Update app.py

app.py

@@ -254,35 +254,60 @@ question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)
 
 rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)
 
-chat_history = ['Moodle','course','un cours']
-import gradio as gr
+chat_history = []
+
+def ask(question, chat_history):
+    # Prepend a phrase to the question to ensure relevance to Moodle
+    prepended_phrase = "using platform Moodle :"
+    modified_question = prepended_phrase + question
 
-#def ask(question, history):
-#    ai_message = rag_chain.invoke({"input": question, "chat_history": chat_history})
-#    chat_history.extend([HumanMessage(content=question), ai_message["answer"]])
-#    return ai_message['answer']
+    
+    # Invoke the chain to get the response
+    ai_message = rag_chain.invoke({"input": modified_question, "chat_history": chat_history})
+    chat_history.append(("user", question))
+    
+    answer = ai_message["answer"]
 
-def ask(question, history):
-    ai_message = rag_chain.invoke({"input": question, "chat_history": chat_history})
-    chat_history.extend([HumanMessage(content=question), ai_message["answer"]])
+    # Prepare document links if available
     document_links = []
-    if 'context' in ai_message and ai_message['context']:
-        for doc in ai_message['context']:
-          if 'url' in doc.metadata:
-              document_links.append(doc.metadata['url'])
-    # Format document links as part of the text output
+    for doc in ai_message.get('context', []):
+        if 'url' in doc.metadata:
+            document_links.append(doc.metadata['url'])
+
+    # Append the question and answer to the chat history (without sources)
+
+    chat_history.append(("assistant", answer))
+
+    # For display purposes, format the chat history without labels
+    display_chat_history = []
+    for role, content in chat_history:
+        if role == "user":
+            display_chat_history.append((None, content))  # User question on the right
+        else:
+            display_chat_history.append((content, None))  # Assistant answer on the left
+
+    # Add sources to the last assistant message for display purposes only
     if document_links:
         document_links_text = "\n".join(document_links)
-        links_text = f"\n\nSources:\n{document_links_text}"
-    else:
-        links_text = "UNTE_ASSISTANTE"
+        display_chat_history[-1] = (display_chat_history[-1][0] + f"\nSources: {document_links_text}", None)
+
+    # Return display history for the UI, and the actual chat history for internal use
+    return display_chat_history, chat_history, ""
+
 
-    return ai_message['answer'] + "\n" + links_text
 
-demo = gr.ChatInterface(fn=ask, title="UNTE ChatBot",theme=gr.themes.Soft())
 
+# Initialize the Gradio interface
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    chatbot = gr.Chatbot()
+    clear_button = gr.Button("Clear")
+    #clear = gr.Button("Clear")
+    question = gr.Textbox(placeholder="Ask me anything about Moodle...")
+    chat_history = gr.State([])
 
+    question.submit(ask, [question, chat_history], [chatbot, chat_history, question])
+    clear_button.click(lambda: ([], [], ""), None, [chatbot, chat_history, question], queue=False)
+    #clear.click(lambda: ("", []), None, [chatbot, chat_history, question], queue=False)
 
-if __name__ == "__main__":
-    gr.close_all()
-    demo.launch(share = False)
+demo.queue()
+demo.launch(share=False)