Update app.py

app.py

@@ -5,82 +5,99 @@ from haystack.dataclasses import ChatMessage
 import time
 import os
 
-def process_files_into_docs(files,progress=gr.Progress()):
-  if isinstance(files, dict):
-    files = [files]
-  if not files:
-    return 'No file uploaded!'
-  
-  preprocessing_pipeline.run({'file_type_router': {'sources': files}})
-
-  return "Database created🤗🤗"
-
-
-def rag(history,question):
-
-  if history is None:
-    history=[]
-  messages = [system_message, user_message]
-  res = conversational_rag.run(
-      data = {'query_rephrase_prompt_builder' : {'query': question},
-              'prompt_builder': {'template': messages, 'query': question},
-              'memory_joiner': {'values': [ChatMessage.from_user(question)]}},
-      include_outputs_from=['llm','query_rephrase_llm'])
-
-  bot_message = res['llm']['replies'][0].content
-
-  streamed_message = ""
-  for token in bot_message.split():
-    streamed_message += f"{token} "
-    yield history + [(question, streamed_message.strip())], " " 
-    time.sleep(0.05)
-
-  history.append((question,bot_message))
-
-  yield history, " "
+def process_files_into_docs(files, progress=gr.Progress()):
+    if isinstance(files, dict):
+        files = [files]
+    
+    if not files:
+        return 'No file uploaded!'
+        
+    preprocessing_pipeline.run({'file_type_router': {'sources': files}})
+    return "Database created🤗🤗"
+
+def rag(history, question):
+    if history is None:
+        history = []
+        
+    messages = [system_message, user_message]
+    res = conversational_rag.run(
+        data = {
+            'query_rephrase_prompt_builder' : {'query': question},
+            'prompt_builder': {'template': messages, 'query': question},
+            'memory_joiner': {'values': [ChatMessage.from_user(question)]}
+        },
+        include_outputs_from=['llm', 'query_rephrase_llm']
+    )
+    
+    bot_message = res['llm']['replies'][0].content
+    streamed_message = ""
+    
+    for token in bot_message.split():
+        streamed_message += f"{token} "
+        yield history + [(question, streamed_message.strip())], " "
+        time.sleep(0.05)
+        
+    history.append((question, bot_message))
+    yield history, " "
 
 EXAMPLE_FILE = "RAG Survey.pdf"
 
-with gr.Blocks(theme=gr.themes.Soft())as demo:
-  
-  gr.HTML("<center><h1>TalkToFiles - Query your documents! 📂📄</h1><center>") 
-  gr.Markdown("""##### This AI chatbot🤖 can help you chat with your documents. Can upload <b>Text(.txt), PDF(.pdf) and Markdown(.md)</b> files.\
-              <b>Please do not upload confidential documents.</b>""")
-  with gr.Row():
-    with gr.Column(scale=86):
-      gr.Markdown("""#### ***Step 1 - Upload Documents and Initialize RAG pipeline***</br>
-                   Can upload Multiple documents""")
-      with gr.Row():
-        file_input = gr.File(label='Upload Files', file_count='multiple',file_types=['.pdf', '.txt', '.md'],interactive=True)
-      with gr.Row():
-        process_files = gr.Button('Create Document store')
-      with gr.Row():
-        result = gr.Textbox(label="Document store", value='Document store not initialized')
-        #Pre-processing Events    
-        process_files.click(fn=process_files_into_docs, inputs=file_input, outputs=result ,show_progress=True)
-      
-      def load_example():
-        return [EXAMPLE_FILE]
-      
-      with gr.Row():
-            gr.Examples(
-                examples=[[EXAMPLE_FILE]],  
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.HTML("<center><h1>TalkToFiles - Query your documents! 📂📄</h1></center>")
+    gr.Markdown("""##### This AI chatbot🤖 can help you chat with your documents. Can upload <b>Text(.txt), PDF(.pdf) and Markdown(.md)</b> files.
+    <b>Please do not upload confidential documents.</b>""")
+    
+    with gr.Row():
+        with gr.Column(scale=86):
+            gr.Markdown("""#### ***Step 1 - Upload Documents and Initialize RAG pipeline***</br> Can upload Multiple documents""")
+            
+            with gr.Row():
+                file_input = gr.File(
+                    label='Upload Files',
+                    file_count='multiple',
+                    file_types=['.pdf', '.txt', '.md'],
+                    interactive=True
+                )
+                
+            with gr.Row():
+                process_files = gr.Button('Create Document store')
+                
+            with gr.Row():
+                result = gr.Textbox(label="Document store", value='Document store not initialized')
+                
+            # Pre-processing Events
+            process_files.click(
+                fn=process_files_into_docs,
                 inputs=file_input,
-                examples_per_page=1,  
-                label="Click to upload an example"
-            ).dataset.click(fn=load_example, inputs=[], outputs=file_input)
-
-
-
-    with gr.Column(scale=200):
-      gr.Markdown("""#### ***Step 2 - Chat with your docs*** """)
-      chatbot = gr.Chatbot(label='ChatBot')
-      user_input = gr.Textbox(label='Enter your query', placeholder='Type here...')
-      
-      with gr.Row():
-        submit_button = gr.Button("Submit")
-        clear_btn = gr.ClearButton([user_input, chatbot], value='Clear')
-        submit_button.click(rag, inputs=[chatbot, user_input], outputs=[chatbot, user_input])
-
-
-demo.launch()
+                outputs=result,
+                show_progress=True
+            )
+            
+            def load_example():
+                return [EXAMPLE_FILE]
+                
+            with gr.Row():
+                gr.Examples(
+                    examples=[[EXAMPLE_FILE]],
+                    inputs=file_input,
+                    examples_per_page=1,
+                    label="Click to upload an example"
+                ).dataset.click(fn=load_example, inputs=[], outputs=file_input)
+                
+        with gr.Column(scale=200):
+            gr.Markdown("""#### ***Step 2 - Chat with your docs*** """)
+            chatbot = gr.Chatbot(label='ChatBot', type="messages")  # <-- Added type="messages" to fix deprecation
+            user_input = gr.Textbox(label='Enter your query', placeholder='Type here...')
+            
+            with gr.Row():
+                submit_button = gr.Button("Submit")
+                clear_btn = gr.ClearButton([user_input, chatbot], value='Clear')
+                
+            submit_button.click(
+                rag,
+                inputs=[chatbot, user_input],
+                outputs=[chatbot, user_input]
+            )
+
+# Use api_name=None to avoid API generation issues
+demo.launch(api_name=None)