Ecosystem & Stack: qdrant

A modular framework for building advanced Agentic RAG systems using LangGraph, featuring intelligent query processing, conversation memory, and human-in-the-loop clarification.

Simplifies the deployment of agentic Retrieval Augmented Generation (RAG) applications within enterprise cloud infrastructure, offering an open-source alternative to custom GPTs.

Learn to design, train, and deploy a real-time financial advisor LLM system using a hands-on, three-pipeline approach.

An intelligent dialogue system leveraging RAG technology to build Q&A services based on your custom knowledge base.

A comprehensive practical guide and accompanying codebase for building, deploying, and monitoring advanced LLM and RAG applications on AWS, emphasizing LLMOps best practices.

A Python library for representing, transmitting, storing, and retrieving multimodal data, designed for AI applications.

An all-in-one API platform providing advanced search, recommendations, and Retrieval-Augmented Generation (RAG) capabilities for developers.

A free, hands-on course teaching how to build and deploy production-ready LLM and RAG systems, including a personalized 'LLM Twin', using LLMOps best practices.

A universal UI and tool suite designed to simplify the management, visualization, and interaction with vector databases like Pinecone, Chroma, Qdrant, and Weaviate.

An open-source Docker Compose template for quickly setting up a secure, self-hosted local AI and low-code development environment.