PyPI: https://pypi.org/project/okareo/

Python library for interacting with Okareo Cloud APIs

Getting Started, Guides, and API docs

1. Install the package

   pip install okareo

2. Get your API token from https://app.okareo.com/ (Note: You will need to register first.)

3. Go directly to the "2. Create your API Token" on the landing page in above app.

4. Set the environment variable OKAREO_API_KEY to your generated API token.

Please see and run this notebook:
https://github.com/okareo-ai/okareo-python-sdk/blob/main/examples/classification_eval.ipynb

See additional examples under:
https://github.com/okareo-ai/okareo-python-sdk/tree/main/examples

We provide a LangChain callback handler that lets you easily integrate your current workflows with the Okareo platform.

If don't have LangChain dependencies installed in your environment, you can install the base ones (that will help you run the examples) with:

pip install okareo[langchain]

Integrating callbacks into your chain is as easy as importing the SDK in your module add adding the following

from okareo.callbacks import CallbackHandler
...
handler = CallbackHandler(mut_name="my-model", context_token="context-token")
llm = OpenAI(temperature=0.3, callbacks=[handler])

During the LangChain LLM runs we will collect input and output information so you can analyze it further with the Okareo toolkit.

You can also see an usage example in ./examples/langchain_callback_example.py

To render the Python SDK documentation, you can use source/build_docs.sh in this repository. This will do the following:

1. Install the SDK poetry environment
2. Run pydoc-markdown as configured in pyproject.toml
3. Perform postprocessing to re-order the generated sidebar file and change heading levels.

The generated docs will be found in the docs/python-sdk and can be rendered with docusaurus.

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