Supply chain risk monitoring — check CPI, commodity prices, freight rates, trade data, and global news to assess risk for any commodity. Uses Yahoo Finance, FRED, Commodities-API, UN Comtrade, World Bank, NewsData, and Gemini AI. Covers 20 items across 8 categories (construction, energy, food, electronics, packaging, chemicals, textiles, electrical). Bring your own API keys (free tiers available). Trigger keywords: supply chain, risk, CPI, freight, import, export, trade, commodity, price trend, supply disruption, shipping cost, inflation, economic indicator.

upstream-alert — Supply Chain Risk Monitor

Installation

pip install upstream-alert

Environment Variables

Set API keys before use. Only GEMINI_API_KEY is required; World Bank and Yahoo Finance work without keys.

# Required
export GEMINI_API_KEY="your_gemini_key"

# Optional (enables more data sources)
# Yahoo Finance: no key needed — daily commodity futures (copper, aluminum, soybean, cotton, coffee)
# Install with: pip install upstream-alert[yahoo]
export FRED_API_KEY="your_fred_key"                    # https://fred.stlouisfed.org/docs/api/api_key.html
export COMMODITIES_API_KEY="your_commodities_key"      # https://commodities-api.com/ (100 req/month free)
export COMTRADE_API_KEY="your_comtrade_key"            # https://comtradeplus.un.org/
export NEWSDATA_API_KEY="your_newsdata_key"            # https://newsdata.io/
export FBX_API_KEY="your_fbx_key"                      # Paid: $119/mo

Supported Item Categories (20 items)

Category	Examples
建材 (Construction)	鋼筋, 合板, 水泥
機電 (Electrical)	電線電纜
能源 (Energy)	柴油, 汽油, 天然氣
食品原料 (Food)	黃豆, 麵粉, 棕櫚油, 砂糖, 咖啡豆
電子零件 (Electronics)	晶片 MCU, 被動元件
包材 (Packaging)	瓦楞紙箱, PE 膜
化工 (Chemicals)	塑膠粒, 工業酒精
紡織 (Textiles)	棉紗, 滌綸纖維

Usage

CLI Commands

# Risk check (human readable)
upstream-alert check "咖啡豆" --country TW

# Risk check (JSON output)
upstream-alert check "semiconductor" --country US -j

# Market pulse
upstream-alert pulse --country JP

# Show configured data sources
upstream-alert sources

Python API

from upstream_alert import check_risk, RiskEngine

# One-liner
result = check_risk("coffee", country="US")
print(result.score)       # 45
print(result.level)       # RiskLevel.MEDIUM
print(result.ai_summary)  # AI-generated analysis

# Full control
engine = RiskEngine(fred_key="...", gemini_key="...")
result = engine.check("半導體", country="TW")

Output Format (JSON)

{
  "item": "coffee",
  "country": "US",
  "score": 45,
  "level": "medium",
  "ai_summary": "Risk assessment for coffee (US): ...",
  "sources_used": ["fred", "commodities_api", "newsdata"],
  "market_pulse": {
    "cpi_change": 2.1,
    "commodity_price": 5.62,
    "freight": { "index": 2150.0, "change_pct": -1.5 }
  }
}

When to Use

Use when the user asks about:

Supply chain risks for a product or commodity
Real-time commodity prices (metals, energy, food, textiles)
Price trends (CPI, PPI, inflation data)
Shipping / freight cost trends
Trade data for imports/exports
Economic indicators for a country
News analysis related to supply chain disruptions

Trigger Keywords

supply chain, risk, CPI, freight, import, export, trade, commodity, price trend, supply disruption, shipping cost, inflation, PMI, economic indicator, commodity price