In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

Self-Hosting Guide. Learn all about locally hosting (on premises & private web servers) and managing software applications by yourself or your organization. Including Cloud, LLMs, WireGuard, Automation, Home Assistant, and Networking.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.

A Go implementation of the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources and tools.

⚙️🦀 Build modular and scalable LLM Applications in Rust

🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation

A curated list of Large Language Model resources, covering model training, serving, fine-tuning, and building LLM applications.

LLM Zoomcamp - a free online course about real-life applications of LLMs. In 10 weeks you will learn how to build an AI system that answers questions about your knowledge base.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

A curated list of resources for using LLMs to develop more competitive grant applications.

AdalFlow: The library to build & auto-optimize LLM applications.

Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.

Easiest and laziest way for building multi-agent LLMs applications.

Data framework for your LLM applications. Focus on server side solution

AgentScope Java: Agent-Oriented Programming for Building LLM Applications

Code and Slides

No-code multi-agent framework to build LLM Agents, workflows and applications with your data

agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications.

Build LLM-powered applications in Ruby

A comprehensive guide to building RAG-based LLM applications for production.

The PHP Agentic Framework to build production-ready AI driven applications. Connect components (LLMs, vector DBs, memory) to agents that can interact with your data.

DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough.

An LLM-based autonomous agent controlling real-world applications via RESTful APIs

Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.

The Context Optimization Layer for LLM Applications

Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