pathwaycom/llm-app
Ready-to-run cloud templates for building real-time RAG, AI pipelines, and enterprise search applications that synchronize with various live data sources.
Awesome Infra for AI › Vector Databases & Retrieval Infrastructure
vespa-engine/vespa
Vespa is an open-source, high-performance AI search platform designed for serving and organizing various data types, including vectors, tensors, text, and structured data. It specializes in handling real-time serving use cases such as search, recommendation, and personalization, where data selection, machine-learned model evaluation, and aggregation must occur with low latency (typically under 100 milliseconds) over constantly changing, large datasets. The platform is built to distribute and evaluate data across multiple nodes in parallel, ensuring high availability and performance. Unlike general-purpose databases that merely add vector indexing, Vespa's core purpose is an "AI search platform" with integrated machine learning capabilities at serving time, making it particularly well-suited for RAG (Retrieval Augmented Generation) architectures. It has been developed over many years and is used in large internet services, handling hundreds of thousands of queries per second. While it can store diverse data, its primary focus is on the AI serving and retrieval layer rather than generic data storage. Its capabilities include inference at serving time, organization of data for AI applications, and robust scaling for operational AI.
https://github.com/vespa-engine/vespa
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