A JSONL or Parquet collection with a text field and an embedding model suited to the task.
Semantic search and retrieval
letsearch
Connect applications to relevant text.
letsearch provides a semantic search layer by indexing text collections as vectors. It imports JSONL, Parquet, or Hugging Face datasets, embeds selected fields, and exposes indexed collections through a search service. The repository documents current API behavior and usage details.
01 / INPUT TO OUTPUT
Import the collection, embed the selected field, build an index, and start the search service.
Indexed records matching a semantic query, available for an application to use.
02 / WHAT IT DOES
Import text collections
Read JSONL and Parquet files, including datasets addressed through Hugging Face Hub paths.
Build a vector index
Select collection fields and an embedding model to create a searchable vector index.
Expose search to an application
Run a search service over an indexed collection and query it with the companion client.
03 / WORK WITH ALTAI
From a component
to your application.
ALTAI uses letsearch to build retrieval layers that connect document collections to applications. We prepare the source text and evaluation set, measure retrieval quality, and integrate results into the target workflow.
Explore custom developmentWORK WITH ALTAI
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