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AI Gateway

Route to 250+ LLMs with 1 fast & friendly API

Docs | Enterprise | Hosted Gateway | Changelog | API Reference

The AI Gateway is designed for fast, reliable & secure routing to 1600+ language, vision, audio, and image models. It is a lightweight, open-source, and enterprise-ready solution that allows you to integrate with any language model in under 2 minutes.

• [x] Blazing fast (<1ms latency) with a tiny footprint (122kb)
• [x] Battle tested, with over 10B tokens processed everyday
• [x] Enterprise-ready with enhanced security, scale, and custom deployments

What can you do with the AI Gateway?

• Integrate with any LLM in under 2 minutes - Quickstart
• Prevent downtimes through automatic retries and fallbacks
• Scale AI apps with load balancing and conditional routing
• Protect your AI deployments with guardrails
• Go beyond text with multi-modal capabilities
• Finally, explore agentic workflow integrations

[!TIP] Starring this repo helps more developers discover the AI Gateway 🙏🏻

Quickstart (2 mins)

1. Setup your AI Gateway

# Run the gateway locally (needs Node.js and npm)
npx @portkey-ai/gateway

The Gateway is running on http://localhost:8787/v1

The Gateway Console is running on http://localhost:8787/public/

^{Deployment guides:   Portkey Cloud (Recommended)   Docker   Node.js   Cloudflare   Replit   Others...}

2. Make your first request

# pip install -qU portkey-ai

from portkey_ai import Portkey

# OpenAI compatible client
client = Portkey(
    provider="openai", # or 'anthropic', 'bedrock', 'groq', etc
    Authorization="sk-***" # the provider API key
)

# Make a request through your AI Gateway
client.chat.completions.create(
    messages=[{"role": "user", "content": "What's the weather like?"}],
    model="gpt-4o-mini"
)

^{Supported Libraries:   JS   Python   REST   OpenAI SDKs   Langchain   LlamaIndex   Autogen   CrewAI   More..}

On the Gateway Console (http://localhost:8787/public/) you can see all of your local logs in one place.

3. Routing & Guardrails

Configs in the LLM gateway allow you to create routing rules, add reliability and setup guardrails.

config = {
  "retry": {"attempts": 5},

  "output_guardrails": [{
    "default.contains": {"operator": "none", "words": ["Apple"]},
    "deny": True
  }]
}

# Attach the config to the client
client = client.with_options(config=config)

client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Reply randomly with Apple or Bat"}]
)

# This would always response with "Bat" as the guardrail denies all replies containing "Apple". The retry config would retry 5 times before giving up.

You can do a lot more stuff with configs in your AI gateway. Jump to examples →

Enterprise Version (Private deployments)

AWS   Azure   GCP   OpenShift   Kubernetes

The LLM Gateway's enterprise version offers advanced capabilities for org management, governance, security and more out of the box. View Feature Comparison →

The enterprise deployment architecture for supported platforms is available here - Enterprise Private Cloud Deployments

Core Features

Reliable Routing

• Fallbacks: Fallback to another provider or model on failed requests using the LLM gateway. You can specify the errors on which to trigger the fallback. Improves reliability of your application.
• Automatic Retries: Automatically retry failed requests up to 5 times. An exponential backoff strategy spaces out retry attempts to prevent network overload.
• Load Balancing: Distribute LLM requests across multiple API keys or AI providers with weights to ensure high availability and optimal performance.
• Request Timeouts: Manage unruly LLMs & latencies by setting up granular request timeouts, allowing automatic termination of requests that exceed a specified duration.
• Multi-modal LLM Gateway: Call vision, audio (text-to-speech & speech-to-text), and image generation models from multiple providers — all using the familiar OpenAI signature
• Realtime APIs: Call realtime APIs launched by OpenAI through the integrate websockets server.

Security & Accuracy

• Guardrails: Verify your LLM inputs and outputs to adhere to your specified checks. Choose from the 40+ pre-built guardrails to ensure compliance with security and accuracy standards. You can bring your own guardrails or choose from our many partners.
• Secure Key Management: Use your own keys or generate virtual keys on the fly.
• Role-based access control: Granular access control for your users, workspaces and API keys.
• Compliance & Data Privacy: The AI gateway is SOC2, HIPAA, GDPR, and CCPA compliant.

Cost Management

• Smart caching: Cache responses from LLMs to reduce costs and improve latency. Supports simple and semantic* caching.
• Usage analytics: Monitor and analyze your AI and LLM usage, including request volume, latency, costs and error rates.
• Provider optimization*: Automatically switch to the most cost-effective provider based on usage patterns and pricing models.

Collaboration & Workflows

• Agents Support: Seamlessly integrate with popular agent frameworks to build complex AI applications. The gateway seamlessly integrates with Autogen, CrewAI, LangChain, LlamaIndex, Phidata, Control Flow, and even Custom Agents.
• Prompt Template Management*: Create, manage and version your prompt templates collaboratively through a universal prompt playground.

^{* Available in hosted and enterprise versions}

Cookbooks

☄️ Trending

• Use models from Nvidia NIM with AI Gateway
• Monitor CrewAI Agents with Portkey!
• Comparing Top 10 LMSYS Models with AI Gateway.

🚨 Latest

• Create Synthetic Datasets using Nemotron
• Use the LLM Gateway with Vercel's AI SDK
• Monitor Llama Agents with Portkey's LLM Gateway

View all cookbooks →

Supported Providers

Explore Gateway integrations with 45+ providers and 8+ agent frameworks.

	Provider	Support	Stream
	OpenAI	✅	✅
	Azure OpenAI	✅	✅
	Anyscale	✅	✅
	Google Gemini	✅	✅
	Anthropic	✅	✅
	Cohere	✅	✅
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