crewAIInc/crewAI · error · ValueError

dataset_type is required either in constructor or method cal

Error message

dataset_type is required either in constructor or method call

What it means

Raised in BrightDataDatasetTool._run when neither the method call nor the constructor supplied dataset_type. Each parameter falls back to the instance attribute first (dataset_type = dataset_type or self.dataset_type); if both are falsy the tool refuses before making any request.

Source

Thrown at lib/crewai-tools/src/crewai_tools/tools/brightdata_tool/brightdata_dataset.py:566

                return await snapshot_response.text()

    def _run(
        self,
        url: str | None = None,
        dataset_type: str | None = None,
        format: str | None = None,
        zipcode: str | None = None,
        additional_params: dict[str, Any] | None = None,
        **kwargs: Any,
    ) -> Any:
        dataset_type = dataset_type or self.dataset_type
        output_format = format or self.format
        url = url or self.url
        zipcode = zipcode or self.zipcode
        additional_params = additional_params or self.additional_params

        if not dataset_type:
            raise ValueError(
                "dataset_type is required either in constructor or method call"
            )
        if not url:
            raise ValueError("url is required either in constructor or method call")

        valid_output_formats = {"json", "ndjson", "jsonl", "csv"}
        if output_format not in valid_output_formats:
            raise ValueError(
                f"Unsupported output format: {output_format}. Must be one of {', '.join(valid_output_formats)}."
            )

        api_key = os.getenv("BRIGHT_DATA_API_KEY")
        if not api_key:
            raise ValueError("BRIGHT_DATA_API_KEY environment variable is required.")

        try:
            return asyncio.run(
                self.get_dataset_data_async(

View on GitHub (pinned to 754d7323be)

Solutions

Pass dataset_type in the constructor: BrightDataDatasetTool(dataset_type='amazon_product', url=...).
Or pass it per call: tool.run(url=..., dataset_type='amazon_product').
Use one of the registry's exact dataset type strings (see filter_dataset_by_id's mapping).

Example fix

# before
tool = BrightDataDatasetTool()
result = tool.run(url='https://www.amazon.com/dp/B0...')

# after
tool = BrightDataDatasetTool(dataset_type='amazon_product', url='https://www.amazon.com/dp/B0...')
result = tool.run()

Defensive patterns

Strategy: validation

Validate before calling

from crewai_tools.tools.brightdata_tool import BrightDataDatasetTool

tool = BrightDataDatasetTool(dataset_type='amazon_product')  # bind at construction
# any later call is safe:
result = tool.run(url='https://www.amazon.com/dp/B0XXXX')

Type guard

def has_dataset_type(call_kwargs: dict, tool: BrightDataDatasetTool) -> bool:
    return bool(call_kwargs.get("dataset_type") or tool.dataset_type)

Try / catch

try:
    result = tool.run(url=url)
except ValueError as e:
    if "dataset_type is required" in str(e):
        result = tool.run(url=url, dataset_type='amazon_product')
    else:
        raise

Prevention

Always construct BrightDataDatasetTool with a dataset_type so per-call omission is safe.
Centralize dataset type names as constants in your codebase.
Fail fast at startup if required tool config is missing.

When it happens

Trigger: Constructing BrightDataDatasetTool() with no dataset_type and calling _run(url=...) alone; passing dataset_type=None or '' at both levels.

Common situations: Expecting the tool to infer dataset type from the URL (it does not), partial constructor configuration copied from examples, agents omitting the parameter.

Related errors

AI-assisted analysis of crewAIInc/crewAI@754d7323be (2026-08-15). Data as JSON: /api/errors/3422eea05ea163de. Report an issue: GitHub.