docs: sync Core Integrations API reference (litellm) on Docusaurus

docs-website/reference/integrations-api/litellm.md

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+---
+title: "LiteLLM"
+id: integrations-litellm
+description: "LiteLLM integration for Haystack"
+slug: "/integrations-litellm"
+---
+
+
+## haystack_integrations.components.generators.litellm.chat.chat_generator
+
+### LiteLLMChatGenerator
+
+Completes chats using any of 100+ LLM providers via LiteLLM.
+
+LiteLLM routes to OpenAI, Anthropic, Google, AWS Bedrock, Azure, Cohere,
+Mistral, Groq, and many more through a single unified interface.
+
+Model names use LiteLLM format: `provider/model-name`, e.g.
+`anthropic/claude-sonnet-4-20250514`, `openai/gpt-4o`,
+`bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0`.
+
+See https://docs.litellm.ai/docs/providers for the full list.
+
+Usage example:
+
+```python
+from haystack_integrations.components.generators.litellm import LiteLLMChatGenerator
+from haystack.dataclasses import ChatMessage
+
+generator = LiteLLMChatGenerator(
+    model="anthropic/claude-sonnet-4-20250514",
+    generation_kwargs={"max_tokens": 1024, "temperature": 0.7},
+)
+
+messages = [
+    ChatMessage.from_system("You are a helpful assistant"),
+    ChatMessage.from_user("What's Natural Language Processing?"),
+]
+result = generator.run(messages=messages)
+print(result["replies"][0].text)
+```
+
+#### __init__
+
+```python
+__init__(
+    *,
+    api_key: Secret | None = None,
+    model: str = "openai/gpt-4o",
+    streaming_callback: StreamingCallbackT | None = None,
+    api_base_url: str | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    tools: ToolsType | None = None
+) -> None
+```
+
+Create a LiteLLMChatGenerator instance.
+
+**Parameters:**
+
+- **api_key** (<code>Secret | None</code>) – The API key for the provider. Optional: when not set, LiteLLM resolves
+  credentials itself from the provider's standard environment variable
+  (e.g. `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`). Pass a `Secret` only
+  when you want Haystack to manage and serialize the key explicitly.
+- **model** (<code>str</code>) – The model name in LiteLLM format (provider/model-name).
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – A callback function invoked with each new StreamingChunk.
+- **api_base_url** (<code>str | None</code>) – Custom API base URL (e.g. for a self-hosted LiteLLM proxy).
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Additional parameters passed to litellm.completion().
+  See https://docs.litellm.ai/docs/completion/input for details.
+- **tools** (<code>ToolsType | None</code>) – A list of Tool / Toolset objects the model can prepare calls for.
+
+#### run
+
+```python
+run(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Invoke chat completion via LiteLLM.
+
+**Parameters:**
+
+- **messages** (<code>list\[ChatMessage\]</code>) – Input messages as ChatMessage instances.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – Override the streaming callback for this call.
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Override generation parameters for this call.
+- **tools** (<code>ToolsType | None</code>) – Override tools for this call.
+
+**Returns:**
+
+- <code>dict\[str, list\[ChatMessage\]\]</code> – A dict with key `replies` containing ChatMessage instances.
+
+#### run_async
+
+```python
+run_async(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Async version of run().
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serialize this component to a dictionary.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> LiteLLMChatGenerator
+```
+
+Deserialize a component from a dictionary.

docs-website/reference_versioned_docs/version-2.18/integrations-api/litellm.md

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+---
+title: "LiteLLM"
+id: integrations-litellm
+description: "LiteLLM integration for Haystack"
+slug: "/integrations-litellm"
+---
+
+
+## haystack_integrations.components.generators.litellm.chat.chat_generator
+
+### LiteLLMChatGenerator
+
+Completes chats using any of 100+ LLM providers via LiteLLM.
+
+LiteLLM routes to OpenAI, Anthropic, Google, AWS Bedrock, Azure, Cohere,
+Mistral, Groq, and many more through a single unified interface.
+
+Model names use LiteLLM format: `provider/model-name`, e.g.
+`anthropic/claude-sonnet-4-20250514`, `openai/gpt-4o`,
+`bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0`.
+
+See https://docs.litellm.ai/docs/providers for the full list.
+
+Usage example:
+
+```python
+from haystack_integrations.components.generators.litellm import LiteLLMChatGenerator
+from haystack.dataclasses import ChatMessage
+
+generator = LiteLLMChatGenerator(
+    model="anthropic/claude-sonnet-4-20250514",
+    generation_kwargs={"max_tokens": 1024, "temperature": 0.7},
+)
+
+messages = [
+    ChatMessage.from_system("You are a helpful assistant"),
+    ChatMessage.from_user("What's Natural Language Processing?"),
+]
+result = generator.run(messages=messages)
+print(result["replies"][0].text)
+```
+
+#### __init__
+
+```python
+__init__(
+    *,
+    api_key: Secret | None = None,
+    model: str = "openai/gpt-4o",
+    streaming_callback: StreamingCallbackT | None = None,
+    api_base_url: str | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    tools: ToolsType | None = None
+) -> None
+```
+
+Create a LiteLLMChatGenerator instance.
+
+**Parameters:**
+
+- **api_key** (<code>Secret | None</code>) – The API key for the provider. Optional: when not set, LiteLLM resolves
+  credentials itself from the provider's standard environment variable
+  (e.g. `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`). Pass a `Secret` only
+  when you want Haystack to manage and serialize the key explicitly.
+- **model** (<code>str</code>) – The model name in LiteLLM format (provider/model-name).
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – A callback function invoked with each new StreamingChunk.
+- **api_base_url** (<code>str | None</code>) – Custom API base URL (e.g. for a self-hosted LiteLLM proxy).
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Additional parameters passed to litellm.completion().
+  See https://docs.litellm.ai/docs/completion/input for details.
+- **tools** (<code>ToolsType | None</code>) – A list of Tool / Toolset objects the model can prepare calls for.
+
+#### run
+
+```python
+run(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Invoke chat completion via LiteLLM.
+
+**Parameters:**
+
+- **messages** (<code>list\[ChatMessage\]</code>) – Input messages as ChatMessage instances.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – Override the streaming callback for this call.
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Override generation parameters for this call.
+- **tools** (<code>ToolsType | None</code>) – Override tools for this call.
+
+**Returns:**
+
+- <code>dict\[str, list\[ChatMessage\]\]</code> – A dict with key `replies` containing ChatMessage instances.
+
+#### run_async
+
+```python
+run_async(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Async version of run().
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serialize this component to a dictionary.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> LiteLLMChatGenerator
+```
+
+Deserialize a component from a dictionary.

