Open Source · RAG
ragfresh
Detect stale, drifted, and ghost documents in RAG vector indexes
Our verdict
We have not reviewed ragfresh yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About ragfresh
ragfresh is a Python-based observability tool that detects stale, drifted, and ghost documents in RAG vector indexes. It helps identify documents that are outdated, have changed, or are no longer present in the source data, enabling better index hygiene.
Best for
Teams building RAG systems who need to track index health and document lifecycle.
Use cases
- Monitor RAG index freshness
- Audit document drift against source data
- Identify ghost documents that linger in vector stores
Notes
0 stars on GitHub. Last updated 2026-08-22. Licensed MIT.
Pros
- Focused on a specific RAG pain point
- Open source and community-driven
- Python-based, easy to integrate into existing pipelines
Cons
- No stars yet, indicating limited community adoption
- Python-only, may not suit non-Python environments
- Documentation and support are minimal given its early stage
Key facts
What we have checked
- GitHub stars
- 0
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Sources
Where this comes from
- github api via nightly crawl, recovered from git history a4692e327b8f3e9910b4a3a1a5a01e375baca892Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
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