Python: Standardize docstrings: Use Keyword Args for Settings classes and add environment variable examples (#1202)

* Initial plan * Update Settings classes to use Keyword Args and add examples Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Add examples and env var documentation to chat clients Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Add env var docs and examples to Responses and AzureAI clients Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Remove Args from class docstrings where they belong in __init__ Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Add env var docs and examples to Assistants clients Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * updated to keyword args * Fix incorrect code block formatting in _workflows/_executor.py Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Fix markdown code blocks in _workflows/_edge.py - use Sphinx format Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Update _assistants_client.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> Co-authored-by: eavanvalkenburg <github@vanvalkenburg.eu> Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2025-10-06 07:37:34 +00:00
parent 0cd794abe7
commit 8bd3e11d3e
17 changed files with 711 additions and 477 deletions
@@ -104,13 +104,31 @@ class AzureAISettings(AFBaseSettings):
    with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
    are ignored; however, validation will fail alerting that the settings are missing.

-    Args:
+    Keyword Args:
        project_endpoint: The Azure AI Project endpoint URL.
-            (Env var AZURE_AI_PROJECT_ENDPOINT)
+            Can be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
        model_deployment_name: The name of the model deployment to use.
-            (Env var AZURE_AI_MODEL_DEPLOYMENT_NAME)
+            Can be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
        env_file_path: If provided, the .env settings are read from this file path location.
        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework_azure_ai import AzureAISettings
+
+            # Using environment variables
+            # Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
+            # Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
+            settings = AzureAISettings()
+
+            # Or passing parameters directly
+            settings = AzureAISettings(
+                project_endpoint="https://your-project.cognitiveservices.azure.com", model_deployment_name="gpt-4"
+            )
+
+            # Or loading from a .env file
+            settings = AzureAISettings(env_file_path="path/to/.env")
    """

    env_prefix: ClassVar[str] = "AZURE_AI_"
@@ -144,24 +162,47 @@ class AzureAIAgentClient(BaseChatClient):
        env_file_encoding: str | None = None,
        **kwargs: Any,
    ) -> None:
-        """Initialize a AzureAIAgentClient.
+        """Initialize an Azure AI Agent client.

-        Args:
+        Keyword Args:
            project_client: An existing AIProjectClient to use. If not provided, one will be created.
            agent_id: The ID of an existing agent to use. If not provided and project_client is provided,
                a new agent will be created (and deleted after the request). If neither project_client
                nor agent_id is provided, both will be created and managed automatically.
            agent_name: The name to use when creating new agents.
            thread_id: Default thread ID to use for conversations. Can be overridden by
-                conversation_id property, when making a request.
-            project_endpoint: The Azure AI Project endpoint URL, can also be set via
-                'AZURE_AI_PROJECT_ENDPOINT' environment variable. Is ignored when a project_client is passed.
+                conversation_id property when making a request.
+            project_endpoint: The Azure AI Project endpoint URL.
+                Can also be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
+                Ignored when a project_client is passed.
            model_deployment_name: The model deployment name to use for agent creation.
-                Can also be set via 'AZURE_AI_MODEL_DEPLOYMENT_NAME' environment variable.
+                Can also be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
            async_credential: Azure async credential to use for authentication.
            env_file_path: Path to environment file for loading settings.
            env_file_encoding: Encoding of the environment file.
-            **kwargs: Additional keyword arguments passed to the parent class.
+            kwargs: Additional keyword arguments passed to the parent class.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework_azure_ai import AzureAIAgentClient
+                from azure.identity.aio import DefaultAzureCredential
+
+                # Using environment variables
+                # Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
+                # Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
+                credential = DefaultAzureCredential()
+                client = AzureAIAgentClient(async_credential=credential)
+
+                # Or passing parameters directly
+                client = AzureAIAgentClient(
+                    project_endpoint="https://your-project.cognitiveservices.azure.com",
+                    model_deployment_name="gpt-4",
+                    async_credential=credential,
+                )
+
+                # Or loading from a .env file
+                client = AzureAIAgentClient(async_credential=credential, env_file_path="path/to/.env")
        """
        try:
            azure_ai_settings = AzureAISettings(
@@ -31,18 +31,33 @@ class CopilotStudioSettings(AFBaseSettings):
    with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
    are ignored; however, validation will fail alerting that the settings are missing.

-    Attributes:
-        environmentid: Environment ID of environment with the Copilot Studio App..
-            (Env var COPILOTSTUDIOAGENT__ENVIRONMENTID)
+    Keyword Args:
+        environmentid: Environment ID of environment with the Copilot Studio App.
+            Can be set via environment variable COPILOTSTUDIOAGENT__ENVIRONMENTID.
        schemaname: The agent identifier or schema name of the Copilot to use.
-            (Env var COPILOTSTUDIOAGENT__SCHEMANAME)
+            Can be set via environment variable COPILOTSTUDIOAGENT__SCHEMANAME.
        agentappid: The app ID of the App Registration used to login.
-            (Env var COPILOTSTUDIOAGENT__AGENTAPPID)
+            Can be set via environment variable COPILOTSTUDIOAGENT__AGENTAPPID.
        tenantid: The tenant ID of the App Registration used to login.
-            (Env var COPILOTSTUDIOAGENT__TENANTID)
-    Parameters:
+            Can be set via environment variable COPILOTSTUDIOAGENT__TENANTID.
        env_file_path: If provided, the .env settings are read from this file path location.
        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework_copilotstudio import CopilotStudioSettings
+
+            # Using environment variables
+            # Set COPILOTSTUDIOAGENT__ENVIRONMENTID=env-123
+            # Set COPILOTSTUDIOAGENT__SCHEMANAME=my-agent
+            settings = CopilotStudioSettings()
+
+            # Or passing parameters directly
+            settings = CopilotStudioSettings(environmentid="env-123", schemaname="my-agent")
+
+            # Or loading from a .env file
+            settings = CopilotStudioSettings(env_file_path="path/to/.env")
    """

