Ai Engineering Hub

🌟 AI Engineering Hub ✨ 5/15 projects · more on the way

A comprehensive showcase of enterprise-grade LLM applications featuring RAG architectures, intelligent AI agents, autonomous agentic systems, Model Context Protocol (MCP), LangChain/LangGraph frameworks, and cutting-edge generative AI patterns

This repository features LLM apps that use models from OpenAI, Anthropic, Google, xAI and open-source models like Qwen or Llama that you can run locally on your computer.

[](README.md) [](README.de.md) [](README.ru.md) [](README.zh.md)

[📂 Featured AI Projects](#-featured-ai-projects) • [🚀 Getting Started](#-getting-started) • [🤔 Why AI Engineering Hub?](#-why-ai-engineering-hub) • [🤝 Contributing](#-contributing) • [🙏 Thank You](#-thank-you-community-for-the-support)

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5 projects live. More shipping every few weeks.

This is where I build and document real AI engineering work — not tutorials copied from docs, not "hello world" agents. Every project here started from a problem I actually wanted to solve, and the code reflects that.

The stack changes per project depending on what fits. LangGraph when I need stateful agent loops. Groq when inference speed matters. Local models when I want to understand what's actually happening under the hood. Each folder has a working app, a proper README, and usually a live demo you can try right now without cloning anything.

If you're an engineer looking to see how these systems get built in practice — not in theory — this is the repo for that. ---

What's here

|#|Project|What it does|Stack|Demo| |---|---|---|---|---| |01|Agentic RAG Assistant|Smart Q&A with self-correction and hallucination detection|LangGraph · Hybrid Search · GPT-4o|🤗 Try it| |02|Voice AI Assistant|Talk to an AI, get voice responses back|Groq · Whisper · gTTS · Streamlit|🌐 Live app| |03|AI Podcast Generator|News URLs → produced podcast episode with MP3|LangGraph · BART · Groq · gTTS|🤗 Try it| |04|YouTubeScriptMaster|YouTube video → structured script and summary|LangGraph · Groq · yt-dlp · BART|🤗 Try it| |05|AI Presentation Generator|Plain text → full PowerPoint deck with AI images|LangGraph · Groq · python-pptx · Streamlit|🤗 Try it|

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📂 Featured AI Projects

👨‍💼 [1. Agentic RAG Assistant](./01-agentic-rag-assistant)

[](01-agentic-rag-assistant/assets/project1.gif) [](https://huggingface.co/spaces/fcyber/agenticrag)

Smart Q&A Assistant with intelligent routing, query refinement, hallucination checking, and self-correction loops.

🤖 [2. Voice AI Assistant](./02-voice-ai-assistant)

[](02-voice-ai-assistant/assets/project_2.gif) [](https://fcyber-labs-voice-ai-assistant.streamlit.app/)

Voice AI Assistant featuring real-time speech recognition, ultra-fast Groq inference, natural voice synthesis, and downloadable audio responses.

🎧 [3. AI News Podcast Generator - AI DAILY DIGEST](./03-ai-podcast-generator)

[](03-ai-podcast-generator/assets/project3_demo.gif) [](https://huggingface.co/spaces/fcyber/ai-podcast)

AI Podcast Generator transforms top AI news headlines into fully-produced podcast episodes automatically. Simply enter URLs of AI news sources, and the app scrapes, summarizes, and converts the content into a professional podcast script with downloadable MP3 audio. Choose your source - either extract the best AI news from top 50 websites or discover trending stories from HackerNews.

📺 [4. YouTubeScriptMaster](./04-YouTubeScriptMaster)

[](assets/project4-demo.gif) [](https://huggingface.co/spaces/fcyber/YouTubeScriptMaster)

Automatically generate structured scripts from any YouTube link with YouTube Summary Master. The system intelligently chunks long videos, extracts metadata, and creates rich summaries including executive overviews, TL;DR, semantic sections, key insights, and named entities – all in a beautifully formatted markdown document. Choose between lightning-fast Groq API or privacy-focused local BART processing, then download both summary and raw transcript with one click.

👨‍🎨 [5. AI Presentation Generator](./05-ai-presentation-generator)

[](assets/project5-demo.gif) [](https://huggingface.co/spaces/fcyber/YouTubeScriptMaster)

AI Presentation Generator is an AI-powered presentation engine that transforms raw text into polished, executive-ready PowerPoint decks using a structured LangGraph pipeline. It extracts key insights, organizes content into compelling narratives, generates concise summaries, and enhances each slide with AI-generated visuals and modern glassmorphism design. The result is a high-impact, visually consistent .pptx presentation that rivals professional-grade work—delivering one clear, memorable takeaway per slide.

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🚧 More Projects Coming Soon

🔮 Planned Projects (Click to Expand)

| Project | Description | Status | | :--- | :--- | :--- | | 🗣️ Voice RAG Agent | Voice-enabled Q&A with real-time transcription | Planned | | 🌐 MCP Browser Agent | Browser automation with Model Context Protocol | Planned | | 🤝 Multi-Agent Research | Collaborative research agents with handoffs | Planned | | 📄 Chat with PDF | Document Q&A with hybrid search | Planned | | 💬 Stateful Memory | Conversational AI with persistent memory | Planned |

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🚀 Getting Started

🎯 Quick Start Comparison (Updated)

| Method | Command | Time | Requires | |--------|---------|------|----------| | Python | pip install -r requirements.txt && python app.py | 2-5 min | Python 3.9+ | | Docker | docker-compose up -d | 30 sec | Docker + Compose | | Hugging Face | [](https://huggingface.co/spaces/fcyber/agentic_rag) | 1 sec | Web browser |

📦 Option 1: Python (Local Setup)

1. Clone the repository

``bash git clone https://github.com/fcyber-labs/ai-engineering-hub.git ``

1. Navigate to the desired project directory

``bash cd ai-engineering-hub/01-agentic-rag-assistant ``

1. Install the required dependencies

``bash pip install -r requirements.txt ``

1. Run Python apps

``bash python app.py ``

Follow the project-specific instructions in each project's README.md file to set up and run the app.

• • •

🐳 Option 2: Docker Compose (Recommended)

[](https://hub.docker.com/r/fcyber/agentic-rag-assistant) [](https://docs.docker.com/compose/)

1. Clone the repository

git clone https://github.com/fcyber-labs/ai-engineering-hub.git

1. Navigate to the desired project directory

cd ai-engineering-hub/01-agentic-rag-assistant

1. Set up environment variables

cp .env.example .env
# Edit .env with your GROQ_API_KEY keys

1. Run with Docker Compose

docker-compose up -d

1. View logs (optional)

docker-compose logs -f

1. Open in browser

http://localhost:7860

1. Stop the container

docker-compose down

That's it! The project includes a pre-configured Dockerfile and docker-compose.yml — no additional setup needed.

• • •

🤗 Option 3: Hugging Face Spaces

[](https://huggingface.co/spaces/fcyber/)

# No installation needed! Click the badge above to try the live demo.
# Or clone and run locally:
pip install huggingface-hub
huggingface-cli download fcyber/agentic-rag-assistant
python app.py  # Gradio apps run with python

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📝 Article

I wrote an article related to this project:

• Why Integrating Apple’s Ecosystem into a Local RAG Project Is Harder Than It Looks

This article explores the real-world challenges of integrating Apple’s CLaRa-7B-Instruct into a local RAG system. While the model offers impressive compression and reasoning capabilities, running it locally introduces significant hardware, architectural, and deployment complexity. I break down what made it difficult and what I learned from the process.

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🛠️ Technology Stack

| Category | Technologies | | --- | --- | | LLM Frameworks | LangChain, LangGraph, LlamaIndex | | Models | GPT-4, Claude 3.5, Sonnet, Gemini 1.5 Pro, Llama 3.1, Qwen 2.5 | | Vector Databases | Pinecone, Chroma, Weaviate, Qdrant | | Embeddings | OpenAI, Cohere, HuggingFace, Voyage | | Frontend | Streamlit, Gradio, Chainlit | | Monitoring | LangSmith, Arize Phoenix, Weights & Biases | | Deployment | Streamlit Cloud, Hugging Face Spaces, Docker, AWS |

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🤝 Contributing

We welcome contributions! Please follow these steps:

• Fork the repository
• Create a feature branch

``bash git checkout -b feature/amazing-project ``

• Commit your changes

``bash git commit -am 'Add amazing project' ``

• Push to the branch

``bash git push origin feature/amazing-project ``

• Open a Pull Request

✅ Contribution Checklist

• Self-contained project directory
• Comprehensive README with setup instructions

-Working demo with clear setup steps -.env.example with all required variables -requirements.txt with pinned versions -Screenshots demonstrating functionality ---

🙏 Thank You, Community, for the Support!

⭐ Star this repository if you find it useful! ⭐

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📊 Repository Stats

| ⭐ Stars | 🍴 Forks | 👀 Watchers | |:-----------:|:-----------:|:--------------:| | [](https://github.com/fcyber-labs/ai-engineering-hub/stargazers) | [](https://github.com/fcyber-labs/ai-engineering-hub/network/members) | [](https://github.com/fcyber-labs/ai-engineering-hub/watchers) |

| 🐛 Issues | 🔀 PRs | 📦 Releases | |:------------:|:----------:|:---------------:| | [](https://github.com/fcyber-labs/ai-engineering-hub/issues) | [](https://github.com/fcyber-labs/ai-engineering-hub/pulls) | [](https://github.com/fcyber-labs/ai-engineering-hub/releases) |

| 👥 Contributors | 📅 Last Commit | 📝 License | |:------------------:|:------------------:|:--------------:| | [](https://github.com/fcyber-labs/ai-engineering-hub/graphs/contributors) | [](https://github.com/fcyber-labs/ai-engineering-hub/commits/main) | [](https://github.com/fcyber-labs/ai-engineering-hub/blob/main/LICENSE) |

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[](https://star-history.com/#fcyber-labs/ai-engineering-hub&Date) --- Built with ❤️ by AI Engineers for AI Engineers

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: fcyber-labs
• Source: fcyber-labs/ai-engineering-hub
• License: MIT

Install and usage instructions live in the source repository linked above.