OpenAI-Compatible API

A RocketRide LLM node that connects any OpenAI-compatible API endpoint to a pipeline.

What it does

Connects any OpenAI-compatible API endpoint to your pipeline. Use this node for providers that implement the OpenAI API spec (Featherless, Together, Groq, Ollama, LM Studio, and others) but do not have a dedicated RocketRide node. Used primarily as an llm invoke connection by agents and other nodes that need an LLM, but can also be used directly via lanes.

Built on langchain-openai (ChatOpenAI) over the official openai SDK. The chat client is created with temperature: 0 for deterministic output, and max_tokens is set from the shared LLM base's output-token budget (default 4096, minimum 1024). When base_url is empty, the SDK falls back to the default OpenAI endpoint.

When the node configuration is saved, it validates the settings by sending a 1-token "Hi" completion request to the configured endpoint (10-second timeout) and surfaces any provider error (bad key, unknown model, unreachable URL) as a warning with the provider's status code and message, truncated to 500 characters.

Lanes

Lane in	Lane out	Description
`questions`	`answers`	Send a question directly, receive a generated answer

Profiles

Generic endpoint default: Custom OpenAI-compatible endpoint (custom). Nebius preset default: Llama 3.3 70B Instruct (llama-3-3-70b).

The directory documents the generic endpoint and the Nebius branded preset in one combined profile table.

Profile	Model	Context tokens	Source
Generic `custom` (default)	(user-specified)	32,768	Any OpenAI-compatible API
`llama-3-3-70b` (default)	`meta-llama/Llama-3.3-70B-Instruct`	131,072	Nebius Token Factory
`qwen3-235b`	`Qwen/Qwen3-235B-A22B`	131,072	Nebius Token Factory
`deepseek-v3`	`deepseek-ai/DeepSeek-V3`	131,072	Nebius Token Factory

Configuration

Choose custom for a generic provider and set its model ID, base URL, context limit, and API key. Choose one of the named Nebius profiles when using Token Factory; those profiles pin the model ID, endpoint, and context limit.

Generic OpenAI-compatible endpoints

Set base_url to the provider's OpenAI-compatible API root and model to its exact model identifier. When base_url is empty, the OpenAI SDK uses its default endpoint. Use a positive modelTotalTokens value that matches the selected model.

Nebius preset

services.nebius.json registers Nebius (llm_nebius://) as a branded preset of this node. It uses the same Python implementation and pins the base URL to https://api.tokenfactory.nebius.com/v1/. The three named Nebius profiles in the combined table require no model or endpoint edits.

Nebius profiles default the API key to the ${ROCKETRIDE_NEBIUS_KEY} environment substitution, so no per-node key entry is needed when that variable is set. The Nebius service also exposes its own custom option for another Token Factory model, retaining the pinned endpoint, environment-backed key, and 131,072-token context limit. The combined table represents the duplicate custom key once, using the generic service's merged 32,768-token default.

Authentication

For custom, provide the API key expected by the configured endpoint. Nebius named profiles use ${ROCKETRIDE_NEBIUS_KEY} by default; replace it only when the credential must be supplied directly in the node configuration.

Notes

Error handling and retries

Provider errors are mapped to friendly messages and classified for retry:

Provider exception	Retried	Surfaced as
`AuthenticationError`	no	`Invalid API key.`
`APIError`	no	`An error occurred with the API.`
`RateLimitError`	yes	`Rate limit exceeded. Please try again later.`
`APIConnectionError`	yes	`Failed to connect to the API.`

Anything else falls through to the shared LLM base's default retry and mapping logic.

Testing

services.json includes a test block that runs the custom profile against a local test server with a mocked langchain_openai, so no real API key is required. ROCKETRIDE_MOCK must point to nodes/test/mocks.

Schema