> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vlm.run/llms.txt
> Use this file to discover all available pages before exploring further.

# ChromaDB

## Hybrid Document Search with `vlm-1` and ChromaDB

ChromaDB has emerged as one of the most popular databases for Vector Embedding and RAG flows.
With `vlm-1`, we can go beyond simple CLIP embeddings and extract precise metadata from
documents, which can be combined with the document vector to support natural language
lookup with fine-grained metadata matching.

Run the Colab notebook [here](https://colab.research.google.com/github/autonomi-ai/vlm-cookbook/blob/main/examples/vlm-1-hybrid-search-chroma.ipynb)