Does this skill modify my files directly?

It provides scripts to apply changes and can modify source code via the 'Apply migration' step, but it is recommended to review all changes before committing to version control.

Which Python packages are required for this migration?

You will need nixtla, pandas, matplotlib, statsforecast, and pyyaml installed in your environment.

What are the primary changes handled by the migrator?

The migrator primarily handles the transition from the legacy TimeGPT class to the NixtlaClient, updates method calls like forecast(), and ensures data schemas align with the new standard columns.

How do I provide my API key?

The migration tools utilize the NIXTLA_TIMEGPT_API_KEY environment variable to ensure secure access during validation and configuration steps.

Can I validate my data before migrating the code?

Yes, the skill includes a compatibility check script that validates your CSV data schema and data types specifically for TimeGPT-2 requirements.

TimeGPT-2 Migration Assistant

Name: TimeGPT-2 Migration Assistant
Author: intent-solutions-io

byintent-solutions-io

データサイエンスとML

Automates the transition of time-series forecasting pipelines from TimeGPT-1 to the enhanced TimeGPT-2 architecture.

概要

The TimeGPT-2 Migration Assistant streamlines the process of upgrading legacy Nixtla TimeGPT implementations to the latest version. It performs automated codebase scans to detect deprecated patterns, validates data schemas against new requirements, and applies intelligent code transformations—such as replacing the legacy TimeGPT class with the modern NixtlaClient. By generating detailed migration reports and updated configuration files, it minimizes downtime and ensures forecasting models leverage the performance improvements and feature set of TimeGPT-2.

主な機能

Intelligent code replacement for NixtlaClient initialization
Automated YAML configuration generation for TimeGPT-2
0 GitHub stars
Automated codebase scanning for legacy TimeGPT-1 API calls
Detailed migration reports summarizing required changes
Data schema validation for unique_id, ds, and y column requirements

ユースケース

Auditing enterprise repositories for TimeGPT-1 dependencies
Upgrading legacy forecasting pipelines to leverage TimeGPT-2 performance
Refactoring internal analytics tools relying on deprecated Nixtla methods

概要

主な機能

Intelligent code replacement for NixtlaClient initialization
Automated YAML configuration generation for TimeGPT-2
0 GitHub stars
Automated codebase scanning for legacy TimeGPT-1 API calls
Detailed migration reports summarizing required changes
Data schema validation for unique_id, ds, and y column requirements

ユースケース

Auditing enterprise repositories for TimeGPT-1 dependencies
Upgrading legacy forecasting pipelines to leverage TimeGPT-2 performance
Refactoring internal analytics tools relying on deprecated Nixtla methods