Notebooks

Cog plays nicely with Jupyter notebooks.

Install the jupyterlab Python package

First, add jupyterlab to your requirements.txt file and reference it in cog.yaml:

requirements.txt:

jupyterlab

cog.yaml:

build:
  python_requirements: requirements.txt

Run a notebook

Cog can run notebooks in the environment you've defined in cog.yaml with the following command:

cog exec -p 8888 jupyter lab --allow-root --ip=0.0.0.0

Use notebook code in your predictor

You can also import a notebook into your Cog Predictor file.

First, export your notebook to a Python file:

jupyter nbconvert --to script my_notebook.ipynb # creates my_notebook.py

Then import the exported Python script into your predict.py file. Any functions or variables defined in your notebook will be available to your predictor:

from cog import BasePredictor, Input

import my_notebook

class Predictor(BasePredictor):
    def predict(self, prompt: str = Input(description="string prompt")) -> str:
      output = my_notebook.do_stuff(prompt)
      return output