Update app.py

app.py

@@ -476,16 +476,42 @@ def display_documents():
         label="Select documents to query"
     )
 
-def create_interface():
-    # Define components outside the main interface
-    model_dropdown = gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[3])
-    temperature_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature")
-    api_calls_slider = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls")
-    use_web_search = gr.Checkbox(label="Use Web Search", value=True)
-    document_selector = gr.CheckboxGroup(label="Select documents to query")
-
-    # Create the main demo layout
-    with gr.Blocks(css=css, theme=gr.themes.Soft(
+def chat_with_parameters(message, history, model, temperature, num_calls, use_web_search, selected_docs):
+    """
+    This function wraps the chatbot functionality with all parameters.
+    It will be used as the main function for gr.Interface.
+    """
+    try:
+        for response in respond(message, history, model, temperature, num_calls, use_web_search, selected_docs):
+            history.append((message, response))
+            yield history
+    except Exception as e:
+        history.append((message, f"An error occurred: {str(e)}"))
+        yield history
+
+# Define the components that were previously in additional_inputs
+model_dropdown = gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[3])
+temperature_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature")
+api_calls_slider = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls")
+use_web_search = gr.Checkbox(label="Use Web Search", value=True)
+document_selector = gr.CheckboxGroup(label="Select documents to query")
+
+# Create the main interface
+demo = gr.Interface(
+    fn=chat_with_parameters,
+    inputs=[
+        gr.Textbox(lines=2, label="Chat Input"),
+        "state",
+        model_dropdown,
+        temperature_slider,
+        api_calls_slider,
+        use_web_search,
+        document_selector
+    ],
+    outputs=gr.Chatbot(),
+    title="AI-powered Web Search and PDF Chat Assistant",
+    description="Chat with your PDFs or use web search to answer questions",
+    theme=gr.themes.Soft(
         primary_hue="orange",
         secondary_hue="amber",
         neutral_hue="gray",
@@ -502,69 +528,45 @@ def create_interface():
         background_fill_secondary_dark="#0c0505",
         color_accent_soft_dark="transparent",
         code_background_fill_dark="#140b0b"
-    )) as demo:
-        gr.Markdown("# AI-powered Web Search and PDF Chat Assistant")
-        gr.Markdown("Chat with your PDFs or use web search to answer questions")
-        
-        with gr.Row():
-            with gr.Column(scale=3):
-                chatbot = gr.Chatbot(height=600)
-                msg = gr.Textbox(label="Enter your message")
-                clear = gr.Button("Clear")
-            
-            with gr.Column(scale=1):
-                model_dropdown
-                temperature_slider
-                api_calls_slider
-                use_web_search
-                document_selector
-        
-        gr.Markdown("## Upload PDF Documents")
-        with gr.Row():
-            file_input = gr.Files(label="Upload your PDF documents", file_types=[".pdf"])
-            parser_dropdown = gr.Dropdown(choices=["pypdf", "llamaparse"], label="Select PDF Parser", value="llamaparse")
-            update_button = gr.Button("Upload Document")
-        
-        update_output = gr.Textbox(label="Update Status")
-        
-        # Update both the output text and the document selector
-        update_button.click(update_vectors, 
-                            inputs=[file_input, parser_dropdown], 
-                            outputs=[update_output, document_selector])
-
-        # Set up the chat functionality
-        msg.submit(chatbot_interface, 
-                   inputs=[msg, chatbot, use_web_search, model_dropdown, temperature_slider, api_calls_slider, document_selector],
-                   outputs=[chatbot])
-        clear.click(lambda: None, None, chatbot, queue=False)
-
-        gr.Markdown(
-        """
-        ## How to use
-        1. Upload PDF documents using the file input at the top.
-        2. Select the PDF parser (pypdf or llamaparse) and click "Upload Document" to update the vector store.
-        3. Select the documents you want to query using the checkboxes.
-        4. Ask questions in the chat interface. 
-        5. Toggle "Use Web Search" to switch between PDF chat and web search.
-        6. Adjust Temperature and Number of API Calls to fine-tune the response generation.
-        7. Use the provided examples or ask your own questions.
-        """
-        )
-
-        # Add examples
-        gr.Examples(
-            examples=[
-                ["Tell me about the contents of the uploaded PDFs."],
-                ["What are the main topics discussed in the documents?"],
-                ["Can you summarize the key points from the PDFs?"]
-            ],
-            inputs=msg,
-        )
+    ),
+    css=css,
+    examples=[
+        ["Tell me about the contents of the uploaded PDFs."],
+        ["What are the main topics discussed in the documents?"],
+        ["Can you summarize the key points from the PDFs?"]
+    ],
+    cache_examples=False,
+    analytics_enabled=False,
+)
 
-    return demo
+# Add file upload functionality
+with demo:
+    gr.Markdown("## Upload PDF Documents")
 
-# Use the function to create the interface
-demo = create_interface()
+    with gr.Row():
+        file_input = gr.Files(label="Upload your PDF documents", file_types=[".pdf"])
+        parser_dropdown = gr.Dropdown(choices=["pypdf", "llamaparse"], label="Select PDF Parser", value="llamaparse")
+        update_button = gr.Button("Upload Document")
+    
+    update_output = gr.Textbox(label="Update Status")
+    
+    # Update both the output text and the document selector
+    update_button.click(update_vectors, 
+                        inputs=[file_input, parser_dropdown], 
+                        outputs=[update_output, document_selector])
+
+    gr.Markdown(
+    """
+    ## How to use
+    1. Upload PDF documents using the file input at the top.
+    2. Select the PDF parser (pypdf or llamaparse) and click "Upload Document" to update the vector store.
+    3. Select the documents you want to query using the checkboxes.
+    4. Ask questions in the chat interface. 
+    5. Toggle "Use Web Search" to switch between PDF chat and web search.
+    6. Adjust Temperature and Number of API Calls to fine-tune the response generation.
+    7. Use the provided examples or ask your own questions.
+    """
+    )
 
 if __name__ == "__main__":
     demo.launch(share=True)