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

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

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+---
+title: "Datadog"
+id: integrations-datadog
+description: "Datadog integration for Haystack"
+slug: "/integrations-datadog"
+---
+
+
+## haystack_integrations.components.connectors.datadog.datadog_connector
+
+### DatadogConnector
+
+DatadogConnector connects Haystack to [Datadog](https://www.datadoghq.com/) in order to enable the tracing of
+
+operations and data flow within the components of a pipeline.
+
+To use the DatadogConnector, add it to your pipeline without connecting it to any other component. It will
+automatically trace all pipeline operations when tracing is enabled.
+
+**Environment Configuration:**
+
+- `HAYSTACK_CONTENT_TRACING_ENABLED`: Must be set to `"true"` to trace the content (inputs and outputs) of the
+  pipeline components.
+- Datadog is configured through the standard `ddtrace` mechanisms, e.g. the `DD_SERVICE`, `DD_ENV` and
+  `DD_VERSION` environment variables or by running your application with the `ddtrace-run` command. See the
+  [ddtrace documentation](https://ddtrace.readthedocs.io/en/stable/) for more details.
+
+Here is an example of how to use the DatadogConnector in a pipeline:
+
+```python
+import os
+
+os.environ["HAYSTACK_CONTENT_TRACING_ENABLED"] = "true"
+
+from haystack import Pipeline
+from haystack.components.builders import ChatPromptBuilder
+from haystack.components.generators.chat import OpenAIChatGenerator
+from haystack.dataclasses import ChatMessage
+from haystack_integrations.components.connectors.datadog import DatadogConnector
+
+pipe = Pipeline()
+pipe.add_component("tracer", DatadogConnector("Chat example"))
+pipe.add_component("prompt_builder", ChatPromptBuilder())
+pipe.add_component("llm", OpenAIChatGenerator(model="gpt-4o-mini"))
+
+pipe.connect("prompt_builder.prompt", "llm.messages")
+
+messages = [
+    ChatMessage.from_system("Always respond in German even if some input data is in other languages."),
+    ChatMessage.from_user("Tell me about {{location}}"),
+]
+
+response = pipe.run(
+    data={"prompt_builder": {"template_variables": {"location": "Berlin"}, "template": messages}}
+)
+print(response["llm"]["replies"][0])
+```
+
+#### __init__
+
+```python
+__init__(name: str = 'datadog') -> None
+```
+
+Initialize the DatadogConnector component.
+
+**Parameters:**
+
+- **name** (<code>str</code>) – The name used to identify this tracing component. It is returned by the `run` method and can be
+  used to mark traces produced by this connector.
+
+#### run
+
+```python
+run() -> dict[str, str]
+```
+
+Runs the DatadogConnector component.
+
+**Returns:**
+
+- <code>dict\[str, str\]</code> – A dictionary with the following keys:
+- `name`: The name of the tracing component.
+
+#### 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.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> DatadogConnector
+```
+
+Deserialize this component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – The dictionary representation of this component.
+
+**Returns:**
+
+- <code>DatadogConnector</code> – The deserialized component instance.
+
+## haystack_integrations.tracing.datadog.tracer
+
+### DatadogSpan
+
+Bases: <code>Span</code>
+
+#### __init__
+
+```python
+__init__(span: ddSpan) -> None
+```
+
+Creates an instance of DatadogSpan.
+
+#### set_tag
+
+```python
+set_tag(key: str, value: Any) -> None
+```
+
+Set a single tag on the span.
+
+**Parameters:**
+
+- **key** (<code>str</code>) – the name of the tag.
+- **value** (<code>Any</code>) – the value of the tag.
+
+#### raw_span
+
+```python
+raw_span() -> Any
+```
+
+Provides access to the underlying span object of the tracer.
+
+**Returns:**
+
+- <code>Any</code> – The underlying span object.
+
+#### get_correlation_data_for_logs
+
+```python
+get_correlation_data_for_logs() -> dict[str, Any]
+```
+
+Return a dictionary with correlation data for logs.
+
+### DatadogTracer
+
+Bases: <code>Tracer</code>
+
+#### __init__
+
+```python
+__init__(tracer: ddTracer) -> None
+```
+
+Creates an instance of DatadogTracer.
+
+#### trace
+
+```python
+trace(
+    operation_name: str,
+    tags: dict[str, Any] | None = None,
+    parent_span: Span | None = None,
+) -> Iterator[Span]
+```
+
+Activate and return a new span that inherits from the current active span.
+
+#### current_span
+
+```python
+current_span() -> Span | None
+```
+
+Return the current active span

