Data Curation for Post-Training & Structured Data Extraction
### Installation
```bash
pip install bespokelabs-curator
```
### Usage
```python
from bespokelabs import curator
import os
os.environ['OPENAI_API_KEY'] = 'sk-...' # Set your OpenAI API key here
poet = curator.Prompter(
prompt_func=lambda: "Write a poem about the beauty of computer science",
model_name="gpt-4o-mini",
)
poem = poet()
print(poem["response"][0])
```
You can see more examples in the [examples](examples) directory.
To run the examples, make sure to set your OpenAI API key in the environment variable `OPENAI_API_KEY` by running `export OPENAI_API_KEY=sk-...` in your terminal.
## Bespoke Curator Viewer
To run the bespoke dataset viewer:
```bash
curator-viewer
```
This will pop up a browser window with the viewer running on `127.0.0.1:3000` by default if you haven't specified a different host and port.
Optional parameters to run the viewer on a different host and port:
```bash
>>> curator-viewer -h
usage: curator-viewer [-h] [--host HOST] [--port PORT] [--verbose]
Curator Viewer
options:
-h, --help show this help message and exit
--host HOST Host to run the server on (default: localhost)
--port PORT Port to run the server on (default: 3000)
--verbose, -v Enables debug logging for more verbose output
```
The only requirement for running `curator-viewer` is to install node. You can install them by following the instructions [here](https://nodejs.org/en/download/package-manager).
For example, to check if you have node installed, you can run:
```bash
node -v
```
If it's not installed, installing latest node on MacOS, you can run:
```bash
# installs nvm (Node Version Manager)
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.0/install.sh | bash
# download and install Node.js (you may need to restart the terminal)
nvm install 22
# verifies the right Node.js version is in the environment
node -v # should print `v22.11.0`
# verifies the right npm version is in the environment
npm -v # should print `10.9.0`
```
