vector-db

There are 21 repositories under vector-db topic.

  • nitaiaharoni1/vector-storage

    Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

    Language:TypeScript2345940

  • l3vels/L3AGI

    Open-source framework to make AI agents' team collaboration as effective as human collaboration.

    Language:TypeScript2231014063

  • Dripfarm/SVDB

    Swift Vector Database. On-device, local vector database for building the next-generation of user experiences

    Language:Swift171547

  • cgtuebingen/ggnn

    GGNN: State of the Art Graph-based GPU Nearest Neighbor Search

    Language:Cuda163241427
  • youtube-gpt

    vdutts7/youtube-gpt

    YouTubeGPT • AI Chat with 100+ videos ft. YouTuber Marques Brownlee (@ MKBHD) ⚡️🔴🤖💬

    Language:TypeScript682017

  • rafaelpierre/moviegpt

    MovieGPT: A RAG, Gen AI application for Movie Recommendations

    Language:Jupyter Notebook35201

  • prrao87/lancedb-study

    Benchmark study on LanceDB, an embedded vector DB, for full-text search and vector search

    Language:Python27123

  • hkproj/retrieval-augmented-generation-notes

    Slides for "Retrieval Augmented Generation" video

    Language:Jupyter Notebook21302

  • Zipstack/unstract-adapters

    Unstract's interface to LLMs, Embeddings and VectorDBs.

    Language:Python18203

  • mantrakp04/sheer

    A fully client-side chat application with AI capabilities running entirely in your browser. No servers, complete privacy, and persistent storage.

    Language:TypeScript12100

  • hpi-swa-lab/Squeak-SemanticText

    ChatGPT, embedding search, and retrieval-augmented generation for Squeak/Smalltalk

    Language:Smalltalk11841

  • aws-samples/rag-with-amazon-bedrock-and-documentdb

    Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon DocumentDB (with MongoDB Compatibility)

    Language:Jupyter Notebook8201

  • habanoz/crawl-for-vector-db

    A web site crawler for semantic search.

    Language:Jupyter Notebook4100

  • raisultan/pac

    Automation of Prioritization and Categorization of Support Tickets Using LLMs and Vector DBs

    Language:Python3100

  • dhavalCode/genius-ai

    GeniusAI: Personalized AI companions powered by Llama 2 13B model. Engage in diverse conversations, explore personas, and revolutionize learning interactively.

    Language:TypeScript2101

  • legobridge/retrieval-augmented-generation

    A proof-of-concept of retrieval-augmented generation, using Google's PaLM API.

    Language:Python2102

  • Amruth-github/Question-Generation-using-LLMs-and-Vector-DB

    This project generates question over a given corpus of information. It uses a LLM and the FAISS vector DB to acomplish the above mentioned objectives.

    Language:Jupyter Notebook1100

  • oscarcitoz/agent-config

    Kotlin microservice for managing agents, configurations, and tools. Integrates with AI systems like OpenAI and Amazon Bedrock. Uses PostgreSQL and supports agent retrieval by ID or similarity (via Vector DB).

    Language:Kotlin1

  • pintadb/columbus

    Columbus is a cloud-based search platform for searching hosted cloud apps on your personal Kubernetes.

    Language:Go01131

  • tobiasodion/mood-analyzer

    Fullstack AI-powered app that analyzes and tracks users' moods based on their journal entries.

    Language:TypeScript0100

  • xtt28/quora_vector_search

    AI- & vector database-powered Quora question search

    Language:Python00