README.md

metadata

pretty_name: pi-embodied Robotics R&D Multimodal Interactions
language:
  - en
  - zh
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*.parquet
dataset_info:
  features:
    - name: id
      dtype: string
    - name: schema_version
      dtype: string
    - name: trajectory_unit
      dtype: string
    - name: source
      dtype: string
    - name: session_id
      dtype: string
    - name: turn_id
      dtype: string
    - name: model
      dtype: string
    - name: messages
      list:
        - name: role
          dtype: string
        - name: content
          list:
            - name: type
              dtype: string
            - name: text
              dtype: string
            - name: path
              dtype: string
            - name: mime_type
              dtype: string
        - name: tool_calls
          list:
            - name: id
              dtype: string
            - name: type
              dtype: string
            - name: name
              dtype: string
            - name: arguments
              dtype: string
        - name: tool_call_id
          dtype: string
        - name: name
          dtype: string
        - name: timestamp
          dtype: string
    - name: messages_json
      dtype: string
    - name: tools_json
      dtype: string
    - name: tools_status
      dtype: string
    - name: images
      list: image
    - name: media_refs
      sequence: string
    - name: media_status
      dtype: string
    - name: outcome
      dtype: string
    - name: repository_url
      dtype: string
    - name: base_commit
      dtype: string
    - name: patch
      dtype: string
    - name: test_result_json
      dtype: string
    - name: provenance_json
      dtype: string
    - name: native_records_json
      dtype: string
    - name: lerobot_status
      dtype: string

pi-embodied Robotics R&D Multimodal Interactions

This public dataset contains 2,396 project-scoped agent turns, including 184 turns with recoverable, published images. It preserves successful, unsuccessful, interrupted and unverified interactions without inventing outcome labels.

Storage

• data/train-*.parquet: normalized interactions with an explicit Arrow schema and Zstandard compression.
• media/<hash-prefix>/<sha256>.<extension>: deduplicated original image bytes, referenced by messages and exposed through the Hugging Face images feature.
• manifest.json: row counts, media recovery status and image checksums.
• data/batches/ and manifests/: immutable historical text archives, excluded from the default dataset configuration.
• load_multimodal.py: loading helpers for interactions, chat messages and execution exports.

Conversation schema

Each row corresponds to a previously selected task turn, not a certified full robot episode. messages stores ordered user/assistant/tool messages, content parts, call IDs, function names, arguments and timestamps. messages_json stores an OpenAI-style conversation with tool_calls.function and image_url content parts. Decode it with json.loads; image URLs resolve to this repository. Visible reasoning summaries are retained when available; encrypted provider content is excluded.

images is a list of Hugging Face Image features; media_refs identifies the corresponding repository-relative files. Original source records, after media extraction and text redaction, are available in native_records_json. provenance_json links every normalized row to its immutable archive identity. The same row IDs and source classification are retained.

tools_json is [] and tools_status is not_recorded where the original collection did not preserve tool definitions. Tool definitions are not reconstructed from argument examples. Repository revisions, patches, test results and task outcomes remain null or unknown when not independently linked to the recorded turn.

Media recovery and handling

Original inline images were recovered from source logs for previously selected turns. Recoverable explicit local image attachments are included. Referenced files that no longer exist remain marked as missing. Remote URLs are not crawled to reconstruct unavailable content. Text is filtered for recognizable credentials and personal identifiers. Visual outputs of known robot execution and observation tools are retained with their source provenance; other images undergo OCR filtering for recognizable sensitive content. OCR is a filter rather than a guarantee. Original source logs and withheld images remain on their private source/staging storage.

The default train split denotes a usable storage split, not a claim that all examples are suitable for supervised training. Outcome-based curation, overlapping-history deduplication, context completion and tool-schema capture remain necessary for individual training recipes. No new redistribution or training license is assigned; original third-party material retains its applicable rights.