WebSearchPreviewTool

def __init__(
    self,
    *,
    llm_config: LLMConfig | dict[str, Any],
    search_context_size: Literal["low", "medium", "high"] = "medium",
    user_location: dict[str, str] | None = None,
    instructions: str | None = None,
    text_format: type[BaseModel] | None = None,
):
    """Initialize the WebSearchPreviewTool.

    Args:
        llm_config: The LLM configuration to use. This should be a dictionary
            containing the model name and other parameters.
        search_context_size: The size of the search context. One of `low`, `medium`, or `high`.
            `medium` is the default.
        user_location: The location of the user. This should be a dictionary containing
            the city, country, region, and timezone.
        instructions: Inserts a system (or developer) message as the first item in the model's context.
        text_format: The format of the text to be returned. This should be a subclass of `BaseModel`.
            The default is `None`, which means the text will be returned as a string.
    """
    warnings.warn(
        "WebSearchPreviewTool is deprecated and will be removed in v0.14. "
        "Use autogen.beta.tools.WebSearchTool instead.",
        DeprecationWarning,
        stacklevel=2,
    )
    self.web_search_tool_param = WebSearchToolParam(
        type="web_search_preview",  # type: ignore[typeddict-item]
        search_context_size=search_context_size,
        user_location=UserLocation(**user_location) if user_location else None,  # type: ignore[typeddict-item]
    )
    self.instructions = instructions
    self.text_format = text_format

    if isinstance(llm_config, LLMConfig):
        llm_config = llm_config.model_dump()

    llm_config = copy.deepcopy(llm_config)

    if "config_list" not in llm_config:
        raise ValueError("llm_config must contain 'config_list' key")

    # Find first OpenAI model which starts with "gpt-4"
    self.model = None
    self.api_key = None
    for model in llm_config["config_list"]:
        if model["model"].startswith("gpt-4") and model.get("api_type", "openai") == "openai":
            self.model = model["model"]
            self.api_key = model.get("api_key", os.getenv("OPENAI_API_KEY"))
            break
    if self.model is None:
        raise ValueError(
            "No OpenAI model starting with 'gpt-4' found in llm_config, other models do not support web_search_preview"
        )

    if not self.model.startswith("gpt-4.1") and not self.model.startswith("gpt-4o-search-preview"):
        logging.warning(
            f"We recommend using a model starting with 'gpt-4.1' or 'gpt-4o-search-preview' for web_search_preview, but found {self.model}. "
            "This may result in suboptimal performance."
        )

    def web_search_preview(
        query: Annotated[str, "The search query. Add all relevant context to the query."],
    ) -> str | BaseModel | None:
        client = OpenAI()

        if not self.text_format:
            response = client.responses.create(
                model=self.model,  # type: ignore[arg-type]
                tools=[self.web_search_tool_param],
                input=query,
                instructions=self.instructions,
            )
            text = []
            for output in response.output:
                if output.type == "message":
                    for content in output.content:
                        if content.type == "output_text":
                            text.append(content.text)
            return "\n".join(text)

        else:
            response = client.responses.parse(
                model=self.model,  # type: ignore[arg-type]
                tools=[self.web_search_tool_param],
                input=query,
                instructions=self.instructions,
                text_format=self.text_format,
            )
            return response.output_parsed

    super().__init__(
        name="web_search_preview",
        description="Tool used to perform a web search. It can be used as google search or directly searching a specific website.",
        func_or_tool=web_search_preview,
    )