docs: manual update for integrations API references

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

@@ -1135,7 +1135,7 @@ def __init__(
         generation_kwargs: Optional[Dict[str, Any]] = None,
         streaming_callback: Optional[StreamingCallbackT] = None,
         boto3_config: Optional[Dict[str, Any]] = None,
-        tools: Optional[Union[List[Tool], Toolset]] = None,
+        tools: Optional[ToolsType] = None,
         *,
         guardrail_config: Optional[Dict[str, str]] = None) -> None
 ```
@@ -1168,7 +1168,8 @@ function that handles the streaming chunks. The callback function receives a
 [StreamingChunk](https://docs.haystack.deepset.ai/docs/data-classes#streamingchunk) object and switches
 the streaming mode on.
 - `boto3_config`: The configuration for the boto3 client.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should have a unique name.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+Each tool should have a unique name.
 - `guardrail_config`: Optional configuration for a guardrail that has been created in Amazon Bedrock.
 This must be provided as a dictionary matching either
 [GuardrailConfiguration](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_GuardrailConfiguration.html).
@@ -1227,12 +1228,10 @@ Instance of `AmazonBedrockChatGenerator`.
 
 ```python
 @component.output_types(replies=List[ChatMessage])
-def run(
-    messages: List[ChatMessage],
-    streaming_callback: Optional[StreamingCallbackT] = None,
-    generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None
-) -> Dict[str, List[ChatMessage]]
+def run(messages: List[ChatMessage],
+        streaming_callback: Optional[StreamingCallbackT] = None,
+        generation_kwargs: Optional[Dict[str, Any]] = None,
+        tools: Optional[ToolsType] = None) -> Dict[str, List[ChatMessage]]
 ```
 
 Executes a synchronous inference call to the Amazon Bedrock model using the Converse API.
@@ -1248,7 +1247,8 @@ Supports both standard and streaming responses depending on whether a streaming
 - `stopSequences`: List of stop sequences to stop generation.
 - `temperature`: Sampling temperature.
 - `topP`: Nucleus sampling parameter.
-- `tools`: Optional list of Tools that the model may call during execution.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+Each tool should have a unique name.
 
 **Raises**:
 
@@ -1265,11 +1265,10 @@ A dictionary containing the model-generated replies under the `"replies"` key.
 ```python
 @component.output_types(replies=List[ChatMessage])
 async def run_async(
-    messages: List[ChatMessage],
-    streaming_callback: Optional[StreamingCallbackT] = None,
-    generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None
-) -> Dict[str, List[ChatMessage]]
+        messages: List[ChatMessage],
+        streaming_callback: Optional[StreamingCallbackT] = None,
+        generation_kwargs: Optional[Dict[str, Any]] = None,
+        tools: Optional[ToolsType] = None) -> Dict[str, List[ChatMessage]]
 ```
 
 Executes an asynchronous inference call to the Amazon Bedrock model using the Converse API.
@@ -1285,7 +1284,8 @@ Designed for use cases where non-blocking or concurrent execution is desired.
 - `stopSequences`: List of stop sequences to stop generation.
 - `temperature`: Sampling temperature.
 - `topP`: Nucleus sampling parameter.
-- `tools`: Optional list of Tool objects or a Toolset that the model can use.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+Each tool should have a unique name.
 
 **Raises**:
 

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

@@ -196,7 +196,7 @@ def __init__(api_key: Secret = Secret.from_env_var("ANTHROPIC_API_KEY"),
              streaming_callback: Optional[StreamingCallbackT] = None,
              generation_kwargs: Optional[Dict[str, Any]] = None,
              ignore_tools_thinking_messages: bool = True,
-             tools: Optional[Union[List[Tool], Toolset]] = None,
+             tools: Optional[ToolsType] = None,
              *,
              timeout: Optional[float] = None,
              max_retries: Optional[int] = None)
@@ -231,7 +231,8 @@ Supported generation_kwargs parameters are:
 `ignore_tools_thinking_messages` is `True`, the generator will drop so-called thinking messages when tool
 use is detected. See the Anthropic [tools](https://docs.anthropic.com/en/docs/tool-use#chain-of-thought-tool-use)
 for more details.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should have a unique name.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset, that the model can use.
+Each tool should have a unique name.
 - `timeout`: Timeout for Anthropic client calls. If not set, it defaults to the default set by the Anthropic client.
 - `max_retries`: Maximum number of retries to attempt for failed requests. If not set, it defaults to the default set by
 the Anthropic client.
@@ -275,12 +276,10 @@ The deserialized component instance.
 
