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
epsilla-cloud/vectordb
Epsilla is an open-source vector database management system designed for high-performance and scalable similarity search of embedding vectors. Its primary purpose is to bridge the gap between information retrieval and memory retention for Large Language Models (LLMs). The core engine is written in C++ and utilizes advanced academic parallel graph traversal techniques for vector indexing, aiming to provide significantly faster vector search while maintaining high precision. Key features include full-fledged database management with familiar concepts like databases, tables, and fields, metadata filtering, and hybrid search combining dense and sparse vectors. It supports built-in embedding functionality for natural language-based search, offers a cloud-native architecture with compute-storage separation, serverless capabilities, and multi-tenancy. Epsilla provides client libraries for Python, JavaScript, and Ruby, alongside a REST API interface, and integrates with popular LLM frameworks such as LangChain and LlamaIndex. While it can be run via Docker, it also offers an experimental Python library for direct embedding without a Docker container.
https://github.com/epsilla-cloud/vectordb
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