qdrant-vector-database

There are 74 repositories under qdrant-vector-database topic.

  • vault-ai

    pashpashpash/vault-ai

    OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.

    Language:JavaScript3.3k4859306

  • devflowinc/trieve

    All-in-one infrastructure for search, recommendations, RAG, and analytics offered via API

    Language:Rust1.4k11818116

  • mallahyari/drqa

    How to create Question-Answering system combining Langchain and OpenAI

    Language:TypeScript1717828

  • Azure-Samples/qdrant-azure

    Qdrant Vector Database on Azure Cloud

    Language:Shell891831822

  • hkulekci/qdrant-php

    Qdrant is a vector similarity engine & vector database. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more!

    Language:PHP8771719

  • kinfey/MSFabricCopilotWorkshop

    This is Microsoft Fabric Copilot Workshop

    Language:Jupyter Notebook744127

  • ContextData/VectorETL

    Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications

    Language:Python69123

  • mallahyari/ai-starter-kit

    A Web app stack written in FastAPI, Qdrant, and React for creating AI projects

    Language:JavaScript431010

  • sachink1729/DSPy-Chain-of-Thought-RAG

    Building a Chain of Thought RAG Model with DSPy, Qdrant and Ollama

    Language:Jupyter Notebook22102

  • Adii2202/RAG-AI-Voice-assistant-

    Performing a RAG (Retrieval Augmented Generation) assessment using voice-to-voice query resolution. Provide the file containing the queries, ask the questions, and receive the results via voice.

    Language:Python15112

  • kylemclaren/qdrant-on-fly

    Bootstrap a Qdrant vector database cluster on Fly.io

    Language:Shell14300

  • edilma/RAG-App-HackTogether

    ChatGPT-like Application using RAG pattern that allows to ask question to my own documents - I Used Semantic Kernel to integrate a LLM (OpenAI) using C# to orchestrate AI pluggins (Azure Cognitive Services). For the document embeddings I used Qdrant for the vector database and Pdfpig to extract the content from the pdfs

    Language:C#9104

  • Snehil-Shah/Multimodal-Image-Search-Engine

    Text to Image & Reverse Image Search Engine built upon Vector Similarity Search utilizing CLIP VL-Transformer for Semantic Embeddings & Qdrant as the Vector-Store

    Language:Jupyter Notebook9201

  • Mohitkr95/qdrant-multi-node-cluster

    This repository is a demonstration of deploying Qdrant, a high-performance vector database, in a distributed manner.

    Language:Python8202

  • qdrant-operator/qdrant-operator

    Qdrant operator creates and manages Qdrant clusters running in Kubernetes

    Language:C#8291

  • Anush008/qdrant-npm

    Helper package to spin-up a Qdrant instance without Docker

    Language:JavaScript7100

  • codebanesr/fahm

    Feature extraction + chatbot

    Language:TypeScript6201

  • Ashish-Abraham/DocWhisperer-Qdrant

    A Retrieval-Augmented Generation (RAG) System for PDF Chat using Qdrant Vector Database.

    Language:Python5201

  • HemanthSai7/StudyBot

    Revise your subjects with studybot

    Language:Jupyter Notebook5100

  • hriteshMaikap/rag-flask-api

    A repository containing a modularized implementation of a Retrieval-Augmented Generation (RAG) model as Flask APIs.

    Language:Python5100

  • rajkstats/PharmAssistAI

    An innovative application designed to help pharmacists and pharmacy students quickly research FDA-approved drugs by retrieving relevant information from drug labels and adverse event datasets, and providing AI-generated summaries to streamline the learning process

    Language:Jupyter Notebook5102

  • romilandc/llama-index-RAG

    A RAG implementation on Llama Index using Qdrant vector stores as storage. Take some pdfs, store them in the db, use LLM to inference, enjoy.

    Language:Python5200

  • santhalakshminarayana/doppalf

    Doppalf is a RAG powered AI chat bot application

    Language:TypeScript5101

  • yash9439/RayQdrantFastEmbed

    Generating embedding for 1000s of PDF Documents, in Qdrant using FastEmbed with distributed Computing in Ray

    Language:Jupyter Notebook5110

  • devflowinc/vault-search

    A semantic and full text search engine UI written in Astro and SolidJS

    Language:JavaScript44830

  • Praveen76/Introduction-to-LLMs

    Dive into the world of Large Language Models (LLMs) with this comprehensive repository. From understanding basics to exploring various LLMs, finetuning on downstream tasks, and deploying models using Vector DBs like Qurant, this guide equips you with essential skills for harnessing the power of LLMs in your projects.

    Language:Jupyter Notebook3102

  • rosspatil/ai-chatbot

    Dockerized AI Chatbot is an open-source project that provides a chatbot powered by artificial intelligence, specifically built using OpenAI's GPT-3 (Language Model) for natural language processing and understanding

    Language:JavaScript3202

  • rosyteran/Llamaparse-Groq-Retrieval_Augmented_Agent

    User-friendly interface for creating effective Retrieval Augmented Generation (RAGs)

    Language:Jupyter Notebook3100

  • sergio11/voice_passport_architecture

    VoicePassport 🎤is an innovative authentication system leveraging voice recognition technology, blockchain ⛓️ security, and vector databases 📊 for robust and seamless user verification.

    Language:Python310

  • Anandhupa1/GENAI-MAIN-PROJECT

    A dynamic chatbot serving tailored food recommendations and similar recipes.

    Language:JavaScript2100

  • bhattbhavesh91/qdrant-tutorials

    QDrant Vector Database with Python Tutorials

    Language:Jupyter Notebook220

  • mdimado/PaperChat

    PaperChat is an AI-powered chat application designed to handle PDF documents through a user-friendly interface. Users can upload PDF files, ask questions related to the content within those documents, and receive responses generated using advanced natural language processing (NLP) techniques.

    Language:Python2200

  • mfmezger/aleph-alpha-rag

    RAG Backend for Aleph Alpha LLMs.

    Language:Python2101

  • migrx-io/vault-plugin-secrets-qdrant

    A Vault plugin for the Qdrant vector database

    Language:Go2100

  • rust-master/qdrant-rust

    Rust App on Qdrant - Vector database

    Language:Rust210

  • yash9439/Qdrant-DeepsetHaystack-Llama3-QnA-ChatBot

    Question-Answering ChatBot leveraging Qdrant for vector search, Deepset Haystack for NLP pipeline, and Llama3 for advanced language understanding.

    Language:Jupyter Notebook2100