 ```python
 @component.output_types(replies=List[ChatMessage])
-def run(
-    messages: List[ChatMessage],
-    streaming_callback: Optional[StreamingCallbackT] = None,
-    generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None
-) -> Dict[str, List[ChatMessage]]
+def run(messages: List[ChatMessage],
+        streaming_callback: Optional[StreamingCallbackT] = None,
+        generation_kwargs: Optional[Dict[str, Any]] = None,
+        tools: Optional[ToolsType] = None) -> Dict[str, List[ChatMessage]]
 ```
 
 Invokes the Anthropic API with the given messages and generation kwargs.
@@ -290,8 +289,9 @@ Invokes the Anthropic API with the given messages and generation kwargs.
 - `messages`: A list of ChatMessage instances representing the input messages.
 - `streaming_callback`: A callback function that is called when a new token is received from the stream.
 - `generation_kwargs`: Optional arguments to pass to the Anthropic generation endpoint.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should
-have a unique name. If set, it will override the `tools` parameter set during component initialization.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset, that the model can use.
+Each tool should have a unique name. If set, it will override the `tools` parameter set during component
+initialization.
 
 **Returns**:
 
@@ -305,11 +305,10 @@ A dictionary with the following keys:
 ```python
 @component.output_types(replies=List[ChatMessage])
 async def run_async(
-    messages: List[ChatMessage],
-    streaming_callback: Optional[StreamingCallbackT] = None,
-    generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None
-) -> Dict[str, List[ChatMessage]]
+        messages: List[ChatMessage],
+        streaming_callback: Optional[StreamingCallbackT] = None,
+        generation_kwargs: Optional[Dict[str, Any]] = None,
+        tools: Optional[ToolsType] = None) -> Dict[str, List[ChatMessage]]
 ```
 
 Async version of the run method. Invokes the Anthropic API with the given messages and generation kwargs.
@@ -319,8 +318,9 @@ Async version of the run method. Invokes the Anthropic API with the given messag
 - `messages`: A list of ChatMessage instances representing the input messages.
 - `streaming_callback`: A callback function that is called when a new token is received from the stream.
 - `generation_kwargs`: Optional arguments to pass to the Anthropic generation endpoint.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should
-have a unique name. If set, it will override the `tools` parameter set during component initialization.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset, that the model can use.
+Each tool should have a unique name. If set, it will override the `tools` parameter set during component
+initialization.
 
 **Returns**:
 
@@ -392,7 +392,7 @@ def __init__(region: str,
                                                    None]] = None,
              generation_kwargs: Optional[Dict[str, Any]] = None,
              ignore_tools_thinking_messages: bool = True,
-             tools: Optional[List[Tool]] = None,
+             tools: Optional[ToolsType] = None,
              *,
              timeout: Optional[float] = None,
              max_retries: Optional[int] = None)
@@ -425,7 +425,8 @@ Supported generation_kwargs parameters are:
 `ignore_tools_thinking_messages` is `True`, the generator will drop so-called thinking messages when tool
 use is detected. See the Anthropic [tools](https://docs.anthropic.com/en/docs/tool-use#chain-of-thought-tool-use)
 for more details.
-- `tools`: A list of Tool objects that the model can use. Each tool should have a unique name.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset, that the model can use.
+Each tool should have a unique name.
 - `timeout`: Timeout for Anthropic client calls. If not set, it defaults to the default set by the Anthropic client.
 - `max_retries`: Maximum number of retries to attempt for failed requests. If not set, it defaults to the default set by
 the Anthropic client.

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

@@ -745,7 +745,7 @@ def __init__(api_key: Secret = Secret.from_env_var(
              streaming_callback: Optional[StreamingCallbackT] = None,
              api_base_url: Optional[str] = None,
              generation_kwargs: Optional[Dict[str, Any]] = None,
-             tools: Optional[Union[List[Tool], Toolset]] = None,
+             tools: Optional[ToolsType] = None,
              **kwargs: Any)
 ```
 
@@ -770,7 +770,8 @@ Some of the parameters are:
   `accurate` results or `fast` results.
 - 'temperature': A non-negative float that tunes the degree of randomness in generation. Lower temperatures
   mean less random generations.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should have a unique name.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset that the model can use.
+Each tool should have a unique name.
 
