swirl-search VS khoj

Understanding an Open Source Search Platform: Swirl

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Swirl is an open-source Python project. Contributing to Swirl can help you gain production-level knowledge of Python and improve your skills.

Note: This is not how you write a search engine. There's a lot more stuff that goes into it. If you want to know more, check this GitHub Repository:github.com/swirlai/swirl-search

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Swirl is an open-source search engine which is built using Python and Django. Things which makes Swirl more special is that individual developers and organizations can use Swirl without paying single penny and even customize the search results by connecting to Database (E.g. SQL, NoSQL), Public Data Services (E.g. Google) and Enterprise Sources (E.g. Jira). GitHub Link: https://github.com/swirlai/swirl-search

Hello Devs, The team at Swirl has created this amazing guide which contains all the relevant information for anyone who wants to extend Swirl by adding SearchProviders, Connectors, and Processors.

Swirl is an open-source search platform software that simultaneously searches multiple content sources and returns AI-ranked results. You can also use Generative AI Models to get answers based on your data. It’s written in Python.

There are already several RAG chat open source solutions available. Two that immediately come to mind are:

Danswer

https://github.com/danswer-ai/danswer

Khoj

https://github.com/khoj-ai/khoj

I'm a fan of Khoj. Been using it for months. https://github.com/khoj-ai/khoj

https://github.com/khoj-ai/khoj

This is the easiest I found, on here too.

Thanks for the feedback. Does your machine have a GPU? 32GB CPU RAM should be enough but GPU speeds up response time.

We have fixes for the seg fault[1] and improvement to the query speed[2] that should be released by end of day today[3].

Update khoj to version 0.10.1 with pip install --upgrade khoj-assistant to see if that improves your experience.

The number of documents/pages/entries doesn't scale memory utilization as quickly and doesn't affect the search, chat response time as much

[1]: The seg fault would occur when folks sent multiple chat queries at the same time. A lock and some UX improvements fixed that

[2]: The query time improvements are done by increasing batch size, to trade-off increased memory utilization for more speed

[3]: The relevant pull request for reference: https://github.com/khoj-ai/khoj/pull/393

We recently integrated Llama 2 into Khoj. I wanted to share a short real-world evaluation of using Llama 2 for the chat with docs use-cases and hear which models have worked best for you all. The standard benchmarks (ARC, HellaSwag, MMLU etc.) are not tuned for evaluating this

Self-host your Notion assistant using the instructions here. You'll need Python >= 3.8 to get started.

Here's an early example: https://github.com/khoj-ai/khoj