explaingit

jsingh6/releaseradar

Analysis updated 2026-05-18

0PythonAudience · developerComplexity · 4/5LicenseSetup · moderate

TLDR

An AI tool that lets mobile engineering teams ask plain English questions across GitHub issues, crash reports, and release notes and get cited answers.

Mindmap

mindmap
  root((repo))
    What it does
      Query issues in plain English
      Cited grounded answers
      Severity ranked insights
    Tech stack
      Python FastAPI
      ChromaDB
      React frontend
      Claude Sonnet
    Use cases
      Debug production crashes
      Track regressions
      Extend to Jira Splunk
    Audience
      Mobile engineers
      Developers

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What do people build with it?

USE CASE 1

Ask which crash issues affected a platform and whether they have been fixed.

USE CASE 2

Check if a bug regression appeared in a previous release before filing a new ticket.

USE CASE 3

Get a summarized, severity-ranked view of the most critical open issues.

USE CASE 4

Connect your own Jira, Firebase Crashlytics, or Splunk data to search across your real product issues.

What is it built with?

PythonFastAPIChromaDBReactClaude

How does it compare?

jsingh6/releaseradar0xhassaan/nn-from-scratch3ks/embedoc
Stars00
LanguagePythonPythonPython
Last pushed2023-06-08
MaintenanceDormant
Setup difficultymoderatemoderatehard
Complexity4/54/51/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires your own Anthropic and GitHub API keys plus separate backend and frontend installs.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

ReleaseRadar is a tool built for mobile engineering teams that lets you ask plain English questions about your software's health and get precise, cited answers back. Instead of digging through crash logs in one system, bug tickets in another, and old release notes somewhere else, you type a question and the tool pulls the relevant information together for you. The README describes the core problem this solves: when something breaks in a product used by many people, the information needed to understand what happened is usually scattered across tools that do not talk to each other. Teams end up starting from scratch every time a similar issue comes up. ReleaseRadar aims to fix that by centralizing GitHub Issues, crash events, and release notes, then letting you query them in natural language. Under the hood, it works by taking your GitHub Issues and release notes and turning them into numerical representations called embeddings, using a small open source model. When you ask a question, it combines two kinds of search: one that matches on meaning, and one that matches on exact keywords like version numbers or issue IDs, then merges the results. That combined result is handed to Claude, an AI model from Anthropic, which writes a grounded answer along with a structured summary showing severity, affected versions and platforms, and a recommendation. The frontend, built with React, displays this as a color coded card so a team can scan it quickly. The backend is written in Python with FastAPI, and data currently comes from public GitHub repositories such as Flutter and React Native, used as example datasets. The project is designed to be extended with your own data sources, including Jira, Firebase Crashlytics, and Splunk, using pluggable data connectors. Setting it up requires cloning the repository, installing Python and Node dependencies, and providing your own Anthropic and GitHub API keys. There is a live demo linked in the README. The project is released under the MIT license, meaning it can be freely used, including commercially, as long as the copyright notice is kept.

Copy-paste prompts

Prompt 1
Help me set up ReleaseRadar locally with my own Anthropic and GitHub API keys.
Prompt 2
Show me how to write a new data connector for Jira using the pattern in fetch_data.py.
Prompt 3
Explain how the hybrid BM25 and vector search combination works in this project.
Prompt 4
Help me add rate limiting to the query endpoint.
Prompt 5
Walk me through deploying the FastAPI backend and React frontend together.

Frequently asked questions

What is releaseradar?

An AI tool that lets mobile engineering teams ask plain English questions across GitHub issues, crash reports, and release notes and get cited answers.

What language is releaseradar written in?

Mainly Python. The stack also includes Python, FastAPI, ChromaDB.

What license does releaseradar use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is releaseradar to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is releaseradar for?

Mainly developer.

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