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

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+---
+title: "Datadog"
+id: integrations-datadog
+description: "Datadog integration for Haystack"
+slug: "/integrations-datadog"
+---
+
+
+## haystack_integrations.components.connectors.datadog.datadog_connector
+
+### DatadogConnector
+
+DatadogConnector connects Haystack to [Datadog](https://www.datadoghq.com/) in order to enable the tracing of
+
+operations and data flow within the components of a pipeline.
+
+To use the DatadogConnector, add it to your pipeline without connecting it to any other component. It will
+automatically trace all pipeline operations when tracing is enabled.
+
+**Environment Configuration:**
+
+- `HAYSTACK_CONTENT_TRACING_ENABLED`: Must be set to `"true"` to trace the content (inputs and outputs) of the
+  pipeline components.
+- Datadog is configured through the standard `ddtrace` mechanisms, e.g. the `DD_SERVICE`, `DD_ENV` and
+  `DD_VERSION` environment variables or by running your application with the `ddtrace-run` command. See the
+  [ddtrace documentation](https://ddtrace.readthedocs.io/en/stable/) for more details.
+
+Here is an example of how to use the DatadogConnector in a pipeline:
+
+```python
+import os
+
+os.environ["HAYSTACK_CONTENT_TRACING_ENABLED"] = "true"
+
+from haystack import Pipeline
+from haystack.components.builders import ChatPromptBuilder
+from haystack.components.generators.chat import OpenAIChatGenerator
+from haystack.dataclasses import ChatMessage
+from haystack_integrations.components.connectors.datadog import DatadogConnector
+
+pipe = Pipeline()
+pipe.add_component("tracer", DatadogConnector("Chat example"))
+pipe.add_component("prompt_builder", ChatPromptBuilder())
+pipe.add_component("llm", OpenAIChatGenerator(model="gpt-4o-mini"))
+
+pipe.connect("prompt_builder.prompt", "llm.messages")
+
+messages = [
+    ChatMessage.from_system("Always respond in German even if some input data is in other languages."),
+    ChatMessage.from_user("Tell me about {{location}}"),
+]
+
+response = pipe.run(
+    data={"prompt_builder": {"template_variables": {"location": "Berlin"}, "template": messages}}
+)
+print(response["llm"]["replies"][0])
+```
+
+#### __init__
+
+```python
+__init__(name: str = 'datadog') -> None
+```
+
+Initialize the DatadogConnector component.
+
+**Parameters:**
+
+- **name** (<code>str</code>) – The name used to identify this tracing component. It is returned by the `run` method and can be
+  used to mark traces produced by this connector.
+
+#### run
+
+```python
+run() -> dict[str, str]
+```
+
+Runs the DatadogConnector component.
+
+**Returns:**
+
+- <code>dict\[str, str\]</code> – A dictionary with the following keys:
+- `name`: The name of the tracing component.
+
+#### 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.
+
+#### from_dict
+
+```python
+from_dict(data: dict[str, Any]) -> DatadogConnector
+```
+
+Deserialize this component from a dictionary.
+
+**Parameters:**
+
+- **data** (<code>dict\[str, Any\]</code>) – The dictionary representation of this component.
+
+**Returns:**
+
+- <code>DatadogConnector</code> – The deserialized component instance.
+
+## haystack_integrations.tracing.datadog.tracer
+
+### DatadogSpan
+
+Bases: <code>Span</code>
+
+#### __init__
+
+```python
+__init__(span: ddSpan) -> None
+```
+
+Creates an instance of DatadogSpan.
+
+#### set_tag
+
+```python
+set_tag(key: str, value: Any) -> None
+```
+
+Set a single tag on the span.
+
+**Parameters:**
+
+- **key** (<code>str</code>) – the name of the tag.
+- **value** (<code>Any</code>) – the value of the tag.
+
+#### raw_span
+
+```python
+raw_span() -> Any
+```
+
+Provides access to the underlying span object of the tracer.
+
+**Returns:**
+
+- <code>Any</code> – The underlying span object.
+
+#### get_correlation_data_for_logs
+
+```python
+get_correlation_data_for_logs() -> dict[str, Any]
+```
+
+Return a dictionary with correlation data for logs.
+
+### DatadogTracer
+
+Bases: <code>Tracer</code>
+
+#### __init__
+
+```python
+__init__(tracer: ddTracer) -> None
+```
+
+Creates an instance of DatadogTracer.
+
+#### trace
+
+```python
+trace(
+    operation_name: str,
+    tags: dict[str, Any] | None = None,
+    parent_span: Span | None = None,
+) -> Iterator[Span]
+```
+
+Activate and return a new span that inherits from the current active span.
+
+#### current_span
+
+```python
+current_span() -> Span | None
+```
+
+Return the current active span