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Version: 2.26

OrcaRouter

haystack_integrations.components.generators.orcarouter.chat.chat_generator​

OrcaRouterChatGenerator​

Bases: OpenAIChatGenerator

Enables text generation using OrcaRouter generative models.

OrcaRouter is an OpenAI-compatible model routing gateway that exposes 100+ chat models from providers such as OpenAI, Anthropic, Google, DeepSeek, and Qwen behind a single endpoint and API key. Models are addressed with a provider/model namespace (for example openai/gpt-4o-mini or anthropic/claude-opus-4.8). The special orcarouter/auto router selects an upstream model per request according to the routing policy configured in your OrcaRouter console.

For the list of supported models, see the OrcaRouter model catalog.

This component supports streaming, tool-calling, and structured outputs. It uses the ChatMessage format for both input and output; see the Haystack docs for details.

Usage example:

python
from haystack_integrations.components.generators.orcarouter import OrcaRouterChatGenerator
from haystack.dataclasses import ChatMessage

messages = [ChatMessage.from_user("What's Natural Language Processing?")]

client = OrcaRouterChatGenerator(model="openai/gpt-4o-mini")
response = client.run(messages)
print(response)

init​

python
__init__(
    *,
    api_key: Secret = Secret.from_env_var("ORCAROUTER_API_KEY"),
    model: str = "openai/gpt-4o-mini",
    streaming_callback: StreamingCallbackT | None = None,
    api_base_url: str | None = "https://api.orcarouter.ai/v1",
    organization: str | None = None,
    generation_kwargs: dict[str, Any] | None = None,
    tools: ToolsType | None = None,
    tools_strict: bool = False,
    timeout: float | None = None,
    max_retries: int | None = None,
    http_client_kwargs: dict[str, Any] | None = None
) -> None

Creates an instance of OrcaRouterChatGenerator.

Unless specified otherwise, the default model is openai/gpt-4o-mini.

Parameters:

  • api_key (Secret) – The OrcaRouter API key.
  • model (str) – The name of the OrcaRouter chat completion model to use. Models use a provider/model namespace (for example openai/gpt-4o-mini). Use orcarouter/auto to let OrcaRouter route the request.
  • streaming_callback (StreamingCallbackT | None) – A callback function that is called when a new token is received from the stream. The callback function accepts StreamingChunk as an argument.
  • api_base_url (str | None) – The OrcaRouter API base URL. For more details, see the OrcaRouter documentation.
  • organization (str | None) – Your OrcaRouter organization ID, if any.
  • generation_kwargs (dict[str, Any] | None) – Other parameters to use for the model. These parameters are sent directly to the OrcaRouter endpoint. See OrcaRouter API docs for more details. Some of the supported parameters:
  • max_tokens: The maximum number of tokens the output text can have.
  • temperature: The sampling temperature to use. Higher values mean the model takes more risks.
  • top_p: The nucleus sampling value to use.
  • stream: Whether to stream back partial progress.
  • extra_body: A dictionary of OrcaRouter-specific routing preferences (such as a fallback list of models) that is passed straight through to the gateway.
  • tools (ToolsType | None) – A list of tools or a Toolset for which the model can prepare calls. This parameter can accept either a list of Tool objects or a Toolset instance.
  • tools_strict (bool) – Whether to enable strict schema adherence for tool calls. If set to True, the model follows exactly the schema provided in the parameters field of the tool definition.
  • timeout (float | None) – The timeout for the OrcaRouter API call.
  • max_retries (int | None) – Maximum number of retries to contact OrcaRouter after an internal error. If not set, it defaults to either the OPENAI_MAX_RETRIES environment variable, or set to 5.
  • http_client_kwargs (dict[str, Any] | None) – A dictionary of keyword arguments to configure a custom httpx.Clientor httpx.AsyncClient. For more information, see the HTTPX documentation.