Update app.py

app.py

@@ -156,6 +156,30 @@ def conversation(qa_chain, message, history):
     new_history = history + [(message, response_answer)]
     return qa_chain, gr.update(value=""), new_history, response_source1, response_source1_page, response_source2, response_source2_page, response_source3, response_source3_page
 
+def initialize_llm_no_doc(llm_model, temperature, max_tokens, top_k, initial_prompt, progress=gr.Progress()):
+    progress(0.1, desc="Initializing HF tokenizer...")
+    
+    progress(0.5, desc="Initializing HF Hub...")
+
+    llm = HuggingFaceEndpoint(
+        repo_id=llm_model,
+        huggingfacehub_api_token=api_token,
+        temperature=temperature,
+        max_new_tokens=max_tokens,
+        top_k=top_k,
+    )
+
+    progress(0.75, desc="Defining buffer memory...")
+    memory = ConversationBufferMemory(
+        memory_key="chat_history",
+        output_key='answer',
+        return_messages=True
+    )
+    conversation_chain = ConversationChain(llm=llm, memory=memory, verbose=False)
+    conversation_chain({"question": initial_prompt})
+    progress(0.9, desc="Done!")
+    return conversation_chain
+
 def conversation_no_doc(llm, message, history):
     formatted_chat_history = format_chat_history(message, history)
     response = llm({"question": message, "chat_history": formatted_chat_history})
@@ -288,6 +312,27 @@ def demo():
             outputs=[chatbot_no_doc, msg_no_doc], 
             queue=False)
 
+        # Initialize LLM without document for conversation
+        with gr.Tab("Initialize LLM for Chatbot without document"):
+            with gr.Row():
+                llm_no_doc_btn = gr.Radio(list_llm_simple, 
+                    label="LLM models", value=list_llm_simple[0], type="index", info="Choose your LLM model for chatbot without document")
+            with gr.Accordion("Advanced options - LLM model", open=False):
+                with gr.Row():
+                    slider_temperature_no_doc = gr.Slider(minimum=0.01, maximum=1.0, value=0.7, step=0.1, label="Temperature", info="Model temperature", interactive=True)
+                with gr.Row():
+                    slider_maxtokens_no_doc = gr.Slider(minimum=224, maximum=4096, value=1024, step=32, label="Max Tokens", info="Model max tokens", interactive=True)
+                with gr.Row():
+                    slider_topk_no_doc = gr.Slider(minimum=1, maximum=10, value=3, step=1, label="top-k samples", info="Model top-k samples", interactive=True)
+            with gr.Row():
+                llm_no_doc_progress = gr.Textbox(value="None", label="LLM initialization for chatbot without document")
+            with gr.Row():
+                llm_no_doc_init_btn = gr.Button("Initialize LLM for Chatbot without document")
+        
+        llm_no_doc_init_btn.click(initialize_llm_no_doc, 
+            inputs=[llm_no_doc_btn, slider_temperature_no_doc, slider_maxtokens_no_doc, slider_topk_no_doc, initial_prompt], 
+            outputs=[llm_no_doc, llm_no_doc_progress])
+
     demo.queue().launch(debug=True, share=True)
 
 if __name__ == "__main__":