GenAI Projects

A collection of Generative AI projects demonstrating LLM chains, Streamlit applications, and Google GenAI integration.

Prerequisites

• Python 3.8+
• pip (Python package manager)
• Windows/Linux/macOS

Project Structure

GenAI/
├── project_01_basic_llm_chain/
│   └── app.ipynb
├── env-example.md
└── Readme.md

Setup Instructions

1. Install UV (Package Manager)

Install UV globally using pip:

pip install uv

2. Create Virtual Environment

Create a virtual environment using UV:

uv venv

3. Activate Virtual Environment

Windows:

.\venv\Scripts\activate

macOS/Linux:

source venv/bin/activate

4. Install Required Dependencies

Install the core dependencies for LangChain, Google GenAI, and Streamlit:

uv pip install streamlit langchain-google-genai google-genai python-dotenv

5. Install Jupyter (Optional)

If you plan to work with Jupyter notebooks:

uv pip install jupyter ipykernel

Getting Started

1. Navigate to the project directory
2. Ensure your virtual environment is activated
3. Create a .env file based on env-example.md with your API credentials
4. Run Jupyter notebooks or Streamlit apps as needed

Usage

Running Jupyter Notebooks

jupyter notebook

Navigate to project_01_basic_llm_chain/app.ipynb

Running Streamlit Applications

streamlit run app.py

Dependencies

• streamlit: Web app framework
• langchain-google-genai: LangChain integration with Google Generative AI
• google-genai: Google's generative AI SDK
• python-dotenv: Environment variable management
• jupyter: Interactive notebook environment (optional)
• ipykernel: IPython kernel for Jupyter (optional)

Environment Configuration

Create a .env file in the root directory with your API keys:

GOOGLE_API_KEY=your_api_key_here

Refer to env-example.md for additional configuration options.

Support

For issues or questions, please refer to the documentation of the respective libraries:

• LangChain Documentation
• Google GenAI Documentation
• Streamlit Documentation