changes to app

app.py

@@ -4,7 +4,6 @@ import yaml
 import gradio as gr
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
-print(current_dir)
 
 from src.document_retrieval import DocumentRetrieval
 from utils.visual.env_utils import env_input_fields, initialize_env_variables, are_credentials_set, save_credentials
@@ -14,25 +13,20 @@ from utils.vectordb.vector_db import VectorDb
 CONFIG_PATH = os.path.join(current_dir,'config.yaml')
 PERSIST_DIRECTORY = os.path.join(current_dir,f"data/my-vector-db") # changed to current_dir
 
-chat_history = gr.State()
-chat_history = []
-
-def handle_userinput(user_question, conversation):
+def handle_userinput(user_question, conversation, history):
     if user_question:
         try:
+            # Generate response
             response = conversation.invoke({"question": user_question})
-            chat_history.append((user_question, response["answer"]))
 
-            #sources = set([f'{sd.metadata["filename"]}' for sd in response["source_documents"]])
-            #sources_text = "\n".join([f"{i+1}. {source}" for i, source in enumerate(sources)])
-            #state.sources_history.append(sources_text)
+            # Append user message and response to chat history
+            history = history + [(user_question, response["answer"])]
 
-            return chat_history, "" #, state.sources_history
+            return history, "" 
         except Exception as e:
-            return f"An error occurred: {str(e)}", "" #, state.sources_history
+            return f"An error occurred: {str(e)}", "" 
     else:
-        return "An error occurred", ""
-    #return chat_history, "" #, state.sources_history
+        return history, ""
 
 def process_documents(files, document_retrieval, vectorstore, conversation, save_location=None):
     try:
@@ -49,10 +43,6 @@ def process_documents(files, document_retrieval, vectorstore, conversation, save
     except Exception as e:
         return conversation, vectorstore, document_retrieval, f"An error occurred while processing: {str(e)}"
 
-def reset_conversation(chat_history):
-    chat_history = []
-    return chat_history, ""
-
 # Read config file
 with open(CONFIG_PATH, 'r') as yaml_file:
     config = yaml.safe_load(yaml_file)
@@ -91,23 +81,17 @@ with gr.Blocks() as demo:
       
     # Preprocessing events
     process_btn.click(process_documents, inputs=[docs, document_retrieval, vectorstore, conversation], outputs=[conversation, vectorstore, document_retrieval, setup_output], concurrency_limit=10)
-        #process_save_btn.click(process_documents, inputs=[file_upload, save_location], outputs=setup_output)
-        #load_db_btn.click(load_existing_db, inputs=[db_path], outputs=setup_output)
     
     # Step 3: Chat with your data
     gr.Markdown("## 3️⃣ Chat with your document")
     chatbot = gr.Chatbot(label="Chatbot", show_label=True, show_share_button=False, show_copy_button=True, likeable=True)
     msg = gr.Textbox(label="Ask questions about your data", show_label=True, placeholder="Enter your message...")
     clear_btn = gr.Button("Clear chat")
-    #show_sources = gr.Checkbox(label="Show sources", value=True)
     sources_output = gr.Textbox(label="Sources", visible=False)
 
     # Chatbot events
-    #msg.submit(handle_userinput, inputs=[msg], outputs=[chatbot, sources_output])
-    msg.submit(handle_userinput, inputs=[msg, conversation], outputs=[chatbot, msg], queue=False)
+    msg.submit(handle_userinput, inputs=[msg, conversation, chatbot], outputs=[chatbot, msg], queue=False)
     clear_btn.click(lambda: [None, ""], inputs=None, outputs=[chatbot, msg], queue=False)
-    #clear_btn.click(reset_conversation, inputs=[], outputs=[chatbot,msg])
-    #show_sources.change(lambda x: gr.update(visible=x), show_sources, sources_output)
 
 if __name__ == "__main__":
     demo.launch()