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. 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 metadatajson, inputjson, and outputjson; parse these JSON strings before training or analysis. processing.py provides streaming normalize and decode commands plus importable normalizetrace and decodetrace helpers for arbitrary JSON-compatible contexts. The repository is publicly discoverable, but files require…
Independent publisher
Dark Panda
dakr-pandas
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Published tasks: Text generation.
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