Building performant embedding workflows with Chroma and Baseten

You can now use Chroma, the open-source AI application database, with Baseten's inference platform to create AI-native apps. Chroma is unique among vector databases because it is open-source and offers a natural choice for developers building with open models who want control over their entire AI infrastructure stack. Baseten offers dedicated deployments of every open-source, fine-tuned, and custom embedding model on autoscaling infrastructure. Recently, Baseten announced Baseten Embedding Inference (BEI), the world's fastest runtime for embedding models, which provides twice the throughput of the previous leading solutions for modern LLM-based embedding models. BEI is useful with Chroma in two ways: it offers substantial speed and cost savings when filling the Chroma vector database with an initial corpus of data, and low-latency, real-time embedding inference when passing user queries to the Chroma database. You can use BEI-optimized embedding models deployed on Baseten with Chroma via our official integration. To use Chroma with Baseten, you can call an embedding model running on Baseten using the Chroma Python SDK in less than five minutes, by deploying an embedding model on Baseten, installing the Chroma Python package, and generating embeddings using Baseten and Chroma. This makes building AI-native apps simpler and faster with Chroma's open-source flexibility paired with Baseten's high-performance embedding inference (BEI).

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