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!
NornicDB is a high-performance graph + vector database built for AI agents and knowledge systems. It speaks Neo4j's (Bolt + Cypher) and qdrant's (gRPC) languages so you can use Nornic with zero code changes, while adding intelligent features including a graphql endpoint, air-gapped embeddings, GPU accelerated search, and other intelligent features.
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
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.
A semantic search engine that transforms your documents into an intelligent, searchable knowledge base using vector embeddings and AI
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
A RAG implementation on Llama Index using Qdrant vector stores as storage. Take some pdfs, store them in the db, use LLM to inference.
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