Update app.py

app.py

@@ -17,14 +17,12 @@ class ChatbotManager:
         self.temperature = 0.7
         
     def set_api_key(self, api_key: str) -> str:
-        """Set the OpenAI API key"""
         if not api_key.strip():
             return "❌ Please enter a valid API key"
         
         self.current_api_key = api_key.strip()
         openai.api_key = self.current_api_key
         
-        # Test the API key
         try:
             openai.Model.list()
             return "✅ API key validated successfully!"
@@ -32,7 +30,6 @@ class ChatbotManager:
             return f"❌ Invalid API key: {str(e)}"
     
     def update_settings(self, model: str, system_prompt: str, max_tokens: int, temperature: float) -> str:
-        """Update chatbot settings"""
         self.current_model = model
         self.system_prompt = system_prompt
         self.max_tokens = max_tokens
@@ -40,17 +37,14 @@ class ChatbotManager:
         return f"✅ Settings updated: Model={model}, Max Tokens={max_tokens}, Temperature={temperature}"
     
     def preprocess_data(self, data_text: str) -> str:
-        """Preprocess and integrate custom data into the system prompt"""
         if not data_text.strip():
             return "No custom data provided"
         
-        # Reset system prompt to avoid accumulation
         base_prompt = "You are a helpful AI assistant. Respond in a friendly and informative manner."
         self.system_prompt = base_prompt + f"\n\nAdditional Context:\n{data_text}"
         return f"✅ Custom data integrated ({len(data_text)} characters)"
     
     def generate_response(self, user_input: str, history: List[Tuple[str, str]]) -> Tuple[str, List[Tuple[str, str]]]:
-        """Generate response using the selected LLM model"""
         if not self.current_api_key:
             return "❌ Please set your API key first!", history
         
@@ -58,18 +52,14 @@ class ChatbotManager:
             return "Please enter a message.", history
         
         try:
-            # Prepare conversation context
             messages = [{"role": "system", "content": self.system_prompt}]
             
-            # Add conversation history
             for user_msg, assistant_msg in history:
                 messages.append({"role": "user", "content": user_msg})
                 messages.append({"role": "assistant", "content": assistant_msg})
             
-            # Add current user input
             messages.append({"role": "user", "content": user_input})
             
-            # Generate response using OpenAI 0.28 syntax
             response = openai.ChatCompletion.create(
                 model=self.current_model,
                 messages=messages,
@@ -80,8 +70,6 @@ class ChatbotManager:
             )
             
             assistant_response = response.choices[0].message.content.strip()
-            
-            # Update history
             history.append((user_input, assistant_response))
             
             return assistant_response, history
@@ -91,12 +79,10 @@ class ChatbotManager:
             return error_msg, history
     
     def clear_conversation(self) -> Tuple[str, List[Tuple[str, str]]]:
-        """Clear conversation history"""
         self.conversation_history = []
         return "", []
     
     def export_conversation(self, history: List[Tuple[str, str]]) -> str:
-        """Export conversation history to JSON format"""
         if not history:
             return "No conversation to export"
         
@@ -112,9 +98,12 @@ class ChatbotManager:
         filename = f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
         
         try:
-            with open(filename, 'w', encoding='utf-8') as f:
+            # For Hugging Face Spaces, use /tmp directory for writing files
+            os.makedirs("/tmp", exist_ok=True)
+            filepath = os.path.join("/tmp", filename)
+            with open(filepath, 'w', encoding='utf-8') as f:
                 json.dump(export_data, f, indent=2, ensure_ascii=False)
-            return f"✅ Conversation exported to {filename}"
+            return f"✅ Conversation exported to {filename}. Download it from the file explorer."
         except Exception as e:
             return f"❌ Export failed: {str(e)}"
 
@@ -132,12 +121,9 @@ AVAILABLE_MODELS = [
 ]
 
 def create_interface():
-    """Create the Gradio interface"""
-    
     with gr.Blocks(title="LLM-Based Chatbot", theme=gr.themes.Soft()) as demo:
         gr.Markdown("""
         # 🤖 LLM-Based Conversational AI Chatbot
-        
         This chatbot leverages powerful Language Models to provide intelligent conversations.
         Enter your OpenAI API key to get started!
         """)
@@ -149,10 +135,10 @@ def create_interface():
                         label="Conversation",
                         height=400,
                         show_label=True,
-                        avatar_images=("👤", "🤖"),
+                        avatar_images=("https://huggingface.co/spaces/gradio/theme-assets/resolve/main/user.png", 
+                                     "https://huggingface.co/spaces/gradio/theme-assets/resolve/main/assistant.png"),
                         show_copy_button=True,
                         bubble_full_width=False,
-                        show_share_button=True
                     )
                     
                     with gr.Row():
@@ -191,7 +177,7 @@ def create_interface():
                     
                     max_tokens_slider = gr.Slider(
                         minimum=50,
-                        maximum=2000,
+                        maximum=4096,
                         value=150,
                         step=10,
                         label="📏 Max Tokens"
@@ -205,7 +191,6 @@ def create_interface():
                         label="🌡️ Temperature"
                     )
                     