    env_prefix: ClassVar[str] = "COPILOTSTUDIOAGENT__"
@@ -161,9 +161,6 @@ class ChatMessageStore:
    The store maintains messages in memory and provides methods to serialize
    and deserialize the state for persistence purposes.

-    Args:
-        messages: The optional initial list of ChatMessage objects to populate the store.
-
    Examples:
        .. code-block:: python

@@ -195,11 +195,6 @@ class BaseTool(SerializationMixin):

    This class provides the foundation for creating custom tools with serialization support.

-    Args:
-        name: The name of the tool.
-        description: A description of the tool.
-        additional_properties: Additional properties associated with the tool.
-
    Examples:
        .. code-block:: python

@@ -545,25 +540,16 @@ def _default_histogram() -> Histogram:


 class AIFunction(BaseTool, Generic[ArgsT, ReturnT]):
-    """A AITool that is callable as code.
+    """A tool that wraps a Python function to make it callable by AI models.

    This class wraps a Python function to make it callable by AI models with automatic
    parameter validation and JSON schema generation.

-    Args:
-        name: The name of the function.
-        description: A description of the function.
-        approval_mode: Whether or not approval is required to run this tool.
-            Default is that approval is not needed.
-        additional_properties: Additional properties to set on the function.
-        func: The function to wrap.
-        input_model: The Pydantic model that defines the input parameters for the function.
-
    Examples:
        .. code-block:: python

            from typing import Annotated
-            from pydantic import BaseModel
+            from pydantic import BaseModel, Field
            from agent_framework import AIFunction, ai_function


@@ -401,13 +401,7 @@ AnnotatedRegions = TextSpanRegion


 class BaseAnnotation(SerializationMixin):
-    """Base class for all AI Annotation types.
-
-    Args:
-        additional_properties: Optional additional properties associated with the content.
-        raw_representation: Optional raw representation of the content from an underlying implementation.
-
-    """
+    """Base class for all AI Annotation types."""

    DEFAULT_EXCLUDE: ClassVar[set[str]] = {"raw_representation", "additional_properties"}

@@ -20,14 +20,14 @@ def _extract_function_name(func: Callable[..., Any]) -> str:
    stable value so that serialized representations remain intelligible when
    they are later rendered in logs or reconstructed during deserialization.

-    Example:
-        ```python
-        def threshold(value: float) -> bool:
-            return value > 0.5
+    Examples:
+        .. code-block:: python
+
+            def threshold(value: float) -> bool:
+                return value > 0.5


-        assert _extract_function_name(threshold) == "threshold"
-        ```
+            assert _extract_function_name(threshold) == "threshold"
    """
    if hasattr(func, "__name__"):
        name = func.__name__
@@ -44,14 +44,14 @@ def _missing_callable(name: str) -> Callable[..., Any]:
    runtime execution, while making it obvious which callable needs to be
    re-registered.

-    Example:
-        ```python
-        guard = _missing_callable("transform_price")
-        try:
-            guard()
-        except RuntimeError as exc:
-            assert "transform_price" in str(exc)
-        ```
+    Examples:
+        .. code-block:: python
+
+            guard = _missing_callable("transform_price")
+            try:
+                guard()
+            except RuntimeError as exc:
+                assert "transform_price" in str(exc)
    """

    def _raise(*_: Any, **__: Any) -> Any:
@@ -70,12 +70,12 @@ class Edge(DictConvertible):
    serialising the edge down to primitives we can reconstruct the topology of
    a workflow irrespective of the original Python process.

-    Example:
-        ```python
-        edge = Edge(source_id="ingest", target_id="score", condition=lambda payload: payload["ready"])
-        assert edge.should_route({"ready": True}) is True
-        assert edge.should_route({"ready": False}) is False
-        ```
+    Examples:
+        .. code-block:: python
+
+            edge = Edge(source_id="ingest", target_id="score", condition=lambda payload: payload["ready"])
+            assert edge.should_route({"ready": True}) is True
+            assert edge.should_route({"ready": False}) is False
    """

    ID_SEPARATOR: ClassVar[str] = "->"
@@ -110,12 +110,12 @@ class Edge(DictConvertible):
            when the callable cannot be introspected (for example after
            deserialization).

