Update Gradio_UI.py

Gradio_UI.py

@@ -10,77 +10,109 @@ class GradioUI:
         Processes user input, which can include a text query and optionally a PDF file.
         If a PDF is uploaded, it assumes the query is a question about it and calls
         the Document Q&A tool directly. Otherwise, it sends the query to the agent.run() method.
+        Args:
+            query (str): The text query from the user.
+            pdf_file (gr.File, optional): The uploaded PDF file object provided by Gradio. Defaults to None.
+        Returns:
+            str: The response from the agent or tool.
         """
+        # Check if a PDF file is uploaded AND there is a text query (assumed to be the question)
         if pdf_file is not None and query and query.strip():
             print(f"PDF file uploaded: {pdf_file.name}")
             print(f"Query (assumed question for PDF): {query}")
             try:
+                # --- Call the Document Q&A tool directly ---
+                # We assume the document_qna_tool is at index 4 as per your app.py initialization
+                # Gradio's gr.File object has a .name attribute which is the file path
+                # The document_qna_tool expects a file path string.
                 print("Detected PDF upload and query. Calling document_qna_tool...")
-
-                # Dynamically find the tool function by actual function name
-                tool_func = None
-                for t in self.agent.tools:
-                    # Some tools may not have the 'name' attribute; fall back to function __name__
-                    tool_name = getattr(t, "name", None) or getattr(t, "__name__", "")
-                    if tool_name == "document_qna_tool":
-                        tool_func = t
-                        break
-
-                if tool_func is None:
-                    return f"❌ Error: Could not find tool named 'document_qna_tool'. Please check your app.py tool registration."
-
-                # Call the tool with the uploaded PDF path and the user's question
-                response = tool_func(pdf_file.name, query)
-                print("✅ Document Q&A tool finished.")
+                # The tool signature is document_qna_tool(pdf_path: str, question: str)
+                response = self.agent.tools[4](pdf_file.name, query)
+                print("Document Q&A tool finished.")
+                # Optional: Clean up the uploaded file after processing
+                # import os
+                # try:
+                #     if os.path.exists(pdf_file.name):
+                #         os.remove(pdf_file.name)
+                #         print(f"Cleaned up file: {pdf_file.name}")
+                # except Exception as e:
+                #     print(f"Error cleaning up file {pdf_file.name}: {e}")
                 return response
 
+            except IndexError:
+                 return "Error: Document Q&A tool not found at the expected index (4). Check agent tool setup in app.py."
             except Exception as e:
-                print(f"❌ Error during Document Q&A tool execution: {e}")
+                print(f"Error during Document Q&A tool execution: {e}")
+                # Optional: Clean up the uploaded file on error too
+                # import os
+                # try:
+                #     if os.path.exists(pdf_file.name):
+                #         os.remove(pdf_file.name)
+                #         print(f"Cleaned up file on error: {pdf_file.name}")
+                # except Exception as e:
+                #     print(f"Error cleaning up file {pdf_file.name} on error: {e}")
                 return f"An error occurred during Document Q&A: {str(e)}"
 
+        # If no PDF file, or query is empty when file is present, handle as a general agent query
         elif query and query.strip():
             print(f"No PDF file or query is for general task. Processing with agent.run(): {query}")
             try:
+                # --- Call the agent's run method for general queries ---
                 response = self.agent.run(query)
-                print("✅ agent.run finished for general query.")
+                print("Agent.run finished for general query.")
                 return response
             except Exception as e:
-                print(f"❌ Error during agent.run: {e}")
+                print(f"Error during agent.run: {e}")
                 return f"An error occurred while processing your request: {str(e)}"
 
+        # Handle cases where only a PDF is uploaded without a question, or no input at all
         elif pdf_file is not None:
-            return "⚠️ Please enter a question in the textbox to ask about the uploaded PDF."
-
+             # Optional: Clean up the uploaded file if no question was provided
+            # import os
+            # try:
+            #     if os.path.exists(pdf_file.name):
+            #         os.remove(pdf_file.name)
+            #         print(f"Cleaned up file: {pdf_file.name}")
+            # except Exception as e:
+            #     print(f"Error cleaning up file {pdf_file.name}: {e}")
+            return "Please enter a question in the textbox to ask about the uploaded PDF."
         else:
-            return "⚠️ Please enter a request or upload a document for analysis."
+            return "Please enter a request or upload a document for analysis."
+
 
     def launch(self):
         """
         Launches the Gradio user interface with input components stacked vertically.
         """
         with gr.Blocks() as demo:
-            gr.Markdown("# 🧠 Multi-Tool AI Agent with Document Upload")
+            gr.Markdown("# Multi-Tool AI Agent with Document Upload")
             gr.Markdown(
-                "Enter your request and optionally upload a PDF document.\n\n"
-                "- If you upload a PDF, the textbox should contain your question about the document.\n"
-                "- Otherwise, use the textbox for general requests (e.g., weather, time, web search, image generation, etc.)."
+                "Enter your request and optionally upload a PDF document. "
+                "If you upload a PDF, the text box should contain your question about the document. "
+                "Otherwise, use the text box for general requests (weather, search, etc.)."
             )
 
+            # Stack components vertically by default within gr.Blocks
+            # Text input for the user's query or question
             query_input = gr.Textbox(
                 label="Enter your request or question:",
-                placeholder="e.g., What is the weather in London? Summarize this PDF.",
-                lines=3,
+                placeholder="e.g., What is the weather in London? Search for the latest news about AI. What does this document say about [topic]? Summarize the document.",
+                lines=3, # Gives height to the textbox
                 interactive=True
             )
 
+            # File upload component for PDF documents - placed below the textbox
             pdf_upload = gr.File(
                 label="Upload PDF (Optional - for Document Q&A)",
-                file_types=[".pdf"],
-                interactive=True
+                file_types=[".pdf"], # Restrict file types to PDF
+                interactive=True,
+                # The vertical size of this component is somewhat fixed by Gradio
             )
 
+            # Button to trigger the processing function - placed below the file upload
             submit_btn = gr.Button("Submit")
 
+            # Output field below the button
             agent_output = gr.Textbox(
                 label="Agent's Response:",
                 interactive=False,
@@ -88,10 +120,26 @@ class GradioUI:
                 autoscroll=True
             )
 
+            # Link the button click to the process_input function
+            # Pass both query_input (text) and pdf_upload (file) as inputs
             submit_btn.click(
                 fn=self.process_input,
-                inputs=[query_input, pdf_upload],
-                outputs=agent_output
+                inputs=[query_input, pdf_upload], # This list specifies all inputs
+                outputs=agent_output # This specifies the output where the return value goes
             )
 
+            # Optional examples - adjust these based on your tools and whether you have default files
+            # examples = [
+            #     ["What is the time in Berlin?", None], # Example with only text
+            #     ["Generate an image of a robot cooking pasta.", None], # Example with only text
+            #     # Example for document Q&A - requires a default file path accessible by the tool
+            #     # and needs to be in the same directory or accessible path
+            #     # ["Summarize the introduction section", "sample_document.pdf"] # Example with text and file
+            # ]
+            # gr.Examples(examples=examples, inputs=[query_input, pdf_upload]) # Examples take same inputs as function
+
+
+        # Launch the Gradio interface
+        # Setting share=True creates a public URL (useful for demos, be mindful of security/costs)
+        # Setting inline=False opens the app in a new browser tab
         demo.launch(share=False, inline=False)