Providers and Routing

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LLMProxy separates the model name a client requests from the upstream deployment that handles it.

A provider describes protocol, endpoint, and credential pool. A model gives clients a stable public name. A model has one or more routes, each pointing at an upstream provider and model ID.

client model "fast"
        │
        ▼
public catalog model
        │
        ├── openai-primary / gpt-4.1-mini
        └── anthropic-primary / claude-3-5-haiku-20241022

Prefer configuration over provider modules

When ReqLLM already supports an upstream protocol, declare a named provider instead of adding Elixir code:

config :llm_proxy,
  providers: %{
    "example-service" => %{
      adapter: "openai",
      base_url: "https://api.example.com/v1",
      token_pool: "example-production"
    }
  },
  models: [
    [
      name: "example/model",
      routes: [[to: "example-service", model: "upstream-model-id"]]
    ]
  ]

Standalone TOML expresses the same data:

[providers.example-service]
adapter = "openai"
base_url = "https://api.example.com/v1"
token_pool = "example-production"

[[models]]
name = "example/model"

[[models.routes]]
to = "example-service"
model = "upstream-model-id"

adapter must be a provider ID registered with ReqLLM. LLMProxy resolves that finite registry and never creates atoms from provider names in data configuration.

A different endpoint, credential pool, or model ID does not justify a new provider module. Add code only when the upstream requires an authentication or wire protocol that ReqLLM does not support; prefer contributing generally useful protocol support to ReqLLM first.

Credential isolation

token_pool defaults at provider level and can be overridden on a route. Provider-token records join a pool through their provider field.

Keep pools separate even when two services use the same adapter:

provider: openai-primary    adapter: openai    token_pool: openai-production
provider: internal-gateway adapter: openai    token_pool: internal-production

This prevents credentials from crossing endpoints during retries or fallback.

Standalone releases can bootstrap named pools from secret environment state:

LLM_PROXY_PROVIDER_KEYS='{"example-production":["secret-a","secret-b"]}'

Persisted provider tokens remain the runtime source after seeding. A token record can override the provider base URL through its proxy field, but that should be reserved for intentional per-token gateways; normal endpoints belong in provider configuration.

Public model aliases

A readable library configuration uses model aliases and routes:

config :llm_proxy,
  models: [
    fast: [
      routing: :ordered,
      routes: [
        [
          to: :openai,
          model: "gpt-4.1-mini",
          timeout: 15_000,
          failure_threshold: 3,
          cooldown_ms: 30_000
        ],
        [
          to: :anthropic,
          model: "claude-3-5-haiku-20241022",
          order: 2
        ]
      ]
    ]
  ]

Clients request fast; they do not need to know which deployment answered. The response and stored usage still record the actual provider and upstream model.

The lower-level :catalog configuration with explicit LLMProxy.Catalog.Model and deployment structs remains available for advanced and existing applications.

Routing strategies

Routing happens within each order group. Lower order groups are attempted first.

  • :ordered — stable route order.
  • :shuffle — randomize routes in an order group.
  • :round_robin — rotate the first route across requests.
  • :weighted_shuffle — randomize by route weight.
  • :lowest_cost — order routes by LLMDB input and output pricing.

A route can define:

OptionPurpose
toNamed or built-in provider
modelUpstream model ID
orderFallback group; lower values run first
weightRelative weight for :weighted_shuffle
token_poolRoute-specific credential pool
timeout / timeout_msProvider attempt deadline
failure_thresholdConsecutive retryable failures before opening the circuit
cooldown_msTime before an open deployment becomes eligible again
hiddenHide the public model from model listing when configured on the model
metadataOperator-defined catalog metadata

Failure handling

LLMProxy resolves an ordered list of deployment attempts, then:

  1. skips deployments with open circuit breakers;
  2. picks an available credential from the route's token pool;
  3. executes with the route timeout;
  4. applies Retry-After cooldowns to rate-limited credentials;
  5. records retryable deployment failures;
  6. falls through to the next eligible route;
  7. records the provider and model that ultimately handled the request.

Authentication failures and other non-retryable errors are returned directly. Timeouts and retryable upstream failures participate in fallback. Circuit breakers move through closed, open, and half-open states per deployment.

Built-in providers

  • OpenAI — API-key authentication and OpenAI APIs.
  • Anthropic — API-key authentication and Anthropic Messages.
  • OpenRouter — OpenAI-compatible API with OpenRouter headers.
  • OpenAI Codex — ChatGPT subscription Codex backend with OAuth credentials; streaming uses ReqLLM's Responses WebSocket transport.

Configuration-driven providers cover other ReqLLM adapters and OpenAI-compatible endpoints.

OpenAI Codex OAuth

openai-codex uses provider-token records. Plain access tokens work until they expire. Refreshable seed entries use:

access_token|refresh_token|expires_unix_ms|account_id

account_id is optional. Refreshed credentials are persisted as token, refresh token, expiry, and account ID.

For standalone services, prefer the live Incant admin action described in Admin Integration. It runs against the active storage owner and persists refreshed credentials without starting a second database owner.

The release also includes bin/codex_login for local or manual recovery. If the release uses exclusive local storage, stop the service before using a separate-VM recovery command.

Custom protocols

Implement LLMProxy.Providers.Behaviour only when the upstream needs a protocol or authentication flow ReqLLM cannot provide:

defmodule MyApp.LLM.CustomProvider do
  @behaviour LLMProxy.Providers.Behaviour

  alias LLMProxy.Providers.Result

  def name, do: "custom"
  def native_protocol, do: :openai
  def models, do: ["custom-model"]

  def call(body, actor_id) do
    # Authenticate, execute, and return an explicit Result variant.
    {:ok, Result.response(%{"choices" => []}, nil)}
  end

  def stream(body, actor_id) do
    {:ok, Result.stream([], nil)}
  end

  def extract_usage(_response), do: LLMProxy.Usage.zero()
  def to_openai_response(response, _model), do: response
end

Use these modules when implementing an extension:

Providers may implement call_native/2 and stream_native/2 for native Messages or Responses passthrough. Native calls still receive catalog routing, timeout, circuit-breaker, and retry-after behavior.

Transport behavior

Configuration-driven providers use LLMProxy's normalized chat path, including conversation history, tools, reasoning deltas, streaming, and usage.

The ReqLLM Finch transport uses eight HTTP/1 pool shards with four connections each by default, allowing bounded concurrency for long-lived streams. Cowboy uses the provider receive timeout as its idle ceiling and resets the timer when data is sent. LLMProxy adds SSE comment heartbeats during upstream silence.

Provider errors are projected onto canonical status, code, and message fields. Exception terms, stacktraces, request bodies, and upstream headers are not rendered to clients.