The Climate Intelligence Framework - Build climate-aware applications with AI-driven orchestration
Project description
GreenLang - The Climate Intelligence Framework
Build climate-intelligent applications with the power of AI-driven orchestration. The LangChain of Climate Intelligence is here.
What is GreenLang?
GreenLang is a developer-first Climate Intelligence Framework that brings LangChain-style modularity to sustainable computing. It provides a comprehensive toolkit for building climate-aware applications across industries - from smart buildings and HVAC systems to industrial processes and renewable energy optimization.
Key Features
- AI-Powered Climate Intelligence: Intelligent agents for automated emissions analysis and optimization recommendations
- Modular Architecture: Composable packs and pipelines for rapid development
- Multi-Industry Support: Buildings, HVAC, solar thermal, cement, and expanding
- Global Coverage: Localized emission factors for 12+ major economies
- Developer-First Design: Clean CLI, Python SDK, and YAML workflows
- Type-Safe APIs: 100% typed public interfaces with strict validation
- Explainable Results: Transparent calculations with full audit trails
- Real-World Data: Integration with industry-standard datasets and benchmarks
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
Documentation
Community & Support
- Discord: Join our community
- GitHub Issues: Report bugs or request features
- Stack Overflow: Tag questions with
greenlang - Twitter: @GreenLangAI
Why GreenLang?
For Developers
- Rapid Development: Build climate apps in hours, not months
- Best Practices Built-in: Industry standards and methodologies included
- Extensible: Easy to add custom agents and packs
- Well-Documented: Comprehensive docs with real examples
For Organizations
- Reduce Emissions: Data-driven insights for real reduction
- Save Costs: Identify efficiency opportunities and ROI
- Ensure Compliance: Meet regulatory requirements
- Transparent Reporting: Explainable, auditable calculations
For the Planet
- Accelerate Net-Zero: Enable faster climate action
- Democratize Climate Intelligence: Make tools accessible to all
- Drive Innovation: Foster new climate solutions
- Scale Impact: From single buildings to entire cities
Roadmap
Current Release (v0.2.x)
- Core CLI and SDK functionality
- Building and HVAC agents
- Basic pipeline orchestration
- Regional emission factors
Next Release (v0.3.0)
- Kubernetes operator for cloud deployment
- Real-time grid carbon integration
- ML-powered prediction models
- Advanced visualization dashboard
Future (v1.0.0)
- Complete industry coverage
- Global emission factor database
- Blockchain-verified carbon credits
- Enterprise governance features
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
Join us in building the climate-intelligent future. Every line of code counts.
Code Green. Deploy Clean. Save Tomorrow.
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