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-0.3.7.tar.gz (137.7 kB view details)

Uploaded Source

Built Distribution

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

traceshub-0.3.7-py3-none-any.whl (51.8 kB view details)

Uploaded Python 3

File details

Details for the file traceshub-0.3.7.tar.gz.

File metadata

  • Download URL: traceshub-0.3.7.tar.gz
  • Upload date:
  • Size: 137.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.23

File hashes

Hashes for traceshub-0.3.7.tar.gz
Algorithm Hash digest
SHA256 e0d41908f3be46f59c23c2c4d3804f4c74e1518f6ce4e48088d9201419edf541
MD5 6b93ec62230d27465f5ba383b459b817
BLAKE2b-256 3617a367bf4ebf5c37a47054dcf81a1f89f82d05a36d27a387421f4a364879d0

See more details on using hashes here.

File details

Details for the file traceshub-0.3.7-py3-none-any.whl.

File metadata

  • Download URL: traceshub-0.3.7-py3-none-any.whl
  • Upload date:
  • Size: 51.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.23

File hashes

Hashes for traceshub-0.3.7-py3-none-any.whl
Algorithm Hash digest
SHA256 fa9faa6f68958d33e76d3fb7e8b25b9a6b1f53dae2ceac2669a2b893013a63b6
MD5 33548a661d8691aaee81a1f4f0c88ba0
BLAKE2b-256 51082085624458eef3f32b0d55d9d709e83ba764c3a6cf1a7ee72fd84de8794f

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