-        Example:
-            ```python
-            edge = Edge("fetch", "parse", condition=lambda data: data.is_valid)
-            assert edge.source_id == "fetch"
-            assert edge.target_id == "parse"
-            ```
+        Examples:
+            .. code-block:: python
+
+                edge = Edge("fetch", "parse", condition=lambda data: data.is_valid)
+                assert edge.source_id == "fetch"
+                assert edge.target_id == "parse"
        """
        if not source_id:
            raise ValueError("Edge source_id must be a non-empty string")
@@ -135,11 +135,11 @@ class Edge(DictConvertible):
        adjacency lists or visualisations to refer to an edge without carrying
        the full object.

-        Example:
-            ```python
-            edge = Edge("reader", "writer")
-            assert edge.id == "reader->writer"
-            ```
+        Examples:
+            .. code-block:: python
+
+                edge = Edge("reader", "writer")
+                assert edge.id == "reader->writer"
        """
        return f"{self.source_id}{self.ID_SEPARATOR}{self.target_id}"

@@ -152,12 +152,12 @@ class Edge(DictConvertible):
        this edge. Any exception raised by the callable is deliberately allowed
        to surface to the caller to avoid masking logic bugs.

-        Example:
-            ```python
-            edge = Edge("stage1", "stage2", condition=lambda payload: payload["score"] > 0.8)
-            assert edge.should_route({"score": 0.9}) is True
-            assert edge.should_route({"score": 0.4}) is False
-            ```
+        Examples:
+            .. code-block:: python
+
+                edge = Edge("stage1", "stage2", condition=lambda payload: payload["score"] > 0.8)
+                assert edge.should_route({"score": 0.9}) is True
+                assert edge.should_route({"score": 0.4}) is False
        """
        if self._condition is None:
            return True
@@ -170,12 +170,12 @@ class Edge(DictConvertible):
        plus the condition name when it is known. Serialisation intentionally
        omits the live callable to keep payloads transport-friendly.

-        Example:
-            ```python
-            edge = Edge("reader", "writer", condition=lambda payload: payload["ok"])
-            snapshot = edge.to_dict()
-            assert snapshot == {"source_id": "reader", "target_id": "writer", "condition_name": "<lambda>"}
-            ```
+        Examples:
+            .. code-block:: python
+
+                edge = Edge("reader", "writer", condition=lambda payload: payload["ok"])
+                snapshot = edge.to_dict()
+                assert snapshot == {"source_id": "reader", "target_id": "writer", "condition_name": "<lambda>"}
        """
        payload = {"source_id": self.source_id, "target_id": self.target_id}
        if self.condition_name is not None:
@@ -191,13 +191,13 @@ class Edge(DictConvertible):
        stored `condition_name` is preserved so that downstream consumers can
        detect missing callables and re-register them where appropriate.

-        Example:
-            ```python
-            payload = {"source_id": "reader", "target_id": "writer", "condition_name": "is_ready"}
-            edge = Edge.from_dict(payload)
-            assert edge.source_id == "reader"
-            assert edge.condition_name == "is_ready"
-            ```
+        Examples:
+            .. code-block:: python
+
+                payload = {"source_id": "reader", "target_id": "writer", "condition_name": "is_ready"}
+                edge = Edge.from_dict(payload)
+                assert edge.source_id == "reader"
+                assert edge.condition_name == "is_ready"
        """
        return cls(
            source_id=data["source_id"],
@@ -217,17 +217,17 @@ class Case:
    `SwitchCaseEdgeGroupCase` so that execution can operate with live callables
    without polluting persisted state.

-    Example:
-        ```python
-        class JsonExecutor(Executor):
-            def __init__(self) -> None:
-                super().__init__(id="json", defer_discovery=True)
+    Examples:
+        .. code-block:: python
+
+            class JsonExecutor(Executor):
+                def __init__(self) -> None:
+                    super().__init__(id="json", defer_discovery=True)


-        processor = JsonExecutor()
-        case = Case(condition=lambda payload: payload["kind"] == "json", target=processor)
-        assert case.target.id == "json"
-        ```
+            processor = JsonExecutor()
+            case = Case(condition=lambda payload: payload["kind"] == "json", target=processor)
+            assert case.target.id == "json"
    """

    condition: Callable[[Any], bool]
@@ -242,16 +242,16 @@ class Default:
    practice it is guaranteed to exist so that routing never produces an empty
    target.

-    Example:
-        ```python
-        class DeadLetterExecutor(Executor):
-            def __init__(self) -> None:
-                super().__init__(id="dead_letter", defer_discovery=True)
+    Examples:
+        .. code-block:: python
+
+            class DeadLetterExecutor(Executor):
+                def __init__(self) -> None:
+                    super().__init__(id="dead_letter", defer_discovery=True)


-        fallback = Default(target=DeadLetterExecutor())
-        assert fallback.target.id == "dead_letter"
-        ```
+            fallback = Default(target=DeadLetterExecutor())
+            assert fallback.target.id == "dead_letter"
    """

    target: Executor
@@ -267,11 +267,11 @@ class EdgeGroup(DictConvertible):
    identifying information and handles serialisation duties so specialised
    groups need only maintain their additional state.

