chore: import upstream snapshot with attribution

docs-website/reference_versioned_docs/version-2.23/integrations-api/openrouter.md

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+---
+title: "OpenRouter"
+id: integrations-openrouter
+description: "OpenRouter integration for Haystack"
+slug: "/integrations-openrouter"
+---
+
+
+## haystack_integrations.components.generators.openrouter.chat.chat_generator
+
+### OpenRouterChatGenerator
+
+Bases: <code>OpenAIChatGenerator</code>
+
+Enables text generation using OpenRouter generative models.
+
+For supported models, see [OpenRouter docs](https://openrouter.ai/models).
+
+Users can pass any text generation parameters valid for the OpenRouter chat completion API
+directly to this component using the `generation_kwargs` parameter in `__init__` or the `generation_kwargs`
+parameter in `run` method.
+
+Key Features and Compatibility:
+
+- **Primary Compatibility**: Compatible with the OpenRouter chat completion endpoint.
+- **Streaming Support**: Supports streaming responses from the OpenRouter chat completion endpoint.
+- **Customizability**: Supports all parameters supported by the OpenRouter chat completion endpoint.
+- **Reasoning Support**: Extracts reasoning/thinking content from models that support it
+  (e.g., DeepSeek R1, Claude with extended thinking) and stores it in the `ReasoningContent`
+  field on `ChatMessage`. Reasoning content is only captured for non-streaming requests.
+
+This component uses the ChatMessage format for structuring both input and output,
+ensuring coherent and contextually relevant responses in chat-based text generation scenarios.
+Details on the ChatMessage format can be found in the
+[Haystack docs](https://docs.haystack.deepset.ai/docs/chatmessage)
+
+For more details on the parameters supported by the OpenRouter API, refer to the
+[OpenRouter API Docs](https://openrouter.ai/docs/quickstart).
+
+Usage example:
+
+```python
+from haystack_integrations.components.generators.openrouter import (
+    OpenRouterChatGenerator,
+)
+from haystack.dataclasses import ChatMessage
+
+messages = [ChatMessage.from_user("What's Natural Language Processing?")]
+
+client = OpenRouterChatGenerator(
+    model="deepseek/deepseek-r1",
+    generation_kwargs={"reasoning": {"effort": "high"}},
+)
+response = client.run(messages)
+print(response["replies"][0].reasoning)  # Access reasoning content
+print(response["replies"][0].text)  # Access final answer
+```
+
+#### __init__
+
+```python
+__init__(
+    *,
+    api_key: Secret = Secret.from_env_var("OPENROUTER_API_KEY"),
+    model: str = "openai/gpt-5-mini",
+    streaming_callback: StreamingCallbackT | None = None,
+    api_base_url: str | None = "https://openrouter.ai/api/v1",
+    generation_kwargs: dict[str, Any] | None = None,
+    tools: ToolsType | None = None,
+    timeout: float | None = None,
+    extra_headers: dict[str, Any] | None = None,
+    max_retries: int | None = None,
+    http_client_kwargs: dict[str, Any] | None = None
+) -> None
+```
+
+Creates an instance of OpenRouterChatGenerator.
+
+**Parameters:**
+
+- **api_key** (<code>Secret</code>) – The OpenRouter API key.
+- **model** (<code>str</code>) – The name of the OpenRouter chat completion model to use.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – 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** (<code>str | None</code>) – The OpenRouter API Base url.
+  For more details, see OpenRouter [docs](https://openrouter.ai/docs/quickstart).
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Other parameters to use for the model. These parameters are all sent directly to
+  the OpenRouter endpoint. See [OpenRouter API docs](https://openrouter.ai/docs/quickstart) for more details.
+  Some of the supported parameters:
+- `max_tokens`: The maximum number of tokens the output text can have.
+- `temperature`: What sampling temperature to use. Higher values mean the model will take more risks.
+  Try 0.9 for more creative applications and 0 (argmax sampling) for ones with a well-defined answer.
