Trending repositories for topic vector-database
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A cloud-native vector database, storage for next generation AI applications
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c...
OceanBase is an enterprise distributed relational database with high availability, high performance, horizontal scalability, and compatibility with SQL standards.
A minimalist yet highly performant, lightweight, lightning fast, multisource, multimodal and local Ingestion, Inference and Indexing solution, built in Rust.
Private & local AI personal knowledge management app for high entropy people.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
A minimalist yet highly performant, lightweight, lightning fast, multisource, multimodal and local Ingestion, Inference and Indexing solution, built in Rust.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
NNV(No-Named.V) is a vector database that supports Multi-Vector Search, high-performance HNSW, FLAT and quantization, and enables fast searches through sophisticated internal data shard design.
Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
Home of the AI workforce - Multi-agent system, AI agents & tools
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
A lightweight library that leverages Language Models (LLMs) to enable natural language interactions, allowing you to source and converse with data.
RAG (Retrieval-augmented generation) ChatBot that provides answers based on contextual information extracted from a collection of Markdown files.
The codebase for the book "AI-Powered Search" (Manning Publications, 2024)
A curated list of awesome works related to high dimensional structure/vector search & database
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A cloud-native vector database, storage for next generation AI applications
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
OceanBase is an enterprise distributed relational database with high availability, high performance, horizontal scalability, and compatibility with SQL standards.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c...
Private & local AI personal knowledge management app for high entropy people.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
NNV(No-Named.V) is a vector database that supports Multi-Vector Search, high-performance HNSW, FLAT and quantization, and enables fast searches through sophisticated internal data shard design.
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
A minimalist yet highly performant, lightweight, lightning fast, multisource, multimodal and local Ingestion, Inference and Indexing solution, built in Rust.
RAG-QA-Generator 是一个用于检索增强生成（RAG）系统的自动化知识库构建与管理工具。该工具通过读取文档数据，利用大规模语言模型生成高质量的问答对（QA对），并将这些数据插入数据库中，实现RAG系统知识库的自动化构建和管理。
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
A repository that showcases the native VECTOR type in Azure SQL Database to perform embeddings and RAG with Azure OpenAI.
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
A simple example implementation of the VoiceRAG pattern to power interactive voice generative AI experiences using RAG with Azure AI Search and Azure OpenAI's gpt-4o-realtime-preview model.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
A JavaScript library that brings vector search and RAG to your browser!
This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.
Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
A NodeJS RAG framework to easily work with LLMs and embeddings
Home of the AI workforce - Multi-agent system, AI agents & tools
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
A cloud-native vector database, storage for next generation AI applications
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c...
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Private & local AI personal knowledge management app for high entropy people.
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
OceanBase is an enterprise distributed relational database with high availability, high performance, horizontal scalability, and compatibility with SQL standards.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
RAG-QA-Generator 是一个用于检索增强生成（RAG）系统的自动化知识库构建与管理工具。该工具通过读取文档数据，利用大规模语言模型生成高质量的问答对（QA对），并将这些数据插入数据库中，实现RAG系统知识库的自动化构建和管理。
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
NNV(No-Named.V) is a vector database that supports Multi-Vector Search, high-performance HNSW, FLAT and quantization, and enables fast searches through sophisticated internal data shard design.
A compute framework for building Search, RAG, Recommendations and Analytics over complex structured & unstructured data.
Example chat-with-pdf app showing how to provision a dedicated database instance for each user. In this app, every database uses pgvector for similarity search. Powered by Neon
A minimalist yet highly performant, lightweight, lightning fast, multisource, multimodal and local Ingestion, Inference and Indexing solution, built in Rust.
Build a Python Reflex App with OpenAI, a Neon Postgres + Vector Database, and Deploy to a Virtual Machine
An intelligent assistant for querying and analyzing real estate condo data in Miami.
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
A simple example implementation of the VoiceRAG pattern to power interactive voice generative AI experiences using RAG with Azure AI Search and Azure OpenAI's gpt-4o-realtime-preview model.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Dabarqus is a stand alone application that implements a complete RAG solution.
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!
A demo ChatBot application developed using Amazon Bedrock service's KnowledgeBase, Agent and other AWS's serveless GenAI solution.
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit w...
The open source Meme Search Engine. Free and built to self-host locally with Python, Ruby, and Docker.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
A minimalist yet highly performant, lightweight, lightning fast, multisource, multimodal and local Ingestion, Inference and Indexing solution, built in Rust.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Super performant RAG pipelines for AI apps. Summarization, Retrieve/Rerank and Code Interpreters in one simple API.
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
A simple example implementation of the VoiceRAG pattern to power interactive voice generative AI experiences using RAG with Azure AI Search and Azure OpenAI's gpt-4o-realtime-preview model.
Radient turns many data types (not just text) into vectors for similarity search, RAG, regression analysis, and more.
Optimized local inference for LLMs with HuggingFace-like APIs for quantization, vision/language models, multimodal agents, speech, vector DB, and RAG.
NNV(No-Named.V) is a vector database that supports Multi-Vector Search, high-performance HNSW, FLAT and quantization, and enables fast searches through sophisticated internal data shard design.
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, and more.
A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
Private & local AI personal knowledge management app for high entropy people.
A cloud-native vector database, storage for next generation AI applications
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, a...
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c...
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
OceanBase is an enterprise distributed relational database with high availability, high performance, horizontal scalability, and compatibility with SQL standards.
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ...
The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.
Practical course about Large Language Models.
Private & local AI personal knowledge management app for high entropy people.
In-memory vector store with efficient read and write performance for semantic caching and retrieval system. Redis for Semantic Caching.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Semantic Search on Wikipedia with Upstash Vector
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
VectorHub is a free, open-source learning website for people (software developers to senior ML architects) interested in adding vector retrieval to their ML stack.
Embedding Studio is a framework which allows you transform your Vector Database into a feature-rich Search Engine.
Comprehensive Vector Data Tooling. The universal interface for all vector database, datasets and RAG platforms. Easily export, import, backup, re-embed (using any model) or access your vector data fro...
A NodeJS RAG framework to easily work with LLMs and embeddings
Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.
Community Plugins for Genkit (OpenAI, Groq, Anthropic, Cohere, etc)
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text