-    Example:
-        ```python
-        group = EdgeGroup([Edge("source", "sink")])
-        assert group.source_executor_ids == ["source"]
-        ```
+    Examples:
+        .. code-block:: python
+
+            group = EdgeGroup([Edge("source", "sink")])
+            assert group.source_executor_ids == ["source"]
    """

    id: str
@@ -303,12 +303,12 @@ class EdgeGroup(DictConvertible):
            Logical discriminator used to recover the appropriate subclass when
            de-serialising.

-        Example:
-            ```python
-            edges = [Edge("validate", "persist")]
-            group = EdgeGroup(edges, id="stage", type="Custom")
-            assert group.to_dict()["type"] == "Custom"
-            ```
+        Examples:
+            .. code-block:: python
+
+                edges = [Edge("validate", "persist")]
+                group = EdgeGroup(edges, id="stage", type="Custom")
+                assert group.to_dict()["type"] == "Custom"
        """
        self.id = id or f"{self.__class__.__name__}/{uuid.uuid4()}"
        self.type = type or self.__class__.__name__
@@ -321,11 +321,11 @@ class EdgeGroup(DictConvertible):
        The property preserves order-of-first-appearance so the caller can rely
        on deterministic iteration when reconstructing graph topology.

-        Example:
-            ```python
-            group = EdgeGroup([Edge("read", "write"), Edge("read", "archive")])
-            assert group.source_executor_ids == ["read"]
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = EdgeGroup([Edge("read", "write"), Edge("read", "archive")])
+                assert group.source_executor_ids == ["read"]
        """
        return list(dict.fromkeys(edge.source_id for edge in self.edges))

@@ -333,11 +333,11 @@ class EdgeGroup(DictConvertible):
    def target_executor_ids(self) -> list[str]:
        """Return the ordered, deduplicated list of downstream executor ids.

-        Example:
-            ```python
-            group = EdgeGroup([Edge("read", "write"), Edge("read", "archive")])
-            assert group.target_executor_ids == ["write", "archive"]
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = EdgeGroup([Edge("read", "write"), Edge("read", "archive")])
+                assert group.target_executor_ids == ["write", "archive"]
        """
        return list(dict.fromkeys(edge.target_id for edge in self.edges))

@@ -348,12 +348,12 @@ class EdgeGroup(DictConvertible):
        round-tripping through formats such as JSON without leaking Python
        objects.

-        Example:
-            ```python
-            group = EdgeGroup([Edge("read", "write")])
-            snapshot = group.to_dict()
-            assert snapshot["edges"][0]["source_id"] == "read"
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = EdgeGroup([Edge("read", "write")])
+                snapshot = group.to_dict()
+                assert snapshot["edges"][0]["source_id"] == "read"
        """
        return {
            "id": self.id,
@@ -370,15 +370,15 @@ class EdgeGroup(DictConvertible):
        `__name__`, which must therefore remain stable across versions when
        persisted workflows are in circulation.

-        Example:
-            ```python
-            @EdgeGroup.register
-            class CustomGroup(EdgeGroup):
-                pass
+        Examples:
+            .. code-block:: python
+
+                @EdgeGroup.register
+                class CustomGroup(EdgeGroup):
+                    pass


-            assert EdgeGroup._TYPE_REGISTRY["CustomGroup"] is CustomGroup
-            ```
+                assert EdgeGroup._TYPE_REGISTRY["CustomGroup"] is CustomGroup
        """
        cls._TYPE_REGISTRY[subclass.__name__] = subclass
        return subclass
@@ -393,12 +393,12 @@ class EdgeGroup(DictConvertible):
        even for complex group types that configure additional runtime
        callables.

-        Example:
-            ```python
-            payload = {"type": "EdgeGroup", "edges": [{"source_id": "a", "target_id": "b"}]}
-            group = EdgeGroup.from_dict(payload)
-            assert isinstance(group, EdgeGroup)
-            ```
+        Examples:
+            .. code-block:: python
+
+                payload = {"type": "EdgeGroup", "edges": [{"source_id": "a", "target_id": "b"}]}
+                group = EdgeGroup.from_dict(payload)
+                assert isinstance(group, EdgeGroup)
        """
        group_type = data.get("type", "EdgeGroup")
        target_cls = cls._TYPE_REGISTRY.get(group_type, EdgeGroup)
@@ -448,11 +448,11 @@ class SingleEdgeGroup(EdgeGroup):
    ) -> None:
        """Create a one-to-one edge group between two executors.

-        Example:
-            ```python
-            group = SingleEdgeGroup("ingest", "validate")
-            assert group.edges[0].source_id == "ingest"
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = SingleEdgeGroup("ingest", "validate")
+                assert group.edges[0].source_id == "ingest"
        """
        edge = Edge(source_id=source_id, target_id=target_id, condition=condition)
        super().__init__([edge], id=id, type=self.__class__.__name__)
@@ -503,15 +503,15 @@ class FanOutEdgeGroup(EdgeGroup):
        id:
            Stable identifier for the group; defaults to an autogenerated UUID.

-        Example:
-            ```python
-            def choose_targets(message: dict[str, Any], available: list[str]) -> list[str]:
-                return [target for target in available if message.get(target)]
+        Examples:
+            .. code-block:: python
+
+                def choose_targets(message: dict[str, Any], available: list[str]) -> list[str]:
+                    return [target for target in available if message.get(target)]


-            group = FanOutEdgeGroup("sensor", ["db", "cache"], selection_func=choose_targets)
-            assert group.selection_func is choose_targets
-            ```
+                group = FanOutEdgeGroup("sensor", ["db", "cache"], selection_func=choose_targets)
+                assert group.selection_func is choose_targets
        """
        if len(target_ids) <= 1:
            raise ValueError("FanOutEdgeGroup must contain at least two targets.")
@@ -532,11 +532,11 @@ class FanOutEdgeGroup(EdgeGroup):
        The list is defensively copied to prevent callers from mutating the
        internal state while still providing deterministic ordering.

-        Example:
-            ```python
-            group = FanOutEdgeGroup("node", ["alpha", "beta"])
-            assert group.target_ids == ["alpha", "beta"]
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = FanOutEdgeGroup("node", ["alpha", "beta"])
+                assert group.target_ids == ["alpha", "beta"]
        """
        return list(self._target_ids)

@@ -547,11 +547,11 @@ class FanOutEdgeGroup(EdgeGroup):
        When no selection function was supplied the property returns `None`,
        signalling that all targets must receive the payload.

-        Example:
-            ```python
-            group = FanOutEdgeGroup("source", ["x", "y"], selection_func=None)
-            assert group.selection_func is None
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = FanOutEdgeGroup("source", ["x", "y"], selection_func=None)
+                assert group.selection_func is None
        """
        return self._selection_func

@@ -561,12 +561,12 @@ class FanOutEdgeGroup(EdgeGroup):
        In addition to the base `EdgeGroup` payload we embed the human-friendly
        name of the selection function. The callable itself is not persisted.

-        Example:
-            ```python
-            group = FanOutEdgeGroup("source", ["a", "b"], selection_func=lambda *_: ["a"])
-            snapshot = group.to_dict()
-            assert snapshot["selection_func_name"] == "<lambda>"
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = FanOutEdgeGroup("source", ["a", "b"], selection_func=lambda *_: ["a"])
+                snapshot = group.to_dict()
+                assert snapshot["selection_func_name"] == "<lambda>"
        """
        payload = super().to_dict()
        payload["selection_func_name"] = self.selection_func_name
@@ -595,11 +595,11 @@ class FanInEdgeGroup(EdgeGroup):
        id:
            Optional explicit identifier for the edge group.

-        Example:
-            ```python
-            group = FanInEdgeGroup(["parser", "enricher"], target_id="writer")
-            assert group.to_dict()["edges"][0]["target_id"] == "writer"
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = FanInEdgeGroup(["parser", "enricher"], target_id="writer")
+                assert group.to_dict()["edges"][0]["target_id"] == "writer"
        """
        if len(source_ids) <= 1:
            raise ValueError("FanInEdgeGroup must contain at least two sources.")
@@ -645,11 +645,11 @@ class SwitchCaseEdgeGroupCase(DictConvertible):
            Human-friendly label for the predicate used for diagnostics and
            on-disk persistence.

-        Example:
-            ```python
-            case = SwitchCaseEdgeGroupCase(lambda payload: payload["type"] == "csv", target_id="csv_handler")
-            assert case.condition_name == "<lambda>"
-            ```
+        Examples:
+            .. code-block:: python
+
+                case = SwitchCaseEdgeGroupCase(lambda payload: payload["type"] == "csv", target_id="csv_handler")
+                assert case.condition_name == "<lambda>"
        """
        if not target_id:
            raise ValueError("SwitchCaseEdgeGroupCase requires a target_id")
@@ -671,26 +671,26 @@ class SwitchCaseEdgeGroupCase(DictConvertible):
        `RuntimeError` when invoked so that workflow authors are forced to
        provide the missing callable explicitly.

-        Example:
-            ```python
-            case = SwitchCaseEdgeGroupCase(None, target_id="missing", condition_name="needs_registration")
-            guard = case.condition
-            try:
-                guard({})
-            except RuntimeError:
-                pass
-            ```
+        Examples:
+            .. code-block:: python
+
+                case = SwitchCaseEdgeGroupCase(None, target_id="missing", condition_name="needs_registration")
+                guard = case.condition
+                try:
+                    guard({})
+                except RuntimeError:
+                    pass
        """
        return self._condition

    def to_dict(self) -> dict[str, Any]:
        """Serialise the case metadata without the executable predicate.

-        Example:
-            ```python
-            case = SwitchCaseEdgeGroupCase(lambda _: True, target_id="handler")
-            assert case.to_dict()["target_id"] == "handler"
-            ```
+        Examples:
+            .. code-block:: python
+
+                case = SwitchCaseEdgeGroupCase(lambda _: True, target_id="handler")
+                assert case.to_dict()["target_id"] == "handler"
        """
        payload = {"target_id": self.target_id, "type": self.type}
        if self.condition_name is not None:
@@ -701,12 +701,12 @@ class SwitchCaseEdgeGroupCase(DictConvertible):
    def from_dict(cls, data: dict[str, Any]) -> "SwitchCaseEdgeGroupCase":
        """Instantiate a case from its serialised dictionary payload.

