altaidevorg/letsearch

A vector DB so easy, even your grandparents can build a RAG system 😁

24
/ 100
Experimental

Letsearch helps you quickly prepare your documents for AI applications, specifically for building Retrieval-Augmented Generation (RAG) systems or semantic search. You provide your documents in JSONL or Parquet files, and it processes them into a searchable index. This tool is ideal for anyone working with large collections of text who wants to make them instantly available for AI models without complex setup.

No commits in the last 6 months.

Use this if you need to rapidly set up a system that allows AI to 'read' and retrieve information from your documents, like creating a smart FAQ bot or a knowledge base search.

Not ideal if you require advanced customization of vector indexing algorithms or need to integrate with a pre-existing, complex data pipeline.

knowledge-management information-retrieval AI-application-development data-preparation
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 0 / 25

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Stars

18

Forks

Language

Rust

License

Apache-2.0

Last pushed

Jul 18, 2025

Commits (30d)

0

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