chroma-core/chroma

Search infrastructure for AI

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Summary Information

Updated 55 minutes ago
Added to GitGenius on November 19th, 2024
Created on October 5th, 2022
Open Issues & Pull Requests: 857 (+0)
GitHub issues: Enabled
Number of forks: 2,505
Total Stargazers: 29,292 (+0)
Total Subscribers: 138 (+0)

Charts & Analytics

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Issue Activity (beta)

Open issues: 354
New in 7 days: 4
Closed in 7 days: 0
Avg open age: 357 days
Stale 30+ days: 322
Stale 90+ days: 277

Recent activity

Opened in 7 days: 3
Closed in 7 days: 0
Comments in 7 days: 3
Events in 7 days: 6

Top labels

  • bug (812)
  • enhancement (313)
  • by-chroma (133)
  • installation trouble (130)
  • good first issue (51)
  • to-discuss (32)
  • Local Chroma (28)
  • cleanup (23)

Detailed Description

Chroma is an open-source data infrastructure platform designed specifically for AI applications, written primarily in Rust. The project describes itself as search infrastructure for AI and provides a core API built around just four functions, making it accessible for developers building AI-powered systems. The platform offers both open-source and commercial hosting options, with Chroma Cloud providing a serverless vector, hybrid, and full-text search service that emphasizes speed, cost-effectiveness, and scalability.

The repository maintains an active development cycle with a structured release cadence, shipping new tagged versions of PyPI and NPM packages every Monday, with hotfixes deployed as needed throughout the week.

This concentrated contributor base suggests a focused development team driving the project's direction.

Chroma is licensed under Apache 2.0, making it freely available for both commercial and non-commercial use. The project actively encourages community participation through multiple channels including a Discord server for real-time discussion, a dedicated contributing guide, and a public roadmap where community members can propose and discuss improvements. The repository maintains a good first issue tag to help new contributors identify suitable entry points into the codebase.

The platform's positioning around vector search, hybrid search, and full-text search capabilities addresses the growing need for efficient data retrieval in AI applications, particularly for retrieval-augmented generation and similar AI patterns. By offering both self-hosted open-source and managed cloud options, Chroma serves different deployment scenarios and organizational requirements, from individual developers experimenting with AI to enterprises requiring managed infrastructure.