box-openai-responses-ai-agent

The OpenAI Responses API will allow developers to inject additional data into the response. This includes web search, computer use, and other types of data. This repository shows how to use this new capability and a Box Agent to add proprietary unstructured data from your Box instance into your agentic work.

Setup

Clone this repo:

git clone https://github.com/box-community/doc-gen-ai-workshop.git

Create a python virtual environment and activate it:

python3.13 -m venv .venv
source .venv/bin/activate

Install the requirements:

pip install --upgrade pip
pip install -r requirements.txt

You will also need to set up your environment. First you will need a Box Platform app using Client Credentials Grant for authorization. You will also need to install and enable that app in your admin console.

Once that is done, create a file called .env at the root level of this project and add the following values:

BOX_CLIENT_ID=your_box_client_id
BOX_CLIENT_SECRET=your_box_client_secret
BOX_SUBJECT_TYPE=user
BOX_SUBJECT_ID=your_box_user_id

You can also set BOX_SUBJECT_TYPE to enterprise and replace your_box_user_id with your_box_enterprise_id.

Finally, you will need to open a terminal window and in that shell, set your OpenAI API key to an environment variable with the following command:

export OPENAI_API_KEY=your_openai_api_key

Now in that terminal window, just run:

python main.py

The available tools you have at your disposal from Box in this example are:

• file_search - search all of Box for files
• ask_box - use the Box AI /ask endpoint
• get_text_from_file - get a text representation of your file
• box_search_folder_by_name - Find a folder by its name
• box_list_folder_content_by_folder_id - List all the files in a given folder