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mlco2Track generative AI's environmental impact
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EcoLogits addresses the need to quantify the environmental impact of generative AI models accessed via APIs. It provides researchers, developers, and organizations with tools to track energy consumption and greenhouse gas (GHG) emissions, enabling more sustainable AI development and deployment. The project aims to bring transparency to the often-opaque environmental footprint of cloud-based AI services.
How It Works
EcoLogits integrates directly with popular generative AI API clients, such as OpenAI, Anthropic, and Google. Upon initialization with specified providers, it intercepts API calls and augments the responses to include estimated energy consumption and GHG emissions data. This approach leverages existing API infrastructure, allowing users to gain environmental insights with minimal code changes, directly correlating usage with tangible environmental metrics.
Quick Start & Requirements
pip install ecologitspip install ecologits[openai], ecologits[anthropic], etc. Supported providers include anthropic, cohere, google-genai, huggingface-hub, mistralai, and openai.ecologits.ai.Highlighted Details
Maintenance & Community
The project acknowledges "Sponsors & benefactors" and provides guidance for contributions via a "Contributing to EcoLogits" document. No direct community channels like Discord or Slack are listed in the README.
Licensing & Compatibility
Licensed under the Mozilla Public License Version 2.0 (MPL-2.0). This license permits use in proprietary software but requires modifications to the licensed code itself to be shared under MPL-2.0.
Limitations & Caveats
Currently, EcoLogits explicitly supports a defined set of API providers. Its functionality with other models, custom integrations, or offline inference scenarios is not detailed in the provided README.
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