Ambar VS MeiliSearch

AnyTXT.net for PC. https://github.com/RD17/ambar and https://docfetcher.sourceforge.net/en/index.html for Linux

One product could be "Ambar: Document Search Engine"

https://github.com/RD17/ambar

> Ambar is an open-source document search engine with automated crawling, OCR, tagging and instant full-text search

> *Easily deploy Ambar with a single docker-compose file; *Perform Google-like search through your documents and contents of your images; *Tag your documents; *Use a simple REST API to integrate Ambar into your workflow

There was an open-source program called Ambar that was pretty chill. It let you full-text search documents, perform OCR on these documents, and tag. There surely exist apps that do each, but the nice thing about Ambar was it incorporated all of the above into one nice GUI.

I don't need any other features (other than batch uploading). The best ones I've found so far are Ambar, I, librarian, and Lodestone with their multiple 'snippet' search functionality, however for various reasons they won't work with my use case.[1]

Ambar - Document Search Engine · An open-source document search engine with automated crawling, OCR, tagging and instant full-text search

Amber Main Page and GitHub

There is also stuff like Mayan EDMS which is much more enterprise-oriented or Ambar which targeted more for individual users.

We needed to introduce a new service for search. As we settled on using meilisearch, we needed a way to sync updates on our models with the records in meilisearch. We could've continued to use callbacks but we needed something better.

Meilisearch

In this case, a good strategy is to use vector search only when the keyword/prefix search returns none or just a small number of results. A good candidate for this is MeiliSearch. It uses custom ranking rules to provide results as fast as the user can type.

With the VertexAI endpoint set up and tested, our next step is to work with LibreChat. LibreChat is an open-source ChatGPT clone that can integrate with various AI models, including the PaLM 2 models via the VertexAI API. It's built using React, MongoDB, and Meilisearch technologies.

Meilisearch seems like it is the best open source option.

https://www.meilisearch.com/

Starting with v1.3, you can use Meilisearch as a vector store. Meilisearch allows you to store vector embeddings alongside your documents conveniently. You will need to create the vector embeddings using your third-party tool of choice (Hugging Face, OpenAI). As we published the first v1.3 release candidate, you can try out vector search today.

I work at Meilisearch, an open-source search engine built in Rust. 🦀

https://www.meilisearch.com/ https://github.com/meilisearch