Toloka-Kit is a powerful Python library designed to work with the Toloka API, allowing for the creation of scalable, automated human-in-the-loop machine learning (ML) pipelines. In this guide, we will walk you through how to get started with Toloka-Kit, troubleshoot common issues, and understand its applications—all wrapped up in user-friendly steps.

Getting Started with Toloka-Kit

Before diving into using Toloka-Kit, make sure you have met the following prerequisites:

• Python version 3.8 or higher installed on your system.
• You are registered in Toloka as a requester.
• Your Toloka account is topped up.
• You have set up an OAuth token to access the Toloka API.

Step 1: Install Toloka-Kit

Begin by installing the Toloka-Kit package. In your command shell, run:

$ pip install toloka-kit

For production environments, specify the exact package version. You can check the latest stable version on the project page at pypi.org.

Note: Starting with version 1.0.0, only the core version of the package is installed by default. You can add optional dependencies later as needed.

Step 2: Verify API Access

Next, you need to verify that you can access the API. Use the following Python script to check your connection:

import toloka.client as toloka
from getpass import getpass

# Uncomment one of the following two lines to specify where to send requests to: 
# target = SANDBOX
target = PRODUCTION

toloka_client = toloka.TolokaClient(getpass('Enter your token:'), target)
print(toloka_client.get_requester())

If the script runs without errors, congratulations! You’re all set up to use Toloka-Kit.

Step 3: Learn the Basics

It’s time to start using the Toloka API with Toloka-Kit. Head over to the Learn the Basics tutorial which will provide you with fundamental concepts and how to execute various tasks.

Optional Features and Dependencies

If you wish to install Toloka-Kit with all additional dependencies, you can run the following command:

$ pip install toloka-kit[all]

If you need specific dependencies, use:

$ pip install toloka-kit[pandas,autoquality,s3,zookeeper,jupyter-metrics]

Common Usage Examples

For examples demonstrating how to carry out specific data labeling tasks, visit our Toloka-kit usage examples. They show how to interact with the Toloka API using the Toloka-Kit effectively.

Troubleshooting

If you encounter issues while using Toloka-Kit, consider the following troubleshooting ideas:

• Ensure your Python version is compatible with Toloka-Kit.
• Verify that your OAuth token is correct and has been entered properly.
• Check your internet connection or access issues with the Toloka API.

For additional assistance, engage with our community or visit the Slack community for support.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.