rag-retrieval / library
EmbedAnything
Capability: EmbedAnything
Use it when
- I need to create local embeddings from a PDF without building separate ingestion code.
- I need one Python pipeline to embed text files and other documented media sources.
What it solves
Not the fit when
- Choosing the best embedding model for a corpus.
- Operating a hosted vector database or search service.
- embedding-model-selection-blind
- vector-store-scale-cost
Install
pip install embed-anything
Invoke
Load `EmbeddingModel.from_pretrained_hf(...)`, then call `embed_anything.embed_file("path/to/file.pdf", embedder=model, config=config)`.Alternatives
No reviewed alternatives recorded yet.