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 platform for search, recommendations, RAG, and analytics offered via API

How to create Question-Answering system combining Langchain and OpenAI

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!

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

Qdrant Vector Database on Azure Cloud

This is Microsoft Fabric Copilot Workshop

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

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.

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

Production-ready local deployment of Cheshire Cat AI that delivers enterprise-grade features

Is a high-performance Augmented Recovery-Generation (RAG) solution based on Redis, Qdrant or PostgreSQL. It offers a high-level interface using FastAPI REST APIs

Qdrant operator creates and manages Qdrant clusters running in Kubernetes

A semantic search engine that transforms your documents into an intelligent, searchable knowledge base using vector embeddings and AI

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

The rag pipeline for optimizing dynamic data editing.

Bootstrap a Qdrant vector database cluster on Fly.io

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

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

Helper package to spin-up a Qdrant instance without Docker