Update app.py

app.py

@@ -2,10 +2,7 @@ import streamlit as st
 from getpass import getpass
 from langchain_google_genai import GoogleGenerativeAI
 from langchain.prompts import PromptTemplate
-
-from typing import List, Tuple
-
-from langchain.agents import AgentExecutor
+from langchain.agents import AgentExecutor, initialize_agent, AgentType
 from langchain.agents.format_scratchpad import format_to_openai_function_messages
 from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
 from langchain.utilities.tavily_search import TavilySearchAPIWrapper
@@ -14,66 +11,57 @@ from langchain_core.messages import AIMessage, HumanMessage
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain.agents import initialize_agent, AgentType
-
-# Create the tool
-search = TavilySearchAPIWrapper(tavily_api_key='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')
-description = """"A search engine optimized for comprehensive, accurate, \
-and trusted results. Useful for when you need to answer questions \
-about current events or about recent information. \
-Input should be a search query. \
-If the user is asking about something that you don't know about, \
-you should probably use this tool to see if that can provide any information."""
-tavily_tool = TavilySearchResults(api_wrapper=search, description=description)
-
-tools = [tavily_tool]
-
-from getpass import getpass
-
-# api_key = getpass()
-
-llm = GoogleGenerativeAI(model="gemini-pro", google_api_key="AIzaSyBNfTHLMjR9vGiomZsW9NFsUTwc2U2NuFA")
-
-prompt = ChatPromptTemplate.from_messages(
-    [
-        MessagesPlaceholder(variable_name="chat_history"),
-        ("user", "{input}"),
-        MessagesPlaceholder(variable_name="agent_scratchpad"),
-    ]
-)
 
-llm_with_tools = llm.bind(functions=tools)
-
-
-
-# Set up Streamlit
-st.title('Fact-Checking Chatbot')
-# Get user input
-user_input = st.text_input("Enter your question")
-
-# If user has entered a question, generate response
-if user_input:
-    response = llm.invoke(user_input)
+def create_tools():
+    search = TavilySearchAPIWrapper(tavily_api_key='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')
+    description = """"A search engine optimized for comprehensive, accurate, \
+    and trusted results. Useful for when you need to answer questions \
+    about current events or about recent information. \
+    Input should be a search query. \
+    If the user is asking about something that you don't know about, \
+    you should probably use this tool to see if that can provide any information."""
+    tavily_tool = TavilySearchResults(api_wrapper=search, description=description)
+    return [tavily_tool]
+
+def create_llm_with_tools(llm, tools):
+    return llm.bind(functions=tools)
+
+def create_agent_chain(tools, llm):
+    return initialize_agent(
+        tools,
+        llm,
+        agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
+        verbose=True,
+    )
+
+def get_user_input():
+    return st.text_input("Enter your question")
+
+def display_response(response):
     st.write(response)
 
-
-
-agent_chain = initialize_agent(
-    [tavily_tool],
-    llm,
-    agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
-    verbose=True,
-)
-prompt = """
-You are a fact-checker. You are asked to verify the following statement based on the information you get from your tool
-and your knowledge. You should provide a response that is based on the information you have and that is as accurate as possible.
-Your response should be True or False. If you are not sure, you should say that you are not sure.
-"""
-
-prompt = st.text_area(prompt)
-
-answer = agent_chain.invoke(
-    prompt + "\n " + user_input,
-)
-
-st.write(answer)
+def main():
+    st.title('Fact-Checking Chatbot')
+    llm = GoogleGenerativeAI(model="gemini-pro", google_api_key="AIzaSyBNfTHLMjR9vGiomZsW9NFsUTwc2U2NuFA")
+    tools = create_tools()
+    llm_with_tools = create_llm_with_tools(llm, tools)
+    agent_chain = create_agent_chain(tools, llm)
+    user_input = get_user_input()
+    if user_input:
+        response = llm.invoke(user_input)
+        display_response(response)
+        prompt = """
+        You are a fact-checker. You are asked to verify the following statement based on the information you get from your tool
+        and your knowledge. You should provide a response that is based on the information you have and that is as accurate as possible.
+        Your response should be True or False. If you are not sure, you should say that you are not sure.
+        """
+        new_prompt = st.text_area(prompt)
+        if new_prompt:
+            prompt = new_prompt
+        answer = agent_chain.invoke(
+            prompt + "\n " + user_input,
+        )
+        display_response(answer)
+
+if __name__ == "__main__":
+    main()