docs-website/reference_versioned_docs/version-2.19/integrations-api/litellm.md

@@ -0,0 +1,125 @@
+---
+title: "LiteLLM"
+id: integrations-litellm
+description: "LiteLLM integration for Haystack"
+slug: "/integrations-litellm"
+---
+
+
+## haystack_integrations.components.generators.litellm.chat.chat_generator
+
+### LiteLLMChatGenerator
+
+Completes chats using any of 100+ LLM providers via LiteLLM.
+
+LiteLLM routes to OpenAI, Anthropic, Google, AWS Bedrock, Azure, Cohere,
+Mistral, Groq, and many more through a single unified interface.
+
+Model names use LiteLLM format: `provider/model-name`, e.g.
+`anthropic/claude-sonnet-4-20250514`, `openai/gpt-4o`,
+`bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0`.
+
+See https://docs.litellm.ai/docs/providers for the full list.
+
+Usage example:
+
+```python
+from haystack_integrations.components.generators.litellm import LiteLLMChatGenerator
+from haystack.dataclasses import ChatMessage
+
+generator = LiteLLMChatGenerator(
+    model="anthropic/claude-sonnet-4-20250514",
+    generation_kwargs={"max_tokens": 1024, "temperature": 0.7},
+)
+
+messages = [
+    ChatMessage.from_system("You are a helpful assistant"),
+    ChatMessage.from_user("What's Natural Language Processing?"),
+]
+result = generator.run(messages=messages)
+print(result["replies"][0].text)
+```
+
+#### __init__
+
+```python
+__init__(
+    *,
+    api_key: Secret | None = None,
+    model: str = "openai/gpt-4o",
+    streaming_callback: StreamingCallbackT | None = None,
+    api_base_url: str | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    tools: ToolsType | None = None
+) -> None
+```
+
+Create a LiteLLMChatGenerator instance.
+
+**Parameters:**
+
+- **api_key** (<code>Secret | None</code>) – The API key for the provider. Optional: when not set, LiteLLM resolves
+  credentials itself from the provider's standard environment variable
+  (e.g. `ANTHROPIC_API_KEY`, `OPENAI_API_KEY`). Pass a `Secret` only
+  when you want Haystack to manage and serialize the key explicitly.
+- **model** (<code>str</code>) – The model name in LiteLLM format (provider/model-name).
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – A callback function invoked with each new StreamingChunk.
+- **api_base_url** (<code>str | None</code>) – Custom API base URL (e.g. for a self-hosted LiteLLM proxy).
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Additional parameters passed to litellm.completion().
+  See https://docs.litellm.ai/docs/completion/input for details.
+- **tools** (<code>ToolsType | None</code>) – A list of Tool / Toolset objects the model can prepare calls for.
+
+#### run
+
+```python
+run(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Invoke chat completion via LiteLLM.
+
+**Parameters:**
+
+- **messages** (<code>list\[ChatMessage\]</code>) – Input messages as ChatMessage instances.
+- **streaming_callback** (<code>StreamingCallbackT | None</code>) – Override the streaming callback for this call.
+- **generation_kwargs** (<code>dict\[str, Any\] | None</code>) – Override generation parameters for this call.
+- **tools** (<code>ToolsType | None</code>) – Override tools for this call.
+
+**Returns:**
+
+- <code>dict\[str, list\[ChatMessage\]\]</code> – A dict with key `replies` containing ChatMessage instances.
+
+#### run_async
+
+```python
+run_async(
+    messages: list[ChatMessage],
+    streaming_callback: StreamingCallbackT | None = None,
+    generation_kwargs: dict[str, Any] | None = None,
+    *,
+    tools: ToolsType | None = None
+) -> dict[str, list[ChatMessage]]
+```
+
+Async version of run().
+
+#### to_dict
+
+```python
+to_dict() -> dict[str, Any]
+```
+
+Serialize this component to a dictionary.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> LiteLLMChatGenerator
+```
+
+Deserialize a component from a dictionary.