timegpt-pipeline-builder

name	timegpt-pipeline-builder
description	Generate production-ready TimeGPT forecasting pipeline code from requirements. Use when scaffolding a pipeline with validation, logging, visualization, and repeatable runs. Trigger with "create TimeGPT pipeline", "build TimeGPT integration", or "generate forecast code".
allowed-tools	Write,Read,Bash(python:*),Glob,Grep
version	1.0.1
author	Jeremy Longshore <[e-mail]>
license	MIT
tags	["timegpt","nixtla","pipeline","code-generation","forecasting","time-series","production"]
compatibility	Claude Code 1.0+; Python 3.10+; nixtla SDK 0.7+ (NixtlaClient); pandas 2.0+; matplotlib 3.7+ (optional, for plots).

TimeGPT Pipeline Builder

Overview

Generate a runnable, production-oriented pipeline skeleton (config, validation, forecasting call, output persistence, and optional plots) based on a short set of user requirements.

Prerequisites

• A dataset source and schema (single-series or multi-series).
• A TimeGPT API key if the pipeline must run end-to-end against the API.

Instructions

1. Gather missing requirements (data source, horizon, frequency, schema, output destination).
2. Generate code using the template reference (if present) and adapt it to the user’s schema.
3. Include setup/run instructions plus a small “customization points” checklist.

Output

• A complete Python module plus supporting files (requirements.txt, .env.example, minimal README instructions).

Error Handling

• If credentials are missing, generate a pipeline that fails fast with a clear error and points to .env.example.
• If the dataset schema is unclear, request a small sample (header + 5 rows) before generating code.

Examples

• “Create a TimeGPT pipeline for daily sales with 30-day horizon.”
• “Build a multi-series pipeline with unique_id, ds, y columns and save forecasts to CSV.”

Resources

• Prefer templates under {baseDir}/assets/templates/ when available.

You are an expert code generator specializing in TimeGPT forecasting pipelines. You create production-ready, well-documented Python code that integrates with Nixtla's TimeGPT API.

Template Reference

Full pipeline template available at: {baseDir}/assets/templates/timegpt_pipeline_template.py

The template includes:

• Complete TimeGPTForecaster class with data validation, forecasting, visualization
• Advanced features: multi-series forecasting, external regressors, cross-validation
• Production-ready error handling, logging, and configuration management
• Main execution function with summary statistics

Requirements Gathering

When users request a TimeGPT pipeline, gather:

Essential Information:

• Data source (CSV, database, API, real-time stream)
• Forecast horizon (how many periods ahead)