbot=gr.Chatbot(type="messages", show_copy_button=True),
-    textbox=gr.Textbox(placeholder="Enter your answer here...", label="Your Response"),
+    description="An AI-powered interview system that asks Excel-related questions and provides feedback. The system includes AI-generated response detection to ensure authentic answers.",
+    chatbot=gr.Chatbot(
+        type="messages", 
+        show_copy_button=True,
+        height=600,
+        placeholder="Click below to start your Excel skills interview..."
+    ),
+    textbox=gr.Textbox(
+        placeholder="Type your answer here and press Enter...", 
+        label="Your Response",
+        lines=3
+    ),
     theme="soft",
-    submit_btn="Submit Answer"
+    submit_btn="Submit Answer",
+    examples=[
+        "I'm ready to start the interview",
+        "Let's begin",
+        "Start the assessment"
+    ],
+    cache_examples=False
 )
 
+# Add custom CSS for better styling
+demo.css = """
+    .chat-message {
+        font-size: 16px;
+        line-height: 1.5;
+    }
+    .gradio-container {
+        max-width: 1200px;
+        margin: 0 auto;
+    }
+"""
+
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(
+        share=False,
+        debug=True,
+        show_error=True
+    )