chain...    0.43```text    0.43    ```    ...numexpr.evaluate("0.43")...        Answer: 0.43    > Finished chain.    Answer: 0.43I'm sorry, but I couldn't find any information about Leo DiCaprio's current girlfriend. As for raising her age to the power of 0.43, I'm not sure what her current age is, so I can't provide an answer for that.        > Finished chain.    {'input': "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?",     'output': "I'm sorry, but I couldn't find any information about Leo DiCaprio's current girlfriend. As for raising her age to the power of 0.43, I'm not sure what her current age is, so I can't provide an answer for that."}Using OpenAIFunctionsAgent‚ÄãWe can now use OpenAIFunctionsAgent, which creates this agent under the hoodagent_executor = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)agent_executor.invoke({"input": "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?"})PreviousConversationalNextOpenAI Multi Functions AgentInitialize toolsUsing LCELUsing OpenAIFunctionsAgentCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Certain OpenAI models (like gpt-3.5-turbo-0613 and gpt-4-0613) have been fine-tuned to detect when a function should be called and respond with the inputs that should be passed to the function. In an API call, you can describe functions and have the model intelligently choose to output a JSON object containing arguments to call those functions. The goal of the OpenAI Function APIs is to more reliably return valid and useful function calls than a generic text completion or chat API.
Certain OpenAI models (like gpt-3.5-turbo-0613 and gpt-4-0613) have been fine-tuned to detect when a function should be called and respond with the inputs that should be passed to the function. In an API call, you can describe functions and have the model intelligently choose to output a JSON object containing arguments to call those functions. The goal of the OpenAI Function APIs is to more reliably return valid and useful function calls than a generic text completion or chat API. ->: chain...    0.43```text    0.43    ```    ...numexpr.evaluate("0.43")...        Answer: 0.43    > Finished chain.    Answer: 0.43I'm sorry, but I couldn't find any information about Leo DiCaprio's current girlfriend. As for raising her age to the power of 0.43, I'm not sure what her current age is, so I can't provide an answer for that.        > Finished chain.    {'input': "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?",     'output': "I'm sorry, but I couldn't find any information about Leo DiCaprio's current girlfriend. As for raising her age to the power of 0.43, I'm not sure what her current age is, so I can't provide an answer for that."}Using OpenAIFunctionsAgent‚ÄãWe can now use OpenAIFunctionsAgent, which creates this agent under the hoodagent_executor = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)agent_executor.invoke({"input": "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?"})PreviousConversationalNextOpenAI Multi Functions AgentInitialize toolsUsing LCELUsing OpenAIFunctionsAgentCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.