Represents built-in tools available from AI/LLM services that can be used within the LangChain framework.

Native tools are functionalities provided directly by language model services (like Google AI, OpenAI) that can be invoked by LLMs to perform specific actions or retrieve information. They are "native" because they're built into the AI service itself, rather than implemented externally.

Each native tool has:

• A unique name that identifies it (e.g., "google_search", "code_interpreter")
• A configuration map that contains tool-specific settings

Google Search Grounding

Starting with Gemini 2.0, Google Search is available as a native tool. This enables the model to decide when to use Google Search to enhance the factuality and recency of responses.

Google Search as a tool enables:

• More accurate and up-to-date answers with grounding sources
• Retrieving information from the web for further analysis
• Finding relevant images, videos, or other media for multimodal reasoning
• Supporting specialized tasks like coding, technical troubleshooting, etc.

Example with Google Search

alias LangChain.Chains.LLMChain
alias LangChain.Message
alias LangChain.NativeTool

model = ChatGoogleAI.new!(%{temperature: 0, stream: false, model: "gemini-2.0-flash"})

{:ok, updated_chain} =
   %{llm: model, verbose: false, stream: false}
   |> LLMChain.new!()
   |> LLMChain.add_message(
     Message.new_user!("What is the current Google stock price?")
   )
   |> LLMChain.add_tools(NativeTool.new!(%{name: "google_search", configuration: %{}}))
   |> LLMChain.run()copy