We've just released GitHub Mode for Devv (https://devv.ai). This feature lets you chat with your GitHub repositories. It's currently in public beta and supports Python repos.
Creating a simple generative search engine is straightforward and can be accomplished over a weekend.
Essential components include:
- A search engine API (such as Bing or Google's)
- Integration of search engine results with a Large Language Model (LLM)
This framework, known as Retrieval-Augmented Generation (RAG), was the foundation for the initial version of Perplexity.
The challenging aspect lies in refining the generation outcomes, which involves more proprietary techniques.
Thank you for your valuable feedback; it's an excellent suggestion! In fact, we've already begun implementing this feature with our initial step being the introduction of GitHub Mode. This new functionality will enable seamless integration with your personal GitHub repositories. We've developed a bespoke indexer tailored to various programming languages to enhance this experience.
Furthermore, we can expand this capability to include documentation and other resources as well. The architecture is designed to be extensible, so all that's needed is the creation of additional indexers to support these materials.
Have you tried Agent Mode? It offers greater intelligence and accuracy compared to Fast Mode.
P.S. Agent Mode is a superior option to Fast Mode. It meticulously examines your questions and assigns an appropriate agent to provide answers, leveraging GPT-4 technology in its operations.
Great, we're on it. We'll be looking into this project and keeping you updated at our changelog hub: https://hub.devv.ai/changelog. As soon as our API goes live, we'll post the announcement there.
Former post: https://news.ycombinator.com/item?id=40299091
We've just released GitHub Mode for Devv (https://devv.ai). This feature lets you chat with your GitHub repositories. It's currently in public beta and supports Python repos.
Here's a brief intro video: https://youtu.be/eYI746AKHQM?si=yOQi0PsOxS4pfpfe
Some examples you can check out:
* mistralai/mistral-finetune: https://devv.ai/search?threadId=dn380pjcbjls * pallets/werkzeug: https://devv.ai/search?threadId=dn38y917snb4 * django/django: https://devv.ai/search?threadId=dn397f4qqghs
Some technical details:
We developed specialized indexers for each programming language to perform in-depth analysis of code repositories. These indexers:
* Understand the structure of the entire repository from a high-level perspective.
* Analyze the relationships between functions and parse Abstract Syntax Trees (AST).
* Break down code into atomic fragments (functions or classes) and use language models to generate descriptive vector-encoded representations.
* Interpret user queries semantically by integrating multiple external data sources including code repositories, documentation, and search engines.
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Let me know if you need any further adjustments!