-        Example:
-            ```python
-            payload = {"target_id": "handler", "condition_name": "is_ready"}
-            case = SwitchCaseEdgeGroupCase.from_dict(payload)
-            assert case.target_id == "handler"
-            ```
+        Examples:
+            .. code-block:: python
+
+                payload = {"target_id": "handler", "condition_name": "is_ready"}
+                case = SwitchCaseEdgeGroupCase.from_dict(payload)
+                assert case.target_id == "handler"
        """
        return cls(
            condition=None,
@@ -729,11 +729,11 @@ class SwitchCaseEdgeGroupDefault(DictConvertible):
    def __init__(self, target_id: str) -> None:
        """Point the default branch toward the given executor identifier.

-        Example:
-            ```python
-            fallback = SwitchCaseEdgeGroupDefault(target_id="dead_letter")
-            assert fallback.target_id == "dead_letter"
-            ```
+        Examples:
+            .. code-block:: python
+
+                fallback = SwitchCaseEdgeGroupDefault(target_id="dead_letter")
+                assert fallback.target_id == "dead_letter"
        """
        if not target_id:
            raise ValueError("SwitchCaseEdgeGroupDefault requires a target_id")
@@ -743,11 +743,11 @@ class SwitchCaseEdgeGroupDefault(DictConvertible):
    def to_dict(self) -> dict[str, Any]:
        """Serialise the default branch metadata for persistence or logging.

-        Example:
-            ```python
-            fallback = SwitchCaseEdgeGroupDefault("dead_letter")
-            assert fallback.to_dict()["type"] == "Default"
-            ```
+        Examples:
+            .. code-block:: python
+
+                fallback = SwitchCaseEdgeGroupDefault("dead_letter")
+                assert fallback.to_dict()["type"] == "Default"
        """
        return {"target_id": self.target_id, "type": self.type}

@@ -755,12 +755,12 @@ class SwitchCaseEdgeGroupDefault(DictConvertible):
    def from_dict(cls, data: dict[str, Any]) -> "SwitchCaseEdgeGroupDefault":
        """Recreate the default branch from its persisted form.

-        Example:
-            ```python
-            payload = {"target_id": "dead_letter", "type": "Default"}
-            fallback = SwitchCaseEdgeGroupDefault.from_dict(payload)
-            assert fallback.target_id == "dead_letter"
-            ```
+        Examples:
+            .. code-block:: python
+
+                payload = {"target_id": "dead_letter", "type": "Default"}
+                fallback = SwitchCaseEdgeGroupDefault.from_dict(payload)
+                assert fallback.target_id == "dead_letter"
        """
        return cls(target_id=data["target_id"])

@@ -797,16 +797,16 @@ class SwitchCaseEdgeGroup(FanOutEdgeGroup):
        id:
            Optional explicit identifier for the edge group.

-        Example:
-            ```python
-            cases = [
-                SwitchCaseEdgeGroupCase(lambda payload: payload["kind"] == "csv", target_id="process_csv"),
-                SwitchCaseEdgeGroupDefault(target_id="process_default"),
-            ]
-            group = SwitchCaseEdgeGroup("router", cases)
-            encoded = group.to_dict()
-            assert encoded["cases"][0]["type"] == "Case"
-            ```
+        Examples:
+            .. code-block:: python
+
+                cases = [
+                    SwitchCaseEdgeGroupCase(lambda payload: payload["kind"] == "csv", target_id="process_csv"),
+                    SwitchCaseEdgeGroupDefault(target_id="process_default"),
+                ]
+                group = SwitchCaseEdgeGroup("router", cases)
+                encoded = group.to_dict()
+                assert encoded["cases"][0]["type"] == "Case"
        """
        if len(cases) < 2:
            raise ValueError("SwitchCaseEdgeGroup must contain at least two cases (including the default case).")
@@ -849,18 +849,18 @@ class SwitchCaseEdgeGroup(FanOutEdgeGroup):
        Each case is converted using `encode_value` to respect dataclass
        semantics as well as any nested serialisable structures.

-        Example:
-            ```python
-            group = SwitchCaseEdgeGroup(
-                "router",
-                [
-                    SwitchCaseEdgeGroupCase(lambda _: True, target_id="handler"),
-                    SwitchCaseEdgeGroupDefault(target_id="fallback"),
-                ],
-            )
-            snapshot = group.to_dict()
-            assert len(snapshot["cases"]) == 2
-            ```
+        Examples:
+            .. code-block:: python
+
+                group = SwitchCaseEdgeGroup(
+                    "router",
+                    [
+                        SwitchCaseEdgeGroupCase(lambda _: True, target_id="handler"),
+                        SwitchCaseEdgeGroupDefault(target_id="fallback"),
+                    ],
+                )
+                snapshot = group.to_dict()
+                assert len(snapshot["cases"]) == 2
        """
        payload = super().to_dict()
        payload["cases"] = [encode_value(case) for case in self.cases]
@@ -178,14 +178,13 @@ class Executor(DictConvertible):

