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RagQL is a local-first Retrieval-Augmented Generation (RAG) system designed for natural language Q&A over your logs and databases. It provides a modular chat-like interface that can index and query local data sources such as log files and SQLite .db database files, using LLM to correlate them and give you a better and more constructive response.

active 2025-05-25 → 2025-06-09 (UTC)

Complete coverage28,521 / 28,521 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-11-15 (UTC)
Events
48
Pushes
23
Pull requests
5
Issues
10
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 16 days from 2025-05-25 to 2025-06-09. Pushes: 23 total, peak 13 in a day. Pull requests: 5 total, peak 3 in a day. Issues: 10 total, peak 5 in a day. Comments: 6 total, peak 2 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
letalboy442356

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.