⚠️ Important Notice

This repository is deprecated and no longer maintained.

For the latest python examples, please refer to the llama-cloud-services repository examples: https://github.com/run-llama/llama_cloud_services/tree/main/examples

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LlamaCloud Demo

This repository contains a collection of cookbooks to show you how to build LLM applications using LlamaCloud to help manage your data pipelines, and LlamaIndex as the core orchestration framework.

Getting Started

1. Follow the instructions in the section below for setting up the Jupyter Environment.
2. Go to https://cloud.llamaindex.ai/ and create an account using one of the authentication providers.
3. Once logged in, go to the API Key page and create an API key. Copy that generated API key to your clipboard.
4. Go back to LlamaCloud. Create a project and initialize a new index by specifying the data source, data sink, embedding, and optionally transformation parameters.
5. Open one of the Jupyter notebooks in this repo (e.g. examples/getting_started.ipynb) and paste the API key into the first cell block that reads os.environ["PLATFORM_API_KEY"] = "..."
6. Copy the index_name and project_name from the deployed index into the LlamaCloudIndex initialization in the notebook.

That should get you started! You should now be able to create an e2e pipeline with a LlamaCloud pipeline as the backend.

Setting up the Jupyter Environment

Here's some commands for installing the Python dependencies & running Jupyter.

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
jupyter lab

Notebooks are in examples.

Note: if you encounter package issues when running notebook examples, please rm -rf .venv and repeat the above steps again.