O'Reilly Live Trainining - Getting Started with LLM Agents using LangChain

Setup

Conda

• Install anaconda
• This repo was tested on a Mac with python=3.10.
• Create an environment: conda create -n oreilly-agents python=3.10
• Activate your environment with: conda activate oreilly-agents
• Install requirements with: pip install -r requirements/requirements.txt
• Setup your openai API key

Pip

1. Create a Virtual Environment: Navigate to your project directory. Make sure you have python3.10 installed! If using Python 3's built-in venv: python -m venv oreilly-agents If you're using virtualenv: virtualenv oreilly-agents

2. Activate the Virtual Environment:

   • On Windows:: .\oreilly-agents\Scripts\activate
   • On macOS and Linux:: source oreilly-agents/bin/activate

3. Install Dependencies from requirements.txt:

   pip install python-dotenv
   pip install -r ./requirements/requirements.txt

4. Setup your openai API key

Remember to deactivate the virtual environment afterwards: deactivate

Setup your .env file

• Change the .env.example file to .env and add your OpenAI API key.

OPENAI_API_KEY=<your openai api key>

To use this Environment with Jupyter Notebooks:

• conda install jupyter -y
• python -m ipykernel install --user --name=oreilly-agents

Notebooks

Here are the notebooks available in the notebooks/ folder:

1. Intro Agents

2. Intro Agents OpenAI Functions

3. Intro LangChain

4. Intro Agents with LangChain

5. Building LLM Agents with LangChain

6. Simple RAG Agent with LangChain

7. LangChain GitHub Agent Prototype

8. Building a Simple Research Agent