Clayton Young
6c44413b7f
Add a self-contained AI agent skill for TimesFM that teaches coding agents (Claude Code, OpenCode, Cursor, Codex) how to use the TimesFM API correctly — safe model loading, zero-shot forecasting, covariate workflows, anomaly detection, and the most common pitfalls. Files added: - AGENTS.md — auto-loaded skill document (root of repo) - claude-skill/scripts/check_system.py — mandatory preflight RAM/GPU/disk checker - claude-skill/scripts/forecast_csv.py — CLI wrapper for CSV forecasting - claude-skill/references/ — ForecastConfig API ref, data prep, HW reqs - claude-skill/examples/global-temperature/ — basic forecast + PNG/GIF pipeline - claude-skill/examples/anomaly-detection/ — two-phase detrend+Z-score + quantile PI - claude-skill/examples/covariates-forecasting/ — forecast_with_covariates() XReg demo - .gitattributes — Git LFS rules for PNG/GIF binary outputs Contributed by Clayton Young / Superior Byte Works LLC (@borealBytes) Apache 2.0 — same license as this repository
54 lines
1.5 KiB
Bash
Executable File
54 lines
1.5 KiB
Bash
Executable File
#!/bin/bash
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# run_example.sh - Run the TimesFM temperature anomaly forecasting example
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#
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# This script:
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# 1. Runs the preflight system check
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# 2. Runs the TimesFM forecast
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# 3. Generates the visualization
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#
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# Usage:
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# ./run_example.sh
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#
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# Prerequisites:
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# - Python 3.10+
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# - timesfm[torch] installed: uv pip install "timesfm[torch]"
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# - matplotlib, pandas, numpy
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set -e
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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SKILL_ROOT="$(dirname "$(dirname "$SCRIPT_DIR")")"
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echo "============================================================"
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echo " TimesFM Example: Global Temperature Anomaly Forecast"
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echo "============================================================"
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# Step 1: Preflight check
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echo ""
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echo "🔍 Step 1: Running preflight system check..."
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python3 "$SKILL_ROOT/scripts/check_system.py" || {
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echo "❌ Preflight check failed. Please fix the issues above before continuing."
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exit 1
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}
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# Step 2: Run forecast
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echo ""
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echo "📊 Step 2: Running TimesFM forecast..."
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cd "$SCRIPT_DIR"
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python3 run_forecast.py
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# Step 3: Generate visualization
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echo ""
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echo "📈 Step 3: Generating visualization..."
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python3 visualize_forecast.py
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echo ""
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echo "============================================================"
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echo " ✅ Example complete!"
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echo "============================================================"
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echo ""
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echo "Output files:"
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echo " - $SCRIPT_DIR/output/forecast_output.csv"
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echo " - $SCRIPT_DIR/output/forecast_output.json"
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echo " - $SCRIPT_DIR/output/forecast_visualization.png"
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