+- `top_p`: An alternative to sampling with temperature, called nucleus sampling, where the model
+  considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens
+  comprising the top 10% probability mass are considered.
+- `stream`: Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent
+  events as they become available, with the stream terminated by a data: [DONE] message.
+- `safe_prompt`: Whether to inject a safety prompt before all conversations.
+- `random_seed`: The seed to use for random sampling.
+- `reasoning`: A dict to configure reasoning/thinking tokens for models that support it.
+  Example: `{"effort": "high"}` or `{"max_tokens": 2000}`.
+  Reasoning content is only captured for non-streaming requests.
+  See [OpenRouter reasoning docs](https://openrouter.ai/docs/use-cases/reasoning-tokens).
+- `response_format`: A JSON schema or a Pydantic model that enforces the structure of the model's response.
+- **tools** (<code>ToolsType | None</code>) – 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.
+- **timeout** (<code>float | None</code>) – The timeout for the OpenRouter API call.
+- **extra_headers** (<code>dict\[str, Any\] | None</code>) – Additional HTTP headers to include in requests to the OpenRouter API.
+  This can be useful for adding site URL or title for rankings on openrouter.ai
+  For more details, see OpenRouter [docs](https://openrouter.ai/docs/quickstart).
+- **max_retries** (<code>int | None</code>) – Maximum number of retries to contact OpenAI after an internal error.
+  If not set, it defaults to either the `OPENAI_MAX_RETRIES` environment variable, or set to 5.
+- **http_client_kwargs** (<code>dict\[str, Any\] | None</code>) – A dictionary of keyword arguments to configure a custom `httpx.Client`or `httpx.AsyncClient`.
+  For more information, see the [HTTPX documentation](https://www.python-httpx.org/api/#client).
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serialize this component to a dictionary.
+
+**Returns:**
+
+- <code>dict\[str, Any\]</code> – The serialized component as a dictionary.
+
+#### run
+
+```python
+run(
+    messages: list[ChatMessage] | str,
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None,
+    tools_strict: bool | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Invokes chat completion on the OpenRouter API.
+
+**Parameters:**
+
+- **messages** (<code>list\[ChatMessage\] | str</code>) – A list of ChatMessage instances representing the input messages.
+  If a string is provided, it is converted to a list containing a ChatMessage with user role.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – A callback function that is called when a new token is received from the stream.
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Additional keyword arguments for text generation. These parameters will
+  override the parameters passed during component initialization.
+  For details on OpenRouter API parameters, see
+  [OpenRouter docs](https://openrouter.ai/docs/quickstart).
+- **tools** (<code>ToolsType | None</code>) – A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+  If set, it will override the `tools` parameter provided during initialization.
+- **tools_strict** (<code>bool | None</code>) – Whether to enable strict schema adherence for tool calls.
+
+**Returns:**
+
+- <code>dict\[str, list\[ChatMessage\]\]</code> – A dictionary with the following key:
+- `replies`: A list containing the generated responses as ChatMessage instances.
+
+#### run_async
+
+```python
+run_async(
+    messages: list[ChatMessage] | str,
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None,
+    tools_strict: bool | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Asynchronously invokes chat completion on the OpenRouter API.
+
+**Parameters:**
+
+- **messages** (<code>list\[ChatMessage\] | str</code>) – A list of ChatMessage instances representing the input messages.
+  If a string is provided, it is converted to a list containing a ChatMessage with user role.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – A callback function that is called when a new token is received from the stream.
+  Must be a coroutine.
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Additional keyword arguments for text generation.
+- **tools** (<code>ToolsType | None</code>) – A list of Tool and/or Toolset objects, or a single Toolset.
+- **tools_strict** (<code>bool | None</code>) – Whether to enable strict schema adherence for tool calls.
+
+**Returns:**
+
+- <code>dict\[str, list\[ChatMessage\]\]</code> – A dictionary with the following key:
+- `replies`: A list containing the generated responses as ChatMessage instances.