greenlang-cli 0.3.0

Climate Intelligence Platform - Enterprise infrastructure with powerful SDK for climate-aware applications

GreenLang - The Climate Intelligence Platform

Enterprise-grade climate intelligence platform for building, deploying, and managing climate-aware applications. Infrastructure-first with a powerful SDK.

What is GreenLang?

GreenLang is the Climate Intelligence Platform that provides managed runtime primitives, governance, and distribution for climate-aware applications. Built infrastructure-first with a comprehensive SDK, GreenLang enables organizations to deploy, manage, and scale climate intelligence across their operations - from smart buildings and HVAC systems to industrial processes and renewable energy optimization.

Platform Capabilities

Infrastructure & Runtime:

• Managed Runtime: Deploy packs with versioning, autoscaling, and isolation
• Policy Governance: RBAC, capability-based security, and audit logging
• Pack Registry: Signed, versioned components with SBOM and dependencies
• Multi-Backend Support: Local, Docker, and Kubernetes deployment options
• Observability: Built-in metrics, tracing, and performance monitoring

Developer SDK & Framework:

• AI-Powered Agents: 15+ specialized climate intelligence components
• Composable Packs: Modular, reusable building blocks for rapid development
• YAML Pipelines: Declarative workflows with conditional logic
• Type-Safe Python SDK: 100% typed interfaces with strict validation
• Global Coverage: Localized emission factors for 12+ major economies

Installation

# Basic installation
pip install greenlang-cli

# With analytics capabilities
pip install greenlang-cli[analytics]

# Full feature set
pip install greenlang-cli[full]

# Development environment
pip install greenlang-cli[dev]

Quick Start

CLI Usage

# Initialize a new GreenLang project
gl init my-climate-app

# Create a new pack for emissions calculation
gl pack new building-emissions

# Run emissions analysis
gl calc --building office_complex.json

# Analyze with recommendations
gl analyze results.json --format detailed

# Execute a pipeline
gl pipeline run decarbonization.yaml

Python SDK

from greenlang import GreenLang
from greenlang.models import Building, EmissionFactors
from greenlang.agents import BuildingAgent, HVACOptimizer

# Initialize GreenLang
gl = GreenLang()

# Create a building model
building = Building(
    name="Tech Campus A",
    area_m2=50000,
    location="San Francisco",
    building_type="office"
)

# Calculate emissions
agent = BuildingAgent()
results = agent.calculate_emissions(
    building=building,
    energy_data=energy_consumption,
    emission_factors=EmissionFactors.get_region("US-CA")
)

# Get optimization recommendations
optimizer = HVACOptimizer()
recommendations = optimizer.optimize(
    building=building,
    current_emissions=results.total_emissions,
    target_reduction=0.30  # 30% reduction target
)

print(f"Current emissions: {results.total_emissions} tCO2e/year")
print(f"Potential savings: ${recommendations.estimated_savings:,.2f}")

YAML Pipelines

# decarbonization_pipeline.yaml
version: "1.0"
name: "Building Decarbonization Analysis"

stages:
  - name: data_collection
    type: ingestion
    sources:
      - type: energy_bills
        format: csv
      - type: occupancy_sensors
        format: json

  - name: emissions_calculation
    type: calculation
    agent: BuildingAgent
    parameters:
      include_scope3: true
      use_regional_factors: true

  - name: optimization
    type: analysis
    agent: DecarbonizationAgent
    parameters:
      target_reduction: 0.40
      max_payback_years: 5

  - name: reporting
    type: output
    format: pdf
    template: executive_summary

Core Concepts

Packs

Modular, reusable components that encapsulate climate intelligence logic:

• Calculation Packs: Emissions calculations for specific industries
• Optimization Packs: Decarbonization strategies and recommendations
• Integration Packs: Connect to external data sources and APIs
• Reporting Packs: Generate customized sustainability reports

Agents

AI-powered components that provide intelligent climate analysis:

• BuildingAgent: Comprehensive building emissions analysis
• HVACOptimizer: HVAC system optimization recommendations
• SolarThermalAgent: Solar thermal replacement calculations
• PolicyAgent: Climate policy compliance checking
• BenchmarkAgent: Industry and regional benchmarking

Pipelines

Orchestrate complex climate intelligence workflows:

• Chain multiple agents and packs together
• Define conditional logic and branching
• Integrate with external systems
• Schedule recurring analyses
• Generate automated reports

Real-World Applications

Smart Buildings

• Real-time emissions monitoring and alerting
• Predictive maintenance for HVAC systems
• Occupancy-based energy optimization
• Automated sustainability reporting

Industrial Decarbonization

• Process emissions calculation
• Energy efficiency recommendations
• Alternative fuel analysis
• Supply chain emissions tracking

Renewable Energy Planning

• Solar thermal viability assessment
• Boiler replacement analysis
• Grid carbon intensity integration
• ROI calculations for green investments

Platform Metrics & Status

Documentation

• Platform Documentation
• SDK & API Reference
• Pack Development Guide
• Deployment Guide
• Contributing Guide

Community & Support

• Discord: Join our community
• GitHub Issues: Report bugs or request features
• Stack Overflow: Tag questions with greenlang
• Twitter: @GreenLangAI

Why GreenLang Platform?

Enterprise Infrastructure

• Production-Ready: Managed runtime with SLOs, versioning, and rollback
• Governance & Security: RBAC, audit trails, signed artifacts with SBOM
• Scale & Performance: Autoscaling, P95 < 5ms response times
• Multi-Tenancy: Org isolation, resource quotas, usage analytics

Developer Experience

• 10x Faster Development: Pre-built climate components and SDK
• Platform + Framework: Infrastructure for ops, SDK for developers
• Best Practices Built-in: Industry standards and methodologies included
• Comprehensive Tooling: CLI, Python SDK, YAML workflows, debugging tools

Climate Impact

• Reduce Emissions: Data-driven insights with real reduction strategies
• Ensure Compliance: Meet regulatory requirements with audit trails
• Transparent Reporting: Explainable, verifiable calculations
• Scale Impact: From single buildings to entire enterprise portfolios

Platform Roadmap

Current Release (v0.3.0) - Foundation

• ✅ Core platform architecture with pack system
• ✅ CLI and Python SDK for developers
• ✅ 15+ climate intelligence agents
• ✅ SBOM generation and security framework
• ✅ Local and Docker runtime support

Q1 2025 - Platform Services

• Managed runtime (beta): autoscaling, versioned deploys, org isolation
• Durable state: run history, checkpoints, replay capabilities
• Pack registry (alpha): semver, signing, install analytics
• Enhanced observability: OTel integration, cost dashboards

Q2 2025 - Enterprise Features

• Full Kubernetes operator with CRDs
• Multi-tenancy with resource isolation
• Advanced policy engine with OPA
• SLA guarantees and status page

v1.0.0 - Production Platform

• 50+ official packs in registry
• Global emission factor service
• ML-powered optimization engine
• Enterprise support and SLAs

Contributing

We welcome contributions from the community! See our Contributing Guide for details on:

• Setting up development environment
• Code style and standards
• Testing requirements
• Submission process

License

GreenLang is released under the MIT License. See LICENSE file for details.

Acknowledgments

GreenLang is built on the shoulders of giants:

• Climate science community for methodologies
• Open source community for inspiration
• Early adopters for invaluable feedback
• Contributors who make this possible

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Join us in building the climate-intelligent future. Every line of code counts.

Code Green. Deploy Clean. Save Tomorrow.