Update app.py

app.py

@@ -31,10 +31,6 @@ from transformers import GPT2LMHeadModel, GPT2Tokenizer, pipeline
 import nltk
 from nltk.util import ngrams
 
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 api_key = os.getenv('API_KEY')
 
 
@@ -91,25 +87,6 @@ def load_db():
 # Initialize langchain LLM chain
 def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, progress=gr.Progress()):
     progress(0.1, desc="Initializing HF tokenizer...")
-    # HuggingFacePipeline uses local model
-    # Note: it will download model locally...
-    # tokenizer=AutoTokenizer.from_pretrained(llm_model)
-    # progress(0.5, desc="Initializing HF pipeline...")
-    # pipeline=transformers.pipeline(
-    #     "text-generation",
-    #     model=llm_model,
-    #     tokenizer=tokenizer,
-    #     torch_dtype=torch.bfloat16,
-    #     trust_remote_code=True,
-    #     device_map="auto",
-    #     # max_length=1024,
-    #     max_new_tokens=max_tokens,
-    #     do_sample=True,
-    #     top_k=top_k,
-    #     num_return_sequences=1,
-    #     eos_token_id=tokenizer.eos_token_id
-    #     )
-    # llm = HuggingFacePipeline(pipeline=pipeline, model_kwargs={'temperature': temperature})
     
     # HuggingFaceHub uses HF inference endpoints
     progress(0.5, desc="Initializing HF Hub...")
@@ -484,17 +461,6 @@ def demo():
                 clear_btn = gr.ClearButton([msg, chatbot], value="Clear conversation")
             with gr.Row("Metrics"):
                 metrics_output = gr.Textbox(lines=10, label="Evaluation Metrics")
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-        
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-            
-    
 
             
         # Preprocessing events
@@ -510,11 +476,7 @@ def demo():
             queue=False)
 
         # Chatbot events
-
-        
-        
-
-        msg.submit(interact, inputs=[qa_chain, msg, chatbot], outputs=[
+        msg.submit(interact, inputs=[gr.State(),qa_chain, msg, history], outputs=[
         gr.State(), chatbot, history, response_source1, response_source1_page,
         response_source2, response_source2_page, response_source3, response_source3_page,
         None, None, None, metrics_output