 <a id="haystack_integrations.components.generators.cohere.chat.chat_generator.CohereChatGenerator.to_dict"></a>
 
@@ -814,7 +815,7 @@ Deserialized component.
 def run(
     messages: List[ChatMessage],
     generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None,
+    tools: Optional[ToolsType] = None,
     streaming_callback: Optional[StreamingCallbackT] = None
 ) -> Dict[str, List[ChatMessage]]
 ```
@@ -828,8 +829,8 @@ Invoke the chat endpoint based on the provided messages and generation parameter
 potentially override the parameters passed in the __init__ method.
 For more details on the parameters supported by the Cohere API, refer to the
 Cohere [documentation](https://docs.cohere.com/reference/chat).
-- `tools`: A list of tools or a Toolset for which the model can prepare calls. If set, it will override
-the `tools` parameter set during component initialization.
+- `tools`: 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 set during component initialization.
 - `streaming_callback`: A callback function that is called when a new token is received from the stream.
 The callback function accepts StreamingChunk as an argument.
 
@@ -847,7 +848,7 @@ A dictionary with the following keys:
 async def run_async(
     messages: List[ChatMessage],
     generation_kwargs: Optional[Dict[str, Any]] = None,
-    tools: Optional[Union[List[Tool], Toolset]] = None,
+    tools: Optional[ToolsType] = None,
     streaming_callback: Optional[StreamingCallbackT] = None
 ) -> Dict[str, List[ChatMessage]]
 ```
@@ -861,8 +862,8 @@ Asynchronously invoke the chat endpoint based on the provided messages and gener
 potentially override the parameters passed in the __init__ method.
 For more details on the parameters supported by the Cohere API, refer to the
 Cohere [documentation](https://docs.cohere.com/reference/chat).
-- `tools`: A list of tools for which the model can prepare calls. If set, it will override
-the `tools` parameter set during component initialization.
+- `tools`: 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 set during component initialization.
 - `streaming_callback`: A callback function that is called when a new token is received from the stream.
 
 **Returns**:

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

@@ -131,7 +131,7 @@ def __init__(*,
              generation_kwargs: Optional[Dict[str, Any]] = None,
              safety_settings: Optional[List[Dict[str, Any]]] = None,
              streaming_callback: Optional[StreamingCallbackT] = None,
-             tools: Optional[Union[List[Tool], Toolset]] = None)
+             tools: Optional[ToolsType] = None)
 ```
 
 Initialize a GoogleGenAIChatGenerator instance.
@@ -156,7 +156,8 @@ For Gemini 2.5 series, supports `thinking_budget` to configure thinking behavior
   - Positive integer: Set explicit budget
 - `safety_settings`: Safety settings for content filtering
 - `streaming_callback`: A callback function that is called when a new token is received from the stream.
-- `tools`: A list of Tool objects or a Toolset that the model can use. Each tool should have a unique name.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+Each tool should have a unique name.
 
 <a id="haystack_integrations.components.generators.google_genai.chat.chat_generator.GoogleGenAIChatGenerator.to_dict"></a>
 
@@ -201,7 +202,7 @@ def run(messages: List[ChatMessage],
         generation_kwargs: Optional[Dict[str, Any]] = None,
         safety_settings: Optional[List[Dict[str, Any]]] = None,
         streaming_callback: Optional[StreamingCallbackT] = None,
-        tools: Optional[Union[List[Tool], Toolset]] = None) -> Dict[str, Any]
+        tools: Optional[ToolsType] = None) -> Dict[str, Any]
 ```
 
 Run the Google Gen AI chat generator on the given input data.
@@ -215,8 +216,8 @@ the default config. Supports `thinking_budget` for Gemini 2.5 series thinking co
 default settings.
 - `streaming_callback`: A callback function that is called when a new token is
 received from the stream.
-- `tools`: A list of Tool objects or a Toolset that the model can use. If provided, it will
-override the tools set during initialization.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+If provided, it will override the tools set during initialization.
 
 **Raises**:
 
@@ -235,12 +236,11 @@ A dictionary with the following keys:
 
 ```python
 @component.output_types(replies=List[ChatMessage])
-async def run_async(
-        messages: List[ChatMessage],
-        generation_kwargs: Optional[Dict[str, Any]] = None,
-        safety_settings: Optional[List[Dict[str, Any]]] = None,
-        streaming_callback: Optional[StreamingCallbackT] = None,
-        tools: Optional[Union[List[Tool], Toolset]] = None) -> Dict[str, Any]
+async def run_async(messages: List[ChatMessage],
+                    generation_kwargs: Optional[Dict[str, Any]] = None,
+                    safety_settings: Optional[List[Dict[str, Any]]] = None,
+                    streaming_callback: Optional[StreamingCallbackT] = None,
+                    tools: Optional[ToolsType] = None) -> Dict[str, Any]
 ```
 
 Async version of the run method. Run the Google Gen AI chat generator on the given input data.
@@ -255,8 +255,8 @@ See https://ai.google.dev/gemini-api/docs/thinking for possible values.
 default settings.
 - `streaming_callback`: A callback function that is called when a new token is
 received from the stream.
-- `tools`: A list of Tool objects or a Toolset that the model can use. If provided, it will
-override the tools set during initialization.
+- `tools`: A list of Tool and/or Toolset objects, or a single Toolset for which the model can prepare calls.
+If provided, it will override the tools set during initialization.
 
 **Raises**: