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Pipelex Gateway & Model Access

Access AI models through the Pipelex Gateway or bring your own API keys.

Pipelex Gateway

A fully managed infrastructure providing unified access to AI models through a single API key. The Gateway eliminates the need to manage multiple provider configurations.

  • Single API key for all supported models
  • Remote model catalog — always access the latest models without updating Pipelex
  • Enterprise-grade architecture — built for reliability and scale
  • Extensive provider support — OpenAI, Google, Anthropic, Mistral, xAI, and more

Browse all supported models in the Gateway Models reference.

Get your Gateway API key at app.pipelex.com or join the waitlist.

Bring Your Own Keys

Direct integration with major providers using your own API keys:

  • OpenAI — GPT-4o, GPT-4.1, o1, o3, o4-mini, etc.
  • Anthropic — Claude Sonnet 4, Claude Haiku, etc.
  • Google — Gemini 2.5 Pro, Gemini 2.5 Flash, etc.
  • Mistral — Mistral Large, Mistral Medium, etc.
  • Azure OpenAI — Azure-hosted OpenAI models
  • Amazon Bedrock — AWS-hosted models
  • Vertex AI — Google Cloud-hosted models
  • xAI — Grok models
  • Portkey — AI gateway for routing and observability
  • OpenRouter — Multi-provider aggregator
  • BlackboxAI — Blackbox-hosted models
  • fal — Image generation models

Open-Source Models

Run open-source models through dedicated providers:

  • Ollama — Run open-source LLMs locally (Llama, Mistral, Qwen, etc.)
  • Hugging Face Inference — including qwen-image for text-to-image
  • Scaleway — Deepseek R1, Llama 3.3, Qwen3, GPT-OSS
  • Groq — Llama-4, Kimi-K2-Instruct

Routing Profiles

Routing profiles control which backend handles each model. Define pattern-based routes, defaults, and fallback orders in routing_profiles.toml. Switch a pipeline from one provider to another — or from Pipelex Gateway to your own keys — without changing the method definition.

See Configure AI Providers for setup details.

Offline Behavior

The Gateway fetches its model catalog from a remote config service. Pipelex stays usable when that service is briefly unreachable:

  • Gateway disabled (Bring Your Own Keys) — no remote fetch is attempted at all. Setup, validation, and dry-runs are fully offline.
  • Gateway enabled — Pipelex primes an on-disk copy of the remote config at ~/.pipelex/cache/remote_config.json on every successful fetch and during pipelex init while online. If a later fetch fails, it falls back to this cache so setup, validation, and --dry-run still complete. When the cache is in use, a RemoteConfigStale warning is emitted (the agent CLI surfaces it on the JSON warnings array).

Only the actual inference call needs the network at runtime — offline support covers setup and dry-run, not live model calls. If the Gateway is enabled, the fetch fails, and no cache has ever been primed, setup raises RemoteConfigUnavailableError: run pipelex init while online to prime the cache, or disable pipelex_gateway for permanent offline (BYOK) operation.