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This dataset contains anonymized tool-calling conversations for approved research, evaluation, and model-development use. Access requests are reviewed manually.
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Tool Calling Conversations
An Arena-style dataset of anonymized, multi-turn conversations focused on real-world tool use. It is intended for research, evaluation, and training of models that decide when and how to call tools.
The conversations include:
- Tool selection and no-tool decisions
- Structured tool arguments
- Sequential and parallel tool calls
- Tool results and error recovery
- Multi-step agent workflows
- Final responses after tool execution
Data is organized into date-partitioned Parquet files. Each row contains one complete
conversation trace with its tool calls and results. Flexible nested payloads are
stored losslessly in metadata_json, input_json, and output_json; parse these
JSON strings before training or analysis.
processing.py provides streaming normalize and decode commands plus importable
normalize_trace and decode_trace helpers for arbitrary JSON-compatible contexts.
Access
The repository is publicly discoverable, but files require a manually approved access request.
Access does not grant permission to redistribute the data or attempt to identify users represented in it.
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