gateway

[!IMPORTANT] :rocket: Gateway 2.0 (Pre-Release) Portkey's core enterprise gateway is merging into open-source with our 2.0 release. You can try the pre-release branch here. Read more about what's next for Portkey in our Series A announcement.

🆕 Portkey Models - Open-source LLM pricing for 2,300+ models across 40+ providers. Explore →

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.

• Blazing fast (<1ms latency) with a tiny footprint (122kb)
• Battle tested, with over 10B tokens processed everyday
• 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
• Explore agentic workflow integrations
• Manage MCP servers with enterprise auth & observability using MCP Gateway

[!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/

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

MCP Gateway

MCP Gateway provides a centralized control plane for managing MCP (Model Context Protocol) servers across your organization.

• Authentication — Single auth layer at the gateway. Users authenticate once; your MCP servers receive verified requests
• Access Control — Control which teams and users can access which servers and tools. Revoke access instantly
• Observability — Every tool call logged with full context: who called what, parameters, response, latency
• Identity Forwarding — Forward user identity (email, team, roles) to MCP servers automatically

Works with Claude Desktop, Cursor, VS Code, and any MCP-compatible client. Get started →

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.

Portkey Models

Open-source LLM pricing database for 40+ providers - used by the Gateway for cost tracking.

GitHub | Model Explorer

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	✅	✅
	Together AI	✅	✅
	Perplexity	✅	✅
	Mistral	✅	✅
	Nomic	✅	✅
	AI21	✅	✅
	Stability AI	✅	✅
	DeepInfra	✅	✅
	Ollama	✅	✅
	Novita AI	✅	✅

View the complete list of 200+ supported models here

Agents

Gateway seamlessly integrates with popular agent frameworks. Read the documentation here.

Framework	Call 200+ LLMs	Advanced Routing	Caching	Logging & Tracing*	Observability*	Prompt Management*
Autogen	✅	✅	✅	✅	✅	✅
CrewAI	✅	✅	✅	✅	✅	✅
LangChain	✅	✅	✅	✅	✅	✅
Phidata	✅	✅	✅	✅	✅	✅
Llama Index	✅	✅	✅	✅	✅	✅
Control Flow	✅	✅	✅	✅	✅	✅
Build Your Own Agents	✅	✅	✅	✅	✅	✅
	IO Intelligence	✅	✅

*Available on the hosted app. For detailed documentation click here.

Gateway Enterprise Version

Make your AI app more reliable and forward compatible, while ensuring complete data security and privacy.

✅  Secure Key Management - for role-based access control and tracking ✅  Simple & Semantic Caching - to serve repeat queries faster & save costs ✅  Access Control & Inbound Rules - to control which IPs and Geos can connect to your deployments ✅  PII Redaction - to automatically remove sensitive data from your requests to prevent indavertent exposure ✅  SOC2, ISO, HIPAA, GDPR Compliances - for best security practices ✅  Professional Support - along with feature prioritization

Schedule a call to discuss enterprise deployments

Contributing

The easiest way to contribute is to pick an issue with the good first issue tag 💪. Read the contribution guidelines here.

Bug Report? File here | Feature Request? File here

Getting Started with the Community

Join our weekly AI Engineering Hours every Friday (8 AM PT) to:

• Meet other contributors and community members
• Learn advanced Gateway features and implementation patterns
• Share your experiences and get help
• Stay updated with the latest development priorities

Join the next session → | Meeting notes

Community

Join our growing community around the world, for help, ideas, and discussions on AI.

• View our official Blog
• Chat with us on Discord
• Follow us on Twitter
• Connect with us on LinkedIn
• Read the documentation in Japanese
• Visit us on YouTube
• Join our Dev community