-                    # Live settings display
                     gr.Markdown("### 📊 Current Settings")
                     current_settings = gr.Textbox(
                         value="Model: gpt-3.5-turbo\nTokens: 150\nTemp: 0.7",
@@ -240,7 +225,6 @@ def create_interface():
                 interactive=False
             )
             
-            # Preset system prompts
             gr.Markdown("### 🎭 Preset System Prompts")
             with gr.Row():
                 preset_customer_support = gr.Button("👥 Customer Support", variant="secondary")
@@ -259,7 +243,7 @@ def create_interface():
             
             ### 2. **Configure Settings**
             - **Model**: Choose from available GPT models
-            - **Max Tokens**: Control response length (50-2000)
+            - **Max Tokens**: Control response length (50-4096)
             - **Temperature**: Adjust creativity (0.0 = focused, 1.0 = creative)
             
             ### 3. **Advanced Customization**
@@ -270,7 +254,7 @@ def create_interface():
             ### 4. **Chat Features**
             - Type messages and get intelligent responses
             - Clear conversation history anytime
-            - Export chat history as JSON
+            - Export chat history as JSON (saved in /tmp directory)
             - Regenerate the last response
             - Copy responses using the copy button
             
@@ -281,7 +265,7 @@ def create_interface():
             - **Custom data integration**: Enhance responses with your own data
             - **Export functionality**: Save conversations for later analysis
             - **Real-time validation**: API key and settings verification
-            - **Visual indicators**: User (👤) and AI (🤖) avatars
+            - **Visual indicators**: User and AI avatars
             
             ## 💡 Use Cases
             
@@ -316,7 +300,7 @@ def create_interface():
             if not user_input.strip():
                 return history, ""
             
-            response, updated_history = chatbot.generate_response(user_input, history)
+            response, updated_history = chatbot.generate_response(user_input, history or [])
             return updated_history, ""
         
         def handle_settings_update(model, system_prompt, max_tokens, temperature):
@@ -332,16 +316,14 @@ def create_interface():
             return chatbot.clear_conversation()
         
         def handle_export(history):
-            return chatbot.export_conversation(history)
+            return chatbot.export_conversation(history or [])
         
         def handle_regenerate(history):
             if not history:
-                return history
+                return history or []
             
-            # Get the last user message and regenerate response
             last_user_msg = history[-1][0]
             history_without_last = history[:-1]
-            
             response, updated_history = chatbot.generate_response(last_user_msg, history_without_last)
             return updated_history
         
@@ -409,7 +391,6 @@ def create_interface():
             outputs=[chatbot_interface]
         )
         
-        # Live settings update
         for component in [model_dropdown, max_tokens_slider, temperature_slider]:
             component.change(
                 update_settings_display,
@@ -417,7 +398,6 @@ def create_interface():
                 outputs=[current_settings]
             )
         
-        # Reset and preset buttons
         reset_prompt_btn.click(
             reset_prompt,
             outputs=[system_prompt_input, settings_status]
@@ -445,41 +425,11 @@ def create_interface():
     
     return demo
 
-# Requirements and setup instructions
-def print_setup_instructions():
-    """Print setup instructions"""
-    print("""
-    🤖 LLM-Based Chatbot Setup Instructions
-    =====================================
-    
-    📦 Required Dependencies:
-    pip install openai==0.28.0
-    pip install gradio
-    pip install requests
-    
-    🔑 API Key Setup:
-    1. Visit https://platform.openai.com/
-    2. Create an account and generate an API key
-    3. Enter the API key in the interface
-    
-    🚀 Running the Application:
-    python app.py
-    
-    📂 Files Created:
-    - conversation_YYYYMMDD_HHMMSS.json (exported chats)
-    
-    🌐 Access: http://localhost:7860
-    """)
-
 if __name__ == "__main__":
-    print_setup_instructions()
-    
     # Create and launch the interface
     demo = create_interface()
     
-    # Launch with custom settings
+    # Launch with settings suitable for Hugging Face Spaces
     demo.launch(
-        share=True,
-        debug=True,
-        show_error=True
+        share=True
     )