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# `langchain_community.agent_toolkits.load_tools`.load_tools

langchain_community.agent_toolkits.load_tools.load_tools(tool_names: List[str], llm: Optional[BaseLanguageModel] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, allow_dangerous_tools: bool = False, **kwargs: Any) → List[BaseTool]

  Load tools based on their name.

  Tools allow agents to interact with various resources and services like APIs, databases, file systems, etc.

  Please scope the permissions of each tools to the minimum required for the application.

  For example, if an application only needs to read from a database, the database tool should not be given write permissions. Moreover consider scoping the permissions to only allow accessing specific tables and impose user-level quota for limiting resource usage.

  Please read the APIs of the individual tools to determine which configuration they support.

  See [Security](https://python.langchain.com/docs/security) for more information.

  Parameters

    - tool_names (List[str]) – name of tools to load.

    - llm (Optional[BaseLanguageModel]) – An optional language model, may be needed to initialize certain tools.

    - callbacks (Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]) – Optional callback manager or list of callback handlers. If not provided, default global callback manager will be used.

    - allow_dangerous_tools (bool) – Optional flag to allow dangerous tools. Tools that contain some level of risk. Please use with caution and read the documentation of these tools to understand the risks and how to mitigate them. Refer to https://python.langchain.com/docs/security for more information. Please note that this list may not be fully exhaustive. It is your responsibility to understand which tools you’re using and the risks associated with them.

    - kwargs (Any) –

  Returns

    List of tools.

  Return type

    List[BaseTool]

# Examples using load_tools

- !pip install -qU langchain-openai

- Answer with ‘Zhu’

- Connect to Comet if no API Key is set

- DataForSEO

- Dataherald

- Debugging

- Each tool wrapps a requests wrapper

- First, define custom callback handler implementations

- Flyte

- Golden

- Google

- LLM Hyperparameters

- LLMonitor

- Needed if you would like to display images in the notebook

- OpenWeatherMap

- SCENARIO 1 - LLM

- SearchApi

- SearxNG Search API

- SerpAPI

- Serper - Google Search API

- Setup and use the ClearML Callback

- Stack Exchange

- Streamlit

- These are sample parameters for Falcon 40B Instruct Deployed from Amazon SageMaker JumpStart

- Used by the agent in this tutorial

- Wolfram Alpha

- argilla.md

- arxiv.md

- awslambda.md

- chatgpt_plugins.md

- eleven_labs_tts.md

- folder_id=’1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5’

- google_finance.md

- graphql.md

- memorize.md

- openweathermap.md

- os.environ[“OPENAI_API_KEY”] = “”

- os.environ[“OPENAI_ORGANIZATION”] = “…”

- prompt_size.md

- scenario 1 - LLM

- sceneXplain.md

- search_tools.md

- setup tools

- token_usage_tracking.md

- use it with langchain {#use-it-with-langchain}

- wandb documentation to configure wandb using env variables