RAG-Buddy Python Scripts

Assumptions

• This Quickstart assumes the following prerequisites are met:

1. You have an active OpenAI API key. If you do not possess one, please obtain it from OpenAI. You are using the OpenAI Python client. Installation and setup instructions can be found in the repository. Your use case involves RAG with the generation of a single citation within the response.

2. Navigate to the python directory cd python

3. Python and pip installed in your system. pipenv installed, if not execute pip install pipenv

4. Download the necessary packages and create the pipenv using pipenv install

5. Activate the pipenv using pipenv shell

Create a Cache

To begin using RAG-Buddy, a new project must be created. If you haven’t set up a project yet, follow these steps:

Visit the RAG-Buddy Console and sign up for an account if you don’t already have one.

1. Once you’re signed in:

   1. On your console, click [Create a new project].
   2. Name your project.
   3. Select OpenAI:ADA2 as your embedding model.
   4. Select OpenAI Chat Completions API as your LLM provider.
   5. Select the 'RAG+Citation' cache type.
   6. Click Create Project to create your project.

2. Next, you’ll need an API key for your cache:

   1. Navigate to the Services tab.
   2. Scroll down to the API Keys for Cache section.
   3. Click on Create new key.
   4. Assign a name to your key and select Create API Key.
   5. Copy the newly generated API key for use in the next step.

3. Copy the .env.sample file and create a .env by executing cp .env.sample .env. Then fill in the required environmental variables.

For more information regarding each use case, consider having a look at our documentation.