EcoAIStop paying for the same AI response twice.

Open-source caching SDK for AI apps. Drop-in wrapper for OpenAI, Anthropic, and Gemini. Zero infrastructure. Instant savings.

npm SDK →

Python SDK →

⚡

Drop-in integration

Wrap your existing AI client in one line. No new infrastructure, no config files, no account needed.

💾

SQLite · Redis · Memory

Responses cached locally by default in SQLite. Scale to Redis for multi-process production deployments.

🧠

Semantic caching

Optionally match semantically similar prompts — not just identical ones. Configurable cosine similarity threshold.

📊

Local dashboard

Built-in analytics dashboard. Cache hit rate, tokens saved, cost saved, CO₂ avoided — all from your local database.

🌱

CO₂ tracking

Every cached response reduces GPU compute. EcoAI measures and logs the estimated carbon footprint avoided.

🔌

OpenAI · Anthropic · Gemini

Works with all three major providers, including vision, tool calling, structured output, and image generation.

Install

npmpip

bash

npm install eco-ai

bash

pip install ecoai-python

eco-ai on npm · ecoai-python on PyPI

Quickstart

OpenAI (JS)OpenAI (Python)

typescript

import { EcoAI } from 'eco-ai';
import OpenAI from 'openai';

const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const eco = new EcoAI({ client: openai });

// Identical to openai.chat.completions.create — cached automatically
const response = await eco.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user', content: 'Summarise the water cycle.' }],
});

python

from openai import OpenAI
from ecoai import EcoAI

client = OpenAI()
eco = EcoAI(client=client)

# Identical to client.chat.completions.create — cached automatically
response = eco.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Summarise the water cycle."}],
)

Before EcoAI  →  38 identical calls  →  $4.26 spent  →  142,000 tokens used
After EcoAI   →  1 real call + 37 cached  →  $0.11 spent  →  97% saved