LLM Gateway (AI Gateway)
An LLM gateway, also called an AI gateway, is a proxy layer between applications and large language model providers such as OpenAI and Anthropic. It injects API keys server-side, enforces rate limits and budgets, caches responses, logs usage, and can fail over between models.
Technical Architecture & Deep-Dive
Shipping AI features directly from a frontend exposes expensive model keys, and a leaked key can generate thousands of dollars in charges within hours. An LLM gateway keeps credentials in a vault and authenticates clients with restricted tokens instead.
Beyond security, gateways add operational controls: caching repeated prompts, slimming verbose response metadata, streaming tokens efficiently to mobile clients, and routing to a fallback provider when the primary model is slow or unavailable.
Key Architectural Benefits
Edge LLM Gateway Injection
const res = await fetch('https://api.anthropic.com/v1/messages', {
method: 'POST',
headers: {
'x-api-key': env.ANTHROPIC_API_KEY,
'anthropic-version': '2023-06-01',
'content-type': 'application/json',
},
body: JSON.stringify({ model, max_tokens: 512, messages }),
});Build a Secure AI Gateway
Proxy OpenAI or Anthropic with vault-held keys, client tokens, and rate limits in minutes.
Frequently Asked Questions
Q:Can an LLM gateway stream responses?
Yes. Edge runtimes can pass server-sent event streams from the model provider to the client while still hiding credentials and enforcing limits.
Related Architecture Concepts
Edge Secret Injection is a security pattern where sensitive upstream API credentials (e.g. Stripe Secret Keys, OpenAI Tokens) are stored in an encrypted vault and injected into HTTP request headers exclusively at the edge runtime, ensuring client browsers and mobile apps never see or store the keys.
Server-Sent Events (SSE) is a web standard that lets a server push a continuous stream of text events to a client over a single long-lived HTTP connection. Browsers consume SSE with the EventSource API, and it is widely used to stream AI model tokens and live updates.
Retrieval-Augmented Generation (RAG) is an AI technique where relevant documents or records are retrieved from a knowledge source, such as a vector database or API, and inserted into the prompt of a large language model. The model then generates answers grounded in that retrieved context.
API Rate Limiting is a traffic control mechanism that caps the number of requests a client, IP address, or API token can execute within a specified time window. Rate limiting prevents server overloading, protects against credential brute-forcing, and shields upstream APIs from exceeding subscription quotas.
Ready-to-Use Edge Recipes
To use OpenAI in a client-side React app without leaking your secret key, never include OPENAI_API_KEY or REACT_APP_OPENAI_API_KEY in frontend .env files. Instead, route your fetch calls through a RealComposer edge endpoint that injects your secret key server-side on Cloudflare Workers and enforces CORS origin whitelisting.
To solve secure anthropic claude api proxy for frontend, never execute unauthenticated requests or embed private tokens directly in client bundles. RealComposer acts as a sub-10ms edge gateway running on Cloudflare Workers that securely injects credentials from your Secret Vault, normalizes responses, and prevents unauthorized API usage. Route calls through your RealComposer edge URL to guarantee complete privacy, robust origin validation, and low mobile latency.
To combine anthropic claude with openai fallback router, use one RealComposer pipeline with parallel steps. Primary Anthropic Messages step plus OpenAI fallback step in one pipeline. Your Frontend / Web app makes one request instead of several sequential upstream calls.