Question: I'm looking for an open-source AI database that supports full-text search and metadata filtering for my app development.

For your app development needs, Chroma is a good example of a powerful open-source AI application database. It offers full-text search, metadata filtering and support for multiple input modes, so it's good for developers and companies building their own AI applications. Chroma can be installed with Python or JavaScript and has an active community for contributions and help.

Another good choice is OpenSearch, a flexible and scalable option that includes geospatial indexing, SQL/PPL support and k-NN/vector database abilities. It's fully open-source and can run on different infrastructure, so it's good for enterprise environments. OpenSearch is good for building high-performance search applications and has a collection of tools to extend its abilities.

Milvus is an open-source vector database geared for high-dimensional vector search. It supports metadata filtering, hybrid search and elastic scaling, so it's good for image search and recommender systems. With several deployment options and a feature-rich interface, Milvus is a good option for high-performance and scalable AI applications.

If you need a system that can handle both structured and unstructured data, Vespa could be a good choice. It's a unified search engine and vector database with vector search, lexical search and machine-learned models. Vespa is geared for building production-ready search applications at any scale and supports a variety of AI use cases, including recommendation and personalization.