Upload app.py

app.py

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+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.format_scratchpad import format_to_openai_function_messages
+from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
+from langchain.utilities.tavily_search import TavilySearchAPIWrapper
+from langchain_community.tools.tavily_search import TavilySearchResults
+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)
+    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)