Update app.py

app.py

@@ -64,74 +64,6 @@ demo = gr.ChatInterface(
 if __name__ == "__main__":
     demo.launch()
 
-    
-
-import gradio as gr
-from langchain.chains import LLMChain
-from langchain.prompts import PromptTemplate
-from langchain_huggingface import HuggingFaceEndpoint
-from langgraph.graph import StateGraph
-
-# Define the LLM models
-llm1 = HuggingFaceEndpoint(model='t5-small')
-llm2 = HuggingFaceEndpoint(model='t5-large')
-
-# Define the agent functions
-def agent1(query):
-    return f"Agent 1: {query}"
-
-def agent2(query):
-    return f"Agent 2: {query}"
-
-# Define the states
-s1 = StateGraph("s1")
-s2 = StateGraph("s2")
-
-# Define the LLM chains
-chain1 = LLMChain(llm=llm1, prompt=PromptTemplate(input_variables=["query"], template="You are in state s1. {{query}}"))
-chain2 = LLMChain(llm=llm2, prompt=PromptTemplate(input_variables=["query"], template="You are in state s2. {{query}}"))
-
-# Define the transition functions
-def transition_s1(query):
-    output = chain1.invoke(input=query)
-    return agent1(output), s2
-
-def transition_s2(query):
-    output = chain2.invoke(input=query)
-    return agent2(output), s1
-
-# Define the respond function
-def respond(input, history, current_state):
-    if current_state == s1:
-        response, next_state = transition_s1(input)
-    elif current_state == s2:
-        response, next_state = transition_s2(input)
-    history.append((input, response))
-    return history, next_state
-
-# Create the Gradio interface
-current_state = s1  # Define current_state here
-
-with gr.Blocks() as demo:
-    gr.Markdown("# Chatbot Interface")
-    chatbot_interface = gr.Chatbot()
-    user_input = gr.Textbox(label="Your Message", placeholder="Type something...")
-    submit_btn = gr.Button("Send")
-
-    # Define the behavior of the submit button
-    def submit_click(input, history):
-        global current_state  # Use global instead of nonlocal
-        history, current_state = respond(input, history, current_state)
-        return history
-    
-    submit_btn.click(
-        fn=submit_click,
-        inputs=[user_input, chatbot_interface],
-        outputs=chatbot_interface
-    )
-
-# Launch the Gradio application
-demo.launch()
 '''
 
 import gradio as gr