OrcaRouter

tip

This provider is an extra of the lfx-bundles metapackage. It is opt-in for both Langflow and standalone LFX installs:

uv pip install "lfx-bundles[<bundle>]"

Replace <bundle> with this page's provider name, for example qdrant. For a torch-free full Langflow install, run uv pip install "langflow[bundles]". For standalone LFX with every provider in lfx-bundles, including PyTorch-based providers, run uv pip install "lfx[bundles]". See Additional bundles for the exact extra name.

Bundles contain custom components that support specific third-party integrations with Langflow.

This page describes the components that are available in the OrcaRouter bundle.

To configure OrcaRouter once for all flows, you can also use the OpenAI Compatible model provider with the base URL https://api.orcarouter.ai/v1.

For more information about OrcaRouter features and functionality used by OrcaRouter components, see the OrcaRouter documentation.

OrcaRouter text generation

This component generates text using OrcaRouter's unified API for multiple AI models from different providers.

It can output either a Model Response (Message) or a Language Model (LanguageModel).

Use the Language Model output when you want to use an OrcaRouter model as the LLM for another LLM-driven component, such as an Agent or Smart Transform component.

For more information, see Language model components.

OrcaRouter text generation parameters

Some parameters are hidden by default in the visual editor. You can modify all component parameters through the component inspection panel that appears when you select a component.

Name	Type	Description
api_key	SecretString	Input parameter. Your OrcaRouter API key for authentication.
model_name	Dropdown	Input parameter. The model to use for chat completion. Options are fetched live from the OrcaRouter model catalog.
temperature	Float	Input parameter. Controls randomness in the output. Range: [0.0, 2.0]. Default: 0.7.
max_tokens	Integer	Input parameter. The maximum number of tokens to generate.