Title: Hi HN! We launched bloop 10 weeks ago (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=35236275" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=35236275</a>) and received a huge amount of feedback (both positive + constructive). We&#x27;ve undertaken a rewrite of the core search framework, which now acts as an LLM agent, significantly improving the number of queries that can be successfully answered.<p>There&#x27;s a bunch of hype surrounding LLM agents, but we&#x27;re positive this is one of the first implementations of an agent that can deliver immediate value for engineers working on existing projects, especially larger ones. We&#x27;ll do a full write up of how the agent works and the tools it can use soon, but we wanted to share our progress, now that we&#x27;ve got a stable release.<p>bloop is a developer assistant that uses GPT-4 to answer questions about your codebase. The agent searches both your local and remote repositories with natural language, regex and filtered queries.<p>Some of the ways engineers use bloop to improve their efficiency when working on large codebases:<p>- Summarise how large files work and how multiple files work together<p>- Understand how to use open source libraries when documentation is lacking<p>- Identify the origin of errors<p>- Ask questions about English-language codebases in other languages<p>- Reduce code duplication by checking for existing functionality<p>- Write new code, taking into account existing codebase context (eg: &quot;write a dockerfile for this project&quot;)<p>bloop runs as a free desktop app on Mac, Windows and Linux: <a href="https:&#x2F;&#x2F;github.com&#x2F;bloopAI&#x2F;bloop&#x2F;releases&#x2F;latest">https:&#x2F;&#x2F;github.com&#x2F;bloopAI&#x2F;bloop&#x2F;releases&#x2F;latest</a>. On desktop, your code is indexed with a MiniLM embedding model and stored locally, meaning at index time your codebase stays private. &#x27;Private&#x27; here means that no code is shared with us or OpenAI at index time, and when a search is made only relevant code snippets are shared to generate the response. (This is more or less the same data usage as Copilot).<p>We also have a paid cloud offering for teams ($45 per user per month). Members of the same organisation can search a shared index hosted by us and will get access to enterprise only features down the line (currently there&#x27;s no feature gap between desktop and cloud).
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