text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsAmadeus ToolkitAzure Cognitive Services ToolkitCSV AgentDocument ComparisonGitHubGmail ToolkitJiraJSON AgentMultion ToolkitOffice365 ToolkitOpenAPI agentsNatural Language APIsPandas Dataframe AgentPlayWright Browser ToolkitPowerBI Dataset AgentPython AgentSpark Dataframe AgentSpark SQL AgentSQL Database AgentVectorstore AgentXorbits AgentToolsVector storesGrouped by providerIntegrationsAgent toolkitsPython AgentOn this pagePython AgentThis notebook showcases an agent designed to write and execute python code to answer a question.from langchain.agents.agent_toolkits import create_python_agentfrom langchain.tools.python.tool import PythonREPLToolfrom langchain.python import PythonREPLfrom langchain.llms.openai import OpenAIfrom langchain.agents.agent_types import AgentTypefrom langchain.chat_models import ChatOpenAIUsing ZERO_SHOT_REACT_DESCRIPTIONâ€‹This shows how to initialize the agent using the ZERO_SHOT_REACT_DESCRIPTION agent type. Note that this is an alternative to the above.agent_executor = create_python_agent(    llm=OpenAI(temperature=0, max_tokens=1000),    tool=PythonREPLTool(),    verbose=True,    agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,)Using OpenAI Functionsâ€‹This shows how to initialize the agent using the OPENAI_FUNCTIONS agent type. Note that this is an alternative to the above.agent_executor = create_python_agent(    llm=ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613"),    tool=PythonREPLTool(),    verbose=True,