All these projects are from AI Engineering Hub. The Repo has 70+ MCP, RAG & AI Agents tutorials! It's 100% open-source Don't forget to star the Repo
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Building a Real-Time Voice RAG Agent Step-by-Step
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4. Voice RAG Agent Learn how to build a real-time Voice RAG Agent, step-by-step. Check this out: https://
github.com/patchy631/ai-e
ngineering-hub/tree/main/rag-voice-agent
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Building a 100% Local Deep Research Tool with MCP
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5. MCP-powered deep researcher Learn how you can build a 100% local deep research. Repo → https://
github.com/patchy631/ai-e
ngineering-hub/tree/main/Multi-Agent-deep-researcher-mcp-windows-linux
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Building Video RAG with MCP for Interactive Video Chat
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2. MCP-powered RAG over videos Learn how to build a video RAG that ingests a video and lets you chat with it. It also fetches the exact video chunk where an event occurred. Check this out: https://
github.com/patchy631/ai-e
ngineering-hub/tree/main/mcp-video-rag
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Local Multimodal RAG with DeepSeek Janus-Pro for Complex Documents
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3. Mumtimodal RAG Build a 100% local RAG over complex real-world docs with images, tables, text, and complex layouts. Powered by DeepSeek Janus-Pro. Check this out: https://
github.com/patchy631/ai-e
ngineering-hub/tree/main/deepseek-multimodal-RAG
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Building Agentic RAG Pipelines with Dynamic Context Retrieval
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1. Agentic RAG Build a RAG pipeline with agentic capabilities that can dynamically fetch context from different sources, like a vector DB and the internet. Check this out: https://
github.com/patchy631/ai-e
ngineering-hub/tree/main/agentic_rag
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Smart Health Agent: GPU-Accelerated Multi-Agent System for Real-Time Monitoring
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Smart Health Agent A GPU-accelerated multi-agent system providing real-time health monitoring with personalized insights. Built with LangGraph to orchestrate agents that process health metrics and environmental data. Check it out here https://
github.com/jayrodge/ai-ag
ents/tree/main/smart_health_agent
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Production-Ready AI Agents: A Practical Guide with LangGraph
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Agents Towards Production Nir Diamant just released a practical guide for building production-ready AI agents. This open-source playbook features tutorials using LangGraph for workflows and LangSmith for observability, plus essential production features. Check it out
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AutoAgent: Zero-Code LLM Agent Framework with Natural Language
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Build and deploy LLM agents just using natural language! AutoAgent is the Fully-Automated & Zero-Code LLM Agent Framework that let's you create and deploy LLM agents using just natural language. 100% Open Source
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Jules now supports AGENTS.md files
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Jules now supports AGENTS md file! So it can use information from this file in your repository as an additional context for coding tasks.