This repository, gpsandhu23/llm_intro_notebooks, contains a series of Jupyter notebooks designed to introduce and explore various aspects of Language Learning Models (LLMs). The notebooks cover a range of topics including:
- Introduction to LLMs
- Summarization techniques
- Building chat applications
- Retrieval Augmented Generation (RAG)
- Schema extraction
- Tools for LLMs
- Building AI agents
Each notebook is self-contained and provides a hands-on approach to learning about LLMs.
To get started with these notebooks, you will need to set up your environment:
- Clone this repository to your local machine.
- Install the required dependencies listed in
requirements.txtby runningpip install -r requirements.txt. - Ensure you have Jupyter installed to run the notebooks. If not, it can be installed via pip with
pip install jupyter.
Some notebooks require API keys to access external services like OpenAI, Langchain, and Google API. To set these up:
- Copy the
.env_examplefile to a new file named.env. - Fill in the
.envfile with your API keys.
Contributions to this repository are welcome! If you have suggestions for improvements or new features, feel free to open an issue or submit a pull request.