Available Integrations
Chroma
Chroma is an open-source vector database tailored to applications with large language models.- Contextual AI on the Chroma Docs Integration Page
- Multimodal RAG with Chroma and Contextual AI Parser
- Using the Contextual AI Reranker with Chroma
- Natural Language Unit Testing for RAG Systems with Chroma and LMUnit
- Chroma on GitHub
Elastic
Elastic is a distributed vector database and search engine built on top of Apache Lucene- Creating a Contextual AI Endpoint in Elastic
- Elastic and Contextual AI Partnership Announcement
- Elastic on GitHub
Snowflake
Snowflake is a leading cloud-native data platform consisting of a data warehouse, data lake, and suite of data services available as a SaaS.- Contextual AI How-to Guide: Snowflake Native App
- Example Script: Contextual AI Python SDK & Snowflake Native App
- Snowflake and Contextual AI Native App Announcement
- Press Release: Snowflake + Contextual AI
- Contextual AI in the Snowflake Marketplace
- Snowflake Labs on GitHub
Weaviate
Weaviate is a vector database that supports object and vector storage, hybrid search, and highly selective filters.Recipes
- Contextual AI Parser + Weaviate Integration: Use Contextual AI’s Parser with Weaviate to build a RAG application over PDF documents.
- Generative Search with Contextual AI:
Use Contextual AI’s generative model (
v2) with Weaviate for RAG. - Reranking with Contextual AI:
Use Contextual AI’s reranking model (
ctxl-rerank-v2-instruct-multilingual) with Weaviate to improve search result quality.
Weaviate Docs on GitHub
- Contextual AI + Weaviate Integrations
- Contextual AI Generative AI with Weaviate
- Contextual AI Reranker Models with Weaviate