There are 0 repository under qdrant-vector-database topic.
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.
All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.
How to create Question-Answering system combining Langchain and OpenAI
Qdrant Vector Database on Azure Cloud
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!
This is Microsoft Fabric Copilot Workshop
A Web app stack written in FastAPI, Qdrant, and React for creating AI projects
Building a Chain of Thought RAG Model with DSPy, Qdrant and Ollama
Bootstrap a Qdrant vector database cluster on Fly.io
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.
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
Qdrant operator creates and manages Qdrant clusters running in Kubernetes
Helper package to spin-up a Qdrant instance without Docker
This repository is a demonstration of deploying Qdrant, a high-performance vector database, in a distributed manner.
Text to Image & Reverse Image Search Engine built upon Vector Similarity Search utilizing CLIP VL-Transformer for Semantic Embeddings & Qdrant as the Vector-Store
A Retrieval-Augmented Generation (RAG) System for PDF Chat using Qdrant Vector Database.
Revise your subjects with studybot
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
A semantic and full text search engine UI written in Astro and SolidJS
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.
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
Doppalf is a RAG powered AI chat bot application
A dynamic chatbot serving tailored food recommendations and similar recipes.
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.
A repository for training transformer based models
Legal Documents Multilingual Semantic Search
User-friendly interface for creating effective Retrieval Augmented Generation (RAGs)
Rust App on Qdrant - Vector database
VoicePassport 🎤is an innovative authentication system leveraging voice recognition technology, blockchain ⛓️ security, and vector databases 📊 for robust and seamless user verification.
A Neural Search Tool that helps you find relevant papers to read based on your interests
Generating embedding for 1000s of PDF Documents, in Qdrant using FastEmbed with distributed Computing in Ray
Build amazing AI and RAG-powered applications, plain and simple🪂
A state-of-the-art Retrieval-Augmented Generation (RAG) application using OpenAI, Qdrant vector store, embeddings, FastAPI, React for the UI, NewsAPI, Word Cloud, and Langchain. This project enables dynamic reading and QA on news articles, focusing on various people of interest, with real-time, personalized news insights.
MedRaga is a medical assistance application aimed at providing accurate and personalized medical information to healthcare professionals. It uses RAG technology to retrieve the latest medical research from trusted sources, augment it with patient data, and deliver personalized diagnoses and treatment plans.
Question-Answering ChatBot leveraging Qdrant for vector search, Deepset Haystack for NLP pipeline, and Llama3 for advanced language understanding.