        @executor
        async def process_text(text: str, ctx: WorkflowContext[str]) -> None:
-        await ctx.send_message(text.upper())
+            await ctx.send_message(text.upper())


-    # Or with custom ID:
-    @executor(id="text_processor")
-    def sync_process(text: str, ctx: WorkflowContext[str]) -> None:
-        ctx.send_message(text.lower())  # Sync functions run in thread pool
-    ```
+        # Or with custom ID:
+        @executor(id="text_processor")
+        def sync_process(text: str, ctx: WorkflowContext[str]) -> None:
+            ctx.send_message(text.lower())  # Sync functions run in thread pool

    ## Sub-workflow Composition
    Executors can contain sub-workflows using WorkflowExecutor. Sub-workflows can make requests
@@ -23,6 +23,7 @@ class AzureOpenAIAssistantsClient(OpenAIAssistantsClient):

    def __init__(
        self,
+        *,
        deployment_name: str | None = None,
        assistant_id: str | None = None,
        assistant_name: str | None = None,
@@ -42,32 +43,56 @@ class AzureOpenAIAssistantsClient(OpenAIAssistantsClient):
    ) -> None:
        """Initialize an Azure OpenAI Assistants client.

-        Args:
+        Keyword Args:
            deployment_name: The Azure OpenAI deployment name for the model to use.
+                Can also be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
            assistant_id: The ID of an Azure OpenAI assistant to use.
                If not provided, a new assistant will be created (and deleted after the request).
            assistant_name: The name to use when creating new assistants.
            thread_id: Default thread ID to use for conversations. Can be overridden by
-                conversation_id property, when making a request.
+                conversation_id property when making a request.
                If not provided, a new thread will be created (and deleted after the request).
-            api_key: The optional API key to use. If provided will override,
-                the env vars or .env file value.
-            endpoint: The optional deployment endpoint. If provided will override the value
+            api_key: The API key to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable AZURE_OPENAI_API_KEY.
+            endpoint: The deployment endpoint. If provided will override the value
                in the env vars or .env file.
-            base_url: The optional deployment base_url. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
+            base_url: The deployment base URL. If provided will override the value
                in the env vars or .env file.
-            api_version: The optional deployment api version. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
+            api_version: The deployment API version. If provided will override the value
                in the env vars or .env file.
-            ad_token: The Azure Active Directory token. (Optional)
-            ad_token_provider: The Azure Active Directory token provider. (Optional)
-            token_endpoint: The token endpoint to request an Azure token. (Optional)
-            credential: The Azure credential to use for authentication. (Optional)
+                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
+            ad_token: The Azure Active Directory token.
+            ad_token_provider: The Azure Active Directory token provider.
+            token_endpoint: The token endpoint to request an Azure token.
+                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
+            credential: The Azure credential to use for authentication.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            env_file_path: Use the environment settings file as a fallback
-                to environment variables. (Optional)
-            env_file_encoding: The encoding of the environment settings file. (Optional)
+                to environment variables.
+            env_file_encoding: The encoding of the environment settings file.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.azure import AzureOpenAIAssistantsClient
+
+                # Using environment variables
+                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
+                # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=gpt-4
+                # Set AZURE_OPENAI_API_KEY=your-key
+                client = AzureOpenAIAssistantsClient()
+
+                # Or passing parameters directly
+                client = AzureOpenAIAssistantsClient(
+                    endpoint="https://your-endpoint.openai.azure.com", deployment_name="gpt-4", api_key="your-key"
+                )
+
+                # Or loading from a .env file
+                client = AzureOpenAIAssistantsClient(env_file_path="path/to/.env")
        """
        try:
            azure_openai_settings = AzureOpenAISettings(
@@ -65,31 +65,55 @@ class AzureOpenAIChatClient(AzureOpenAIConfigMixin, OpenAIBaseChatClient):
        instruction_role: str | None = None,
        **kwargs: Any,
    ) -> None:
-        """Initialize an AzureChatCompletion service.
+        """Initialize an Azure OpenAI Chat completion client.

        Args:
-            api_key: The optional api key. If provided, will override the value in the
-                env vars or .env file.
-            deployment_name: The optional deployment. If provided, will override the value
+            api_key: The API key. If provided, will override the value in the env vars or .env file.
+                Can also be set via environment variable AZURE_OPENAI_API_KEY.
+            deployment_name: The deployment name. If provided, will override the value
                (chat_deployment_name) in the env vars or .env file.
-            endpoint: The optional deployment endpoint. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
+            endpoint: The deployment endpoint. If provided will override the value
                in the env vars or .env file.
-            base_url: The optional deployment base_url. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
+            base_url: The deployment base URL. If provided will override the value
                in the env vars or .env file.
-            api_version: The optional deployment api version. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
+            api_version: The deployment API version. If provided will override the value
                in the env vars or .env file.
-            ad_token: The Azure Active Directory token. (Optional)
-            ad_token_provider: The Azure Active Directory token provider. (Optional)
-            token_endpoint: The token endpoint to request an Azure token. (Optional)
-            credential: The Azure credential for authentication. (Optional)
+                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
+            ad_token: The Azure Active Directory token.
+            ad_token_provider: The Azure Active Directory token provider.
+            token_endpoint: The token endpoint to request an Azure token.
+                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
+            credential: The Azure credential for authentication.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            env_file_path: Use the environment settings file as a fallback to using env vars.
            env_file_encoding: The encoding of the environment settings file, defaults to 'utf-8'.
            instruction_role: The role to use for 'instruction' messages, for example, summarization
-                prompts could use `developer` or `system`. (Optional)
+                prompts could use `developer` or `system`.
            kwargs: Other keyword parameters.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.azure import AzureOpenAIChatClient
+
+                # Using environment variables
+                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
+                # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=gpt-4
+                # Set AZURE_OPENAI_API_KEY=your-key
+                client = AzureOpenAIChatClient()
+
+                # Or passing parameters directly
+                client = AzureOpenAIChatClient(
+                    endpoint="https://your-endpoint.openai.azure.com", deployment_name="gpt-4", api_key="your-key"
+                )
+
+                # Or loading from a .env file
+                client = AzureOpenAIChatClient(env_file_path="path/to/.env")
        """
        try:
            # Filter out any None values from the arguments
@@ -29,6 +29,7 @@ class AzureOpenAIResponsesClient(AzureOpenAIConfigMixin, OpenAIBaseResponsesClie

    def __init__(
        self,
+        *,
        api_key: str | None = None,
        deployment_name: str | None = None,
        endpoint: str | None = None,
@@ -45,31 +46,55 @@ class AzureOpenAIResponsesClient(AzureOpenAIConfigMixin, OpenAIBaseResponsesClie
        instruction_role: str | None = None,
        **kwargs: Any,
    ) -> None:
-        """Initialize an AzureResponses service.
+        """Initialize an Azure OpenAI Responses client.

-        Args:
-            api_key: The optional api key. If provided, will override the value in the
-                env vars or .env file.
-            deployment_name: The optional deployment. If provided, will override the value
+        Keyword Args:
+            api_key: The API key. If provided, will override the value in the env vars or .env file.
+                Can also be set via environment variable AZURE_OPENAI_API_KEY.
+            deployment_name: The deployment name. If provided, will override the value
                (responses_deployment_name) in the env vars or .env file.
-            endpoint: The optional deployment endpoint. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
+            endpoint: The deployment endpoint. If provided will override the value
                in the env vars or .env file.
-            base_url: The optional deployment base_url. If provided will override the value
-                in the env vars or .env file. Currently, the base_url must end with "/openai/v1/"
-            api_version: The optional deployment api version. If provided will override the value
+                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
+            base_url: The deployment base URL. If provided will override the value
+                in the env vars or .env file. Currently, the base_url must end with "/openai/v1/".
+                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
+            api_version: The deployment API version. If provided will override the value
                in the env vars or .env file. Currently, the api_version must be "preview".
-            ad_token: The Azure Active Directory token. (Optional)
-            ad_token_provider: The Azure Active Directory token provider. (Optional)
-            token_endpoint: The token endpoint to request an Azure token. (Optional)
-            credential: The Azure credential for authentication. (Optional)
+                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
+            ad_token: The Azure Active Directory token.
+            ad_token_provider: The Azure Active Directory token provider.
+            token_endpoint: The token endpoint to request an Azure token.
+                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
+            credential: The Azure credential for authentication.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            env_file_path: Use the environment settings file as a fallback to using env vars.
            env_file_encoding: The encoding of the environment settings file, defaults to 'utf-8'.
            instruction_role: The role to use for 'instruction' messages, for example, summarization
-                prompts could use `developer` or `system`. (Optional)
+                prompts could use `developer` or `system`.
            kwargs: Additional keyword arguments.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.azure import AzureOpenAIResponsesClient
+
+                # Using environment variables
+                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
+                # Set AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME=gpt-4o
+                # Set AZURE_OPENAI_API_KEY=your-key
+                client = AzureOpenAIResponsesClient()
+
+                # Or passing parameters directly
+                client = AzureOpenAIResponsesClient(
+                    endpoint="https://your-endpoint.openai.azure.com", deployment_name="gpt-4o", api_key="your-key"
+                )
+
+                # Or loading from a .env file
+                client = AzureOpenAIResponsesClient(env_file_path="path/to/.env")
        """
        if model_id := kwargs.pop("model_id", None) and not deployment_name:
            deployment_name = str(model_id)
@@ -37,45 +37,64 @@ class AzureOpenAISettings(AFBaseSettings):
    with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
    are ignored; however, validation will fail alerting that the settings are missing.

-    Args:
+    Keyword Args:
        endpoint: The endpoint of the Azure deployment. This value
            can be found in the Keys & Endpoint section when examining
            your resource from the Azure portal, the endpoint should end in openai.azure.com.
            If both base_url and endpoint are supplied, base_url will be used.
-            (Env var AZURE_OPENAI_ENDPOINT)
+            Can be set via environment variable AZURE_OPENAI_ENDPOINT.
        chat_deployment_name: The name of the Azure Chat deployment. This value
            will correspond to the custom