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.

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. With its modular architecture it's best suited for building RAG, multi-agent workflows, or business process automations.

Hands-on LangGraph course repo for building production-grade LLM agents with Agentic RAG, ReAct, and reflection workflows.

🧠 A production-grade, agentic RAG platform for portfolio intelligence, combining LangChain, Chroma/FAISS, Hugging Face embeddings, and Ollama with dynamic entity extraction, backend API tool-chaining, and a real-time interactive assistant across deploy-ready frontend, backend, and infrastructure stacks.

Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Temporal. Built-in RAG pipeline for enterprise knowledge retrieval. A2A and MCP protocol support. Visual drag-and-drop blueprint builder.

A production-ready framework for composing AI agents from declarative TOML configuration, with MCP tool integration, RAG pipelines, and an OpenAI-compatible web API.

AgentStack is a production-grade multi-agent framework built on Mastra, delivering 50+ enterprise tools, 25+ specialized agents, and A2A/MCP orchestration for scalable AI systems. Focuses on financial intelligence, RAG pipelines, observability, and secure governance. ACP Openclaw, Gemini CLI, Opencode

Scalable Agentic RAG system using Pydantic AI, FastAPI & pgvector. Modular, production-ready foundation for document-based AI apps

Complete Implementation of 21 Agentic Design Patterns A comprehensive collection of production-ready AI agent patterns, each as a runnable project. Master agentic design through practical examples covering prompt chaining, multi-agent systems, RAG, and more. Perfect for AI developers, researchers, and teams building complex AI workflows

Production-ready RAG framework for Python — multi-tenant chatbots with streaming, tool calling, agent mode (LangGraph), vector search (FAISS), and persistent MongoDB memory. Built on LangChain.

Production-ready Python starter for LLM projects: agents, RAG, evals, and observability

🤖 Advanced Multi-Agent AI Template: Production-ready system combining Groq's speed with LangChain's flexibility. Features RAG, document processing, and real-time agent collaboration. Built with Streamlit for instant deployment. Ready to customize and scale! 🚀

Production-grade TypeScript AI runtime focused on reliability, governance, and reproducible LLM systems. Multi-provider gateway, agents, RAG, workflows, policy engine, audit trails, and deterministic testing — built for teams shipping AI in production.

Develop a production-ready Real-Time Voice AI Agent that combines Retrieval Augmented Generation (RAG) with ultra-low latency voice processing. This system enables natural, spoken conversations with an AI assistant, accessing custom knowledge bases stored in vector databases for instant information retrieval.

Production-grade AI architecture and deployment for critical institutions, specializing in agentic workflows, RAG, and institutional-scale MLOps.

Agentic DSPy RAG is a production-ready, multi-agent Retrieval-Augmented Generation (RAG) system built with the DSPy framework. It features vision-based data ingestion, advanced intent classification, specialized agent routing, multi-step reasoning, and a robust FastAPI backend. Designed for high-quality, context-aware conversational AI over complex

Production-ready Python framework for AI agents with built-in guardrails, audit logging, cost tracking, and hybrid RAG. Supports OpenAI, Anthropic, Gemini, Ollama. By NichevLabs.

Agentic Adaptive RAG is a production-ready framework for building self-correcting, reasoning-based LLM systems that dynamically choose between retrieval, web search, and generation.

🎭 MoE Agent: Replace Multi-Agent with single-prompt AI architecture | RAG + SQL + Tool calling without routing | Zero context loss, 10x cost reduction | LLM Prompt engineering for AGI | Production-ready template | Solve ambiguous queries & cross-domain reasoning

Enterprise LangChain platform with multi-agent collaboration, advanced RAG, local LLM support, and modern web interface. Production-ready AI orchestration for research, coding, and data analysis.

A practical guide to AI engineering — LLMs, RAG, agents, evals, and production ops. Built for engineers who ship AI systems.

TaskForce is a modular, open-source, production-ready TypeScript agent framework for orchestrating AI agents, LLM-powered autonomous agents, task pipelines, dynamic toolchains, RAG workflows and memory/retrieval systems.

SomaBrain is a production-ready cognitive memory and RAG platform for AI agents. Features: multi-tenant memory, advanced math, secure FastAPI, full test coverage, and modular RAG pipeline. Real math, real memory, real docs.

A self-paced bootcamp for engineers building AI into production systems. Starts from fundamentals (tokenization, embeddings, prompting) and builds to RAG, Agents (LangGraph, tool design, memory, multi-agent), and LLMOps. Depth over breadth.

Production-ready Haystack/LangChain pipelines for Hybrid & Parent-Child Retrieval, Diversity Filtering, MMR, Metadata Filtering, Reranking, Query Enhancement, Multi-Tenancy, Agentic RAG across Pinecone, Weaviate, Milvus, Qdrant, Chroma with dataset loaders, evaluation tooling, and benchmarks for TriviaQA, ARC, PopQA, FactScore and Earnings Calls.

An enterprise-grade, full-stack AI travel planner which provides data-driven itineraries for Lucknow, India and showcases production-ready architecture, combining a FastAPI backend with a Streamlit frontend. It leverages an advanced agentic RAG system, context-aware responses by integrating a local knowledge base with live, external APIs.

WindMind-AI is an agentic, RAG-powered ML platform for wind forecasting, combining multi-agent orchestration, deep learning ensembles, and production-grade MLOps pipelines.

Production-grade LlamaIndex agentic system skill for Claude Code. Covers semantic ingestion, property graphs, context RAG, event-driven workflows, and Phoenix observability. Supports 14+ AI coding agents via skilz installer.

Production-ready Employee AI Buddy - A multi-agent system using RAG, MCP, and A2A protocols for intelligent workplace assistance. Features specialized agents for HR, greetings, and data retrieval with Docker deployment and monitoring.

AI career platform API using RAG (pgVector) and LangChain agents for job matching, skill-gap analysis, and career planning—built with FastAPI and production-grade deployment.