Skip to main content

Capture AI coding sessions and sync them to Hugging Face Datasets — an open SpecStory.

Project description

traceshub

Capture AI coding sessions (Claude Code, Codex CLI, Cursor, Gemini CLI, Aider) into a local SQLite store and sync them to a Hugging Face Dataset.

uv tool install traceshub        # or: pipx install traceshub

traceshub init                       # create ~/.traceshub
traceshub login                      # sign in to Hugging Face
traceshub run claude                 # work normally; the session is captured
traceshub sync                       # push sessions to <user>/traceshub on HF
traceshub search "cuda memory leak"  # semantic search over your history
traceshub replay <session-id>        # replay a session in the terminal

Install real embeddings with uv tool install "traceshub[embeddings]". See ../docs/SCHEMA.md for the dataset layout.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

traceshub-0.3.2.tar.gz (136.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

traceshub-0.3.2-py3-none-any.whl (50.2 kB view details)

Uploaded Python 3

File details

Details for the file traceshub-0.3.2.tar.gz.

File metadata

  • Download URL: traceshub-0.3.2.tar.gz
  • Upload date:
  • Size: 136.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.23

File hashes

Hashes for traceshub-0.3.2.tar.gz
Algorithm Hash digest
SHA256 6e89e008da98cf5ce88e9c1a823fe3493c1f6ea2d82adc56f6965559279534bd
MD5 ce428353fd7baa3919d0abf987ceb7ac
BLAKE2b-256 b992cf288e070c713ae1b6c16d2cf272b379a2d7439b0063f7c8446eeb0c5ac8

See more details on using hashes here.

File details

Details for the file traceshub-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: traceshub-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 50.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.23

File hashes

Hashes for traceshub-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8496a8c314a4053a3a8b1e7925e9d403bb61fe8dabbb14a5a77d63ce0609c4cf
MD5 b88d667a107f7669a6b4e22fe748ecc4
BLAKE2b-256 bfcbff3d090b89ec41e41ca52c08afd31c6c5dbfc8b2bdeca542195e65d3590c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page