--- title: "gateway" type: "tool" slug: "adaline-gateway" canonical_url: "https://www.graphcanon.com/tools/adaline-gateway" github_url: "https://github.com/adaline/gateway" homepage_url: "https://www.adaline.ai/docs" stars: 600 forks: 27 primary_language: "TypeScript" license: "MIT" categories: ["llm-frameworks", "developer-tools"] tags: ["llmops", "openai", "typescript", "anthropic", "prompt-engineering", "togetherai", "ai-agents", "language-model"] updated_at: "2026-07-07T18:49:38.644448+00:00" --- # gateway > Fully Local, Production-Grade Super SDK for Calling More Than 300+ LLMs Adaline Gateway provides a simple, unified interface to call over 200 Language Learning Models (LLMs) locally with features such as batching, retries, caching, callbacks and OpenTelemetry support. ## Facts - Repository: https://github.com/adaline/gateway - Homepage: https://www.adaline.ai/docs - Stars: 600 · Forks: 27 · Open issues: 0 · Watchers: 4 - Primary language: TypeScript - License: MIT - Last pushed: 2026-06-09T23:08:20+00:00 ## Categories - [LLM Frameworks](/categories/llm-frameworks.md) - [Developer Tools](/categories/developer-tools.md) ## Tags llmops, openai, typescript, anthropic, prompt-engineering, togetherai, ai-agents, language-model ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. 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(★ 116,702) ## README (excerpt) ```text # Adaline Gateway The only fully local, production-grade Super SDK that provides a simple, unified, and powerful interface for calling more than 300+ LLMs. - Production-ready and trusted by enterprises - Fully local and _NOT_ a proxy - deploy it anywhere - Built-in batching, retries, caching, callbacks, and OpenTelemetry support - Extensible with custom plugins for caching, logging, HTTP clients, and more - use it like building blocks to integrate with your infrastructure - Supports plug-and-play providers - run fully custom providers while leveraging all the benefits of Adaline Gateway ### Features - 🔧 Strongly typed in TypeScript - 📦 Isomorphic - works everywhere - 🔒 100% local, private, and _NOT_ a proxy - 🛠️ Tool calling support across all compatible LLMs - 📊 Batching for all requests with custom queue support - 🔄 Automatic retries with exponential backoff - ⏳ Caching with custom cache plug-in support - 📞 Callbacks for comprehensive instrumentation and hooks - 🔍 OpenTelemetry integration for existing infrastructure - 🔌 Plug-and-play custom providers for local and custom models ### Providers | Provider | Chat Models | Embedding Models | | --------------------- | --------------- | ------------------| | OpenAI | ✅ | ✅ | | Anthropic | ✅ | ❌ | | Google AI Studio | ✅ | ❌ | | Google Vertex | ✅ | ✅ | | xAi | ✅ | ✅ | | AWS Bedrock | ✅ | ❌ | | Azure OpenAI | ✅ | ✅ | | Groq | ✅ | ❌ | | Together AI | ✅ | ❌ | | Open Router | ✅ | ❌ | | Custom (OpenAI-like) | ✅ | ❌ | | Voyage | ❌ | ✅ | ## Installation ### Core packages ```bash npm install @adaline/gateway @adaline/types ``` ### Provider packages Dependencies for providers are optional. You can install them as needed. For example: ```bash npm install @adaline/openai @adaline/anthropic @adaline/google @adaline/open-router @adaline/bedrock ``` ## Quickstart ### Chat This example demonstrates how to invoke an LLM with a simple text prompt in both non-streaming and streaming modes. ```typescript import { Gateway } from "@adaline/gateway"; import { OpenAI } from "@adaline/openai"; import { Config, ConfigType, MessageType } from "@adaline/types"; const OPENAI_API_KEY = "your-api-key"; // Replace with your OpenAI API key const gateway = new Gateway(); const openai = new OpenAI(); const gpt4o = openai.chatModel({ modelName: "gpt-4o", apiKey: OPENAI_API_KEY, }); const config: ConfigType = Config().parse({ temperature: 0.7, maxTokens: 300, }); const messages: MessageType[] = [ { role: "system", content: [{ modality: "text", value: "You are a helpful assistant. You are extremely concise.", }], }, { role: "user", content: [{ modality: "text", value: `What is ${Math.floor(Math.random() * 100) + 1} + ${Math.floor(Math.random() * 100) + 1}?`, }], }, ]; // * Complete chat async function runCompleteChat() { const completeChat = await gateway.completeChat({ model: gpt4o, config, messages, tools: [], }); console.log(completeChat.provider.request); // HTTP Request sent to Provider console.log(completeChat.provider.response); // HTTP Response from Provider console.log(completeChat.cached); // Whether the response was cached console.log(completeChat.latencyInMs); // Latency in milliseconds console.log(completeChat.request); // Request in Gateway types console.log(completeChat.response); // Response in Gateway types, E.g.: // { // "messages": [ // { // "role": "assistant", // "c ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/adaline-gateway`](/api/graphcanon/tools/adaline-gateway) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_