Update app.py

app.py

@@ -8,17 +8,17 @@ class XylariaChat:
         self.hf_token = os.getenv("HF_TOKEN")
         if not self.hf_token:
             raise ValueError("HuggingFace token not found in environment variables")
-        
+
         # Initialize the inference client
         self.client = InferenceClient(
-            model="Qwen/QwQ-32B-Preview", 
+            model="Qwen/QwQ-32B-Preview",
             api_key=self.hf_token
         )
-        
+
         # Initialize conversation history and persistent memory
         self.conversation_history = []
         self.persistent_memory = {}
-        
+
         # System prompt with more detailed instructions
         self.system_prompt = """You are Xylaria 1.4 Senoa, Made by Sk Md Saad Amin designed to provide helpful, accurate, and engaging support across a wide range of topics. Key guidelines for our interaction include:
 Core Principles:
@@ -64,14 +64,14 @@ Capabilities:
             *self.conversation_history,
             {"role": "user", "content": user_input}
         ]
-        
+
         # Add persistent memory context if available
         if self.persistent_memory:
             memory_context = "Remembered Information:\n" + "\n".join(
                 [f"{k}: {v}" for k, v in self.persistent_memory.items()]
             )
             messages.insert(1, {"role": "system", "content": memory_context})
-        
+
         # Generate response with streaming
         try:
             stream = self.client.chat.completions.create(
@@ -81,9 +81,9 @@ Capabilities:
                 top_p=0.7,
                 stream=True
             )
-            
+
             return stream
-        
+
         except Exception as e:
             return f"Error generating response: {str(e)}"
 
@@ -107,25 +107,25 @@ Capabilities:
         def streaming_response(message, chat_history):
             # Clear input textbox
             response_stream = self.get_response(message)
-            
+
             # If it's an error, return immediately
             if isinstance(response_stream, str):
                 return "", chat_history + [[message, response_stream]]
-            
+
             # Prepare for streaming response
             full_response = ""
             updated_history = chat_history + [[message, ""]]
-            
+
             # Streaming output
             for chunk in response_stream:
                 if chunk.choices[0].delta.content:
                     chunk_content = chunk.choices[0].delta.content
                     full_response += chunk_content
-                    
+
                     # Update the last message in chat history with partial response
                     updated_history[-1][1] = full_response
                     yield "", updated_history
-            
+
             # Update conversation history
             self.conversation_history.append(
                 {"role": "user", "content": message}
@@ -133,25 +133,25 @@ Capabilities:
             self.conversation_history.append(
                 {"role": "assistant", "content": full_response}
             )
-            
+
             # Limit conversation history to prevent token overflow
             if len(self.conversation_history) > 10:
                 self.conversation_history = self.conversation_history[-10:]
-            
+
             return "", updated_history
 
         # Custom CSS for Inter font
         custom_css = """
         @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
-        
+
         body, .gradio-container {
             font-family: 'Inter', sans-serif !important;
         }
-        
+
         .chatbot-container .message {
             font-family: 'Inter', sans-serif !important;
         }
-        
+
         .gradio-container input, 
         .gradio-container textarea, 
         .gradio-container button {
@@ -166,61 +166,71 @@ Capabilities:
                     label="Xylaria 1.4 Senoa",
                     height=500,
                     show_copy_button=True,
-                    value=lambda: gr.load("json", "loadFromLocalStorage()")
+                    # value=lambda: gr.load("json", "loadFromLocalStorage()")  # Remove this line
                 )
-                
+
                 # Input row with improved layout
                 with gr.Row():
                     txt = gr.Textbox(
-                        show_label=False, 
-                        placeholder="Type your message...", 
+                        show_label=False,
+                        placeholder="Type your message...",
                         container=False,
                         scale=4
                     )
                     btn = gr.Button("Send", scale=1)
-                
+
                 # Clear history and memory buttons
                 clear = gr.Button("Clear Conversation")
                 clear_memory = gr.Button("Clear Memory")
-            
+
+            # Load chat history from local storage on page load
+            demo.load(
+                fn=None,  # No Python function needed, just JavaScript
+                _js="() => loadFromLocalStorage()"  # Call your JavaScript function
+            ).then(
+                fn=lambda x: x,
+                inputs=chatbot,  # Use chatbot as input to get the loaded value
+                outputs=chatbot
+            )
+
             # Submit functionality with local storage save
             btn.click(
-                fn=streaming_response, 
-                inputs=[txt, chatbot], 
+                fn=streaming_response,
+                inputs=[txt, chatbot],
                 outputs=[txt, chatbot]
             ).then(
                 fn=None,  # JavaScript callback
                 _js='(chatHistory) => saveToLocalStorage(chatHistory)'
             )
             txt.submit(
-                fn=streaming_response, 
-                inputs=[txt, chatbot], 
+                fn=streaming_response,
+                inputs=[txt, chatbot],
                 outputs=[txt, chatbot]
             ).then(
                 fn=None,  # JavaScript callback
                 _js='(chatHistory) => saveToLocalStorage(chatHistory)'
             )
-            
+
             # Clear conversation history with local storage clear
             clear.click(
-                fn=lambda: [], 
-                inputs=None, 
+                fn=lambda: [],
+                inputs=None,
                 outputs=[chatbot]
             ).then(
                 fn=None,  # JavaScript callback
                 _js='() => clearLocalStorage()'
             )
-            
+
             # Clear persistent memory and reset conversation with local storage clear
             clear_memory.click(
-                fn=lambda: [], 
-                inputs=None, 
+                fn=lambda: [],
+                inputs=None,
                 outputs=[chatbot]
             ).then(
                 fn=None,  # JavaScript callback
                 _js='() => clearLocalStorage()'
             )
-        
+
         return demo
 
 # Launch the interface