ai-engineering-hub and awesome-llm-apps
These tools are complements, with "ai-engineering-hub" providing in-depth tutorials for building AI agent and RAG applications, and "awesome-llm-apps" offering a collection of existing, diverse LLM applications and their implementations as practical examples for learners.
About ai-engineering-hub
patchy631/ai-engineering-hub
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
# Technical Summary Curates 93+ production-ready projects across beginner-to-advanced difficulty levels, with implementations spanning OCR, multimodal RAG, voice agents, and agentic workflows using frameworks like CrewAI, LlamaIndex, and AutoGen. Projects demonstrate integration with local models (Llama, DeepSeek, Qwen) alongside cloud APIs, with emphasis on practical patterns like streaming chatbots, MCP (Model Context Protocol) integration, and real-time voice pipelines. Includes structured learning paths from single-component basics to enterprise deployment patterns with vector databases (Qdrant, Milvus) and memory systems.
About awesome-llm-apps
Shubhamsaboo/awesome-llm-apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
Extends beyond standard RAG and agent patterns with specialized implementations like multi-agent teams, voice agents, Model Context Protocol (MCP) integration, and autonomous game-playing agents. Features starter templates and advanced production-ready applications across diverse domains—from financial analysis and medical imaging to self-evolving agents and browser automation—spanning OpenAI, Anthropic, Google, xAI, and locally-runnable open-source models like Llama and Qwen.
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