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1 change: 1 addition & 0 deletions CNAME
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reference.openlayer.com
38 changes: 26 additions & 12 deletions _sources/index.rst.txt
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.. No Errors Test Project documentation master file, created by
sphinx-quickstart on Fri Aug 30 17:07:56 2019.
.. Openlayer Python API reference documentation master file, created by
sphinx-quickstart on Tue Apr 19 16:10:13 2022.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Welcome to No Errors Test Project's documentation!
==================================================
.. module:: openlayer

.. toctree::
:maxdepth: 2
:caption: Hello World!
*********************************
Openlayer Python Client reference
*********************************

**Date**: |today| **Version**: |version|

Welcome to the API documentation for `Openlayer <https://openlayer.com>`__!

These docs cover our official Python library, which you may use to interact with the Openlayer platform.

Installation
============

The :mod:`openlayer` library is available on PyPI and conda-forge, and can be installed with:

.. code:: console
Indices and tables
==================
$ pip install openlayer
.. code:: console
$ conda install openlayer --channel conda-forge
.. toctree::
:hidden:

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
reference/index
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openlayer.InferencePipeline.publish\_batch\_data
================================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.publish_batch_data
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openlayer.InferencePipeline.publish\_ground\_truths
===================================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.publish_ground_truths
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openlayer.InferencePipeline.stream\_data
========================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.stream_data
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openlayer.InferencePipeline.update\_data
========================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.update_data
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openlayer.InferencePipeline.upload\_reference\_dataframe
========================================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.upload_reference_dataframe
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openlayer.InferencePipeline.upload\_reference\_dataset
======================================================

.. currentmodule:: openlayer

.. automethod:: InferencePipeline.upload_reference_dataset
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openlayer.OpenlayerClient.create\_or\_load\_project
===================================================

.. currentmodule:: openlayer

.. automethod:: OpenlayerClient.create_or_load_project
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openlayer.OpenlayerClient.create\_project
=========================================

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.. automethod:: OpenlayerClient.create_project
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openlayer.OpenlayerClient.load\_project
=======================================

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.. automethod:: OpenlayerClient.load_project
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openlayer.OpenlayerClient.load\_project\_version
================================================

.. currentmodule:: openlayer

.. automethod:: OpenlayerClient.load_project_version
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openlayer.OpenlayerClient
=========================

.. currentmodule:: openlayer

.. autoclass:: OpenlayerClient
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openlayer.Project.add\_dataframe
================================

.. currentmodule:: openlayer

.. automethod:: Project.add_dataframe
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openlayer.Project.add\_dataset
==============================

.. currentmodule:: openlayer

.. automethod:: Project.add_dataset
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openlayer.Project.add\_model
============================

.. currentmodule:: openlayer

.. automethod:: Project.add_model
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openlayer.Project.commit
========================

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.. automethod:: Project.commit
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openlayer.Project.create\_inference\_pipeline
=============================================

.. currentmodule:: openlayer

.. automethod:: Project.create_inference_pipeline
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openlayer.Project.export
========================

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.. automethod:: Project.export
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openlayer.Project.load\_inference\_pipeline
===========================================

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.. automethod:: Project.load_inference_pipeline
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openlayer.Project.push
======================

.. currentmodule:: openlayer

.. automethod:: Project.push
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openlayer.Project.restore
=========================

.. currentmodule:: openlayer

.. automethod:: Project.restore
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openlayer.Project.status
========================

.. currentmodule:: openlayer

.. automethod:: Project.status
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openlayer.ProjectVersion
========================

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.. autoclass:: ProjectVersion
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openlayer.llm\_monitors.AzureOpenAIMonitor
==========================================

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.. autoclass:: AzureOpenAIMonitor
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openlayer.llm\_monitors.OpenAIMonitor
=====================================

.. currentmodule:: openlayer.llm_monitors

.. autoclass:: OpenAIMonitor
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openlayer.tasks.TaskType
========================

.. currentmodule:: openlayer.tasks

.. autoclass:: TaskType


.. automethod:: __init__






.. rubric:: Attributes

.. autosummary::

~TaskType.LLMNER
~TaskType.LLMQuestionAnswering
~TaskType.LLMSummarization
~TaskType.LLMTranslation
~TaskType.LLM
~TaskType.TabularClassification
~TaskType.TabularRegression
~TaskType.TextClassification


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openlayer.tracing.tracer.trace
==============================

.. currentmodule:: openlayer.tracing.tracer

.. autofunction:: trace
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.. _api.authentication:

==============
Authentication
==============
.. currentmodule:: openlayer

Openlayer uses API keys for client authentication. You can find your workspace API key on
your `Account settings <https://docs.openlayer.com/docs/how-to-guides/find-your-api-key>`_.

The authentication step happens when the ``OpenlayerClient`` is instantiated.

Client
------
.. autosummary::
:toctree: api/
:template: class.rst

OpenlayerClient
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.. _api.development:

===========
Development
===========
.. currentmodule:: openlayer

The development mode of a project helps you as you iterate on your models and datasets.
You will use the methods described on this page to add models and datasets to your
development project,

To use these methods, you must have:

1. Authenticated, using :obj:`openlayer.OpenlayerClient`

2. Created a project, using :obj:`openlayer.OpenlayerClient.create_project`

**Related guide**: `How to upload datasets and models for development <https://docs.openlayer.com/docs/how-to-guides/upload-datasets-and-models>`_.


Staging area
------------
The upload of models and datasets to a project on Openlayer follows a similar flow
to the one for uploading files to a version control system like Git.

The ``add_*`` methods, add models and datasets to the local staging area.
As you add resources to the staging area, you can check its status using the
``status`` method.


Finally, the resources on the staging area are committed and pushed to the Openlayer
platform using the ``commit`` and ``push`` methods.


Datasets
--------
Datasets stored as Pandas dataframes or csv files can be easily added to a project's
staging area with the methods below.

.. autosummary::
:toctree: api/
:template: class.rst

Project.add_dataset
Project.add_dataframe

Models
------
Models are added to the staging area using the ``add_model`` method.

.. autosummary::
:toctree: api/
:template: class.rst

Project.add_model

Committing and pushing
----------------------
After adding resources to the staging area, you can commit and push them to Openlayer.

.. autosummary::
:toctree: api/
:template: class.rst

Project.commit
Project.push

Other methods to interact with the staging area
-----------------------------------------------
Additional methods used to interact with the staging area.

.. autosummary::
:toctree: api/
:template: class.rst

Project.status
Project.restore
Project.export

Checking a project version's goal statuses
------------------------------------------
To programatically check the status of a project version's goals, use the
``ProjectVersion`` object, which can be obtained using the ``load_project_version`` method.

.. autosummary::
:toctree: api/
:template: class.rst

ProjectVersion
OpenlayerClient.load_project_version





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