StarlightSearch / EmbedAnything
Highly Performant, Modular, Memory Safe and Production-ready Inference, Ingestion and Indexing built in Rust 🦀
Why this job: topics: rag, vector-database
What it does
- No Dependency on Pytorch. Easy to deploy on cloud, comes with low memory footprint.
- Highly Modular . Choose any vectorDB adapter for RAG, with ~~1 line~~ 1 word of code
- Backend . Supports Candle, ONNX and cloud models
- MultiModality . Works with text sources like PDFs, txt, md, Images JPG and Audio, .WAV
- GPU support . Hardware acceleration on GPU as well.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 14 days ago
- Stars
- 1,322
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.7.1
- Released 4 months ago
- Built with
- Rust
- 92% of the code
Is it looked after?
- Contributors
- 4
- Last 90 days
- Issues
- 75% closed
- 19 still open
- Pull requests
- 105 merged
- 1 waiting
- Releases
- 39
- 2 in the last year
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More: languages, topics and project record
Languages
- Rust 92%
- Python 7%
- Dockerfile 1%
- HTML <1%
Topics
- ai
- cloud
- generative-ai
- hacktoberfest
- high-performance
- indexing
- inference
- information-retrieval
- large-language-models
- local
- machine-learning
- onnxruntime
Project record
- JobRAG and search
- StatusListed
- Commits922
- Forks140
- Watching12
- Stars in 28 days+13
- CreatedMar 31, 2024
- First seen by usNov 7, 2026
- CheckedNov 7, 2026