If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else - even if you just want to respond to the user. Do NOT respond with anything except a JSON snippet no matter what!"""agent = {    "input": lambda x: x["input"],    "agent_scratchpad": lambda x: format_log_to_messages(x['intermediate_steps'], template_tool_response=TEMPLATE_TOOL_RESPONSE),    "chat_history": lambda x: x["chat_history"],} | prompt | chat_model_with_stop | JSONAgentOutputParser()from langchain.agents import AgentExecutormemory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, memory=memory)agent_executor.invoke({"input": "hi, i am bob"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Final Answer",        "action_input": "Hello Bob, how can I assist you today?"    }    ```        > Finished chain.    'Hello Bob, how can I assist you today?'agent_executor.invoke({"input": "whats my name?"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Final Answer",        "action_input": "Your name is Bob."    }    ```        > Finished chain.    'Your name is Bob.'agent_executor.invoke({"input": "what are some movies showing 9/21/2023?"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Current Search",        "action_input": "movies showing on 9/21/2023"    }    ```['September 2023 Movies: The Creator ‚Ä¢ Dumb Money ‚Ä¢ Expend4bles ‚Ä¢ The Kill Room ‚Ä¢ The Inventor ‚Ä¢ The Equalizer 3 ‚Ä¢ PAW Patrol: The Mighty Movie, ...']```json    {        "action": "Final Answer",        "action_input": "Some movies that are showing on 9/21/2023 include 'The Creator', 'Dumb Money', 'Expend4bles', 'The
This walkthrough demonstrates how to use an agent optimized for conversation. Other agents are often optimized for using tools to figure out the best response, which is not ideal in a conversational setting where you may want the agent to be able to chat with the user as well.
This walkthrough demonstrates how to use an agent optimized for conversation. Other agents are often optimized for using tools to figure out the best response, which is not ideal in a conversational setting where you may want the agent to be able to chat with the user as well. ->: If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else - even if you just want to respond to the user. Do NOT respond with anything except a JSON snippet no matter what!"""agent = {    "input": lambda x: x["input"],    "agent_scratchpad": lambda x: format_log_to_messages(x['intermediate_steps'], template_tool_response=TEMPLATE_TOOL_RESPONSE),    "chat_history": lambda x: x["chat_history"],} | prompt | chat_model_with_stop | JSONAgentOutputParser()from langchain.agents import AgentExecutormemory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, memory=memory)agent_executor.invoke({"input": "hi, i am bob"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Final Answer",        "action_input": "Hello Bob, how can I assist you today?"    }    ```        > Finished chain.    'Hello Bob, how can I assist you today?'agent_executor.invoke({"input": "whats my name?"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Final Answer",        "action_input": "Your name is Bob."    }    ```        > Finished chain.    'Your name is Bob.'agent_executor.invoke({"input": "what are some movies showing 9/21/2023?"})['output']            > Entering new AgentExecutor chain...    ```json    {        "action": "Current Search",        "action_input": "movies showing on 9/21/2023"    }    ```['September 2023 Movies: The Creator ‚Ä¢ Dumb Money ‚Ä¢ Expend4bles ‚Ä¢ The Kill Room ‚Ä¢ The Inventor ‚Ä¢ The Equalizer 3 ‚Ä¢ PAW Patrol: The Mighty Movie, ...']```json    {        "action": "Final Answer",        "action_input": "Some movies that are showing on 9/21/2023 include 'The Creator', 'Dumb Money', 'Expend4bles', 'The