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    Lantern

    Postgres vector database extension to build AI applications

    Technology

    How Lantern’s technology works — architecture, AI models, and technical capabilities.

    How does Lantern work?

    Lantern operates as an open-source Postgres vector database, enabling developers to build AI applications by utilizing SQL commands. It integrates advanced search functionalities, including vector search and BM25 text search, allowing seamless scaling to millions of vectors with serverless indexing.

    What technology powers Lantern?

    Lantern is built on Postgres, leveraging its capabilities for vector search and indexing. It utilizes extensions like pgvector and the BM25 ranking algorithm to enhance search performance, making it suitable for high-performance AI applications.

    What are Lantern's main features?

    Lantern's key features include serverless indexing, embedding generation, support for 20+ embedding models, and the ability to run LLMs directly within the database. It also offers seamless integration with existing SQL workflows and automatic upgrades.

    What type of AI does Lantern use?

    Lantern utilizes various AI techniques, including embedding generation and large language models (LLMs). It supports integrations with models from OpenAI, Cohere, and other open-source sources, allowing for flexible AI application development.

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