This repository contains a collection of Jupyter notebooks demonstrating various use cases of Generative AI technologies.
genai-samples/
├── notebooks/ # Main directory for all Jupyter notebooks
│ ├── 0-preprocessing/ # Data preprocessing examples
│ │ ├── markdown_conversion/ # Text to markdown conversion examples
│ │ ├── rag/ # Retrieval Augmented Generation examples
│ │ └── web-scrapping/ # Web scraping examples
│ └── 3-agents/ # AI Agent examples
│ ├── autogen-agent/ # AutoGen Agent examples
│ └── qwen-agent/ # Qwen Agent examples with code interpreter
├── data/ # Sample data for notebooks
│ └── raw/ # Raw input data
└── .env.sample # Template for environment variables
- Clone this repository
- Create a virtual environment:
python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Copy
.env.sample
to.env
and fill in your API keys
- Markdown Conversion: Convert various document formats to markdown using LLMs
- RAG (Retrieval Augmented Generation): Examples of implementing RAG systems
- Web Scraping: Web content extraction and analysis using LLMs
browser-use.ipynb
: Demonstrates how to use Browser-Use agent to control browser programmatically for web interactions and data extractioncrawl4ai-sample.ipynb
: Shows how to use crawl4ai for AI-powered web crawling and content extraction with LLM capabilities
- AutoGen Agent: Examples using Microsoft's AutoGen framework
autogen-agent-example1.ipynb
: Demonstrates using AutoGen agents for web surfing and content summarization with multilingual capabilities
- Qwen Agent: Examples using Qwen's agent capabilities
qwen-agent-example.ipynb
: Demonstrates using Qwen agent with code interpreter, fact-checking, and article generation capabilities
Feel free to contribute new examples or improve existing ones through pull requests.
See the LICENSE file for details.