a-agmon/dfembeder
DF Embedder is a high-performance Python library (with a Rust backend) for indexing and embedding Apache Arrow compatible DataFrames (like Polars or Pandas) into low latency vector databases based on Lance files.
This tool helps data professionals quickly prepare large datasets of text for semantic search. You input a spreadsheet or table containing text, and it generates an optimized database ready for finding similar records based on meaning, not just keywords. It's ideal for data scientists, analysts, or anyone managing extensive text-based information.
No commits in the last 6 months.
Use this if you need to rapidly turn massive tables of text data into a searchable format for semantic similarity, especially when dealing with millions of records and requiring high performance.
Not ideal if your data is not primarily textual or if you require highly custom, state-of-the-art embedding models beyond the efficient static one provided.
Stars
8
Forks
—
Language
Rust
License
MIT
Category
Last pushed
Aug 13, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/a-agmon/dfembeder"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Anush008/fastembed-rs
Rust library for vector embeddings and reranking.
huggingface/text-embeddings-inference
A blazing fast inference solution for text embeddings models
MinishLab/model2vec-rs
Official Rust Implementation of Model2Vec
finalfusion/finalfusion-rust
finalfusion embeddings in Rust
finalfusion/finalfusion-python
Finalfusion embeddings in Python