AI Gateway
Unified proxy OpenAI, Anthropic, Google Gemini. Semantic cache, per-tenant budget, token observability. A single SDK for your LLM workloads.
One endpoint, N providers
The AI Gateway is a single HTTP/SDK surface that proxies major LLM providers. The same code runs against OpenAI, Anthropic, Mistral or Vertex AI — you only change provider.
The gateway adds three layers on top: semantic cache (prompt embeddings, hit rate ~30% on average), per-tenant budget (quota $ per user), observability (tokens, cost, latency, provider).
Five GA supported
ProviderChat/completionEmbeddings templates
OpenAIgpt-5.5, gpt-5.4, gpt-5.4-mini/nano``text-embedding-3-large / -small
Anthropicclaude-fable-5, opus-4-8, sonnet-5, haiku-4-5``—
Google Geminigemini-3.8-flash, 3.7-flash, 3.6-flash, 3.1-pro``gemini-embedding-2 / text-embedding-004
~30% of prompts already known
For each incoming request, the gateway embedding the question (internal lightweight model, <10ms) and searches in a similar vector in a TTL cache. If the cosine distance exceeds your threshold (default 0.96), it returns the hidden response without calling the provider.
The cache is scoped per project. Two different users in the same project can benefit from a hidden response — add cache.scope: 'user' if you want to isolate by user.
Chat, embeddings, RAG
Quotas per user, live metrics
Each call is logged with in/out tokens, cost calculated to the hundredth of a cent, provider, model, latency, cache hit. Set a monthly budget per user to avoid surprises.
Roadmap — not available. The aura commands shown below are planned and not delivered yet: the CLI does not have them today.
Exceeded budgets return HTTP 402 Payment Required with a reset_atfield. Your app can handle this gracefully (downgrade to a cheaper model, prompt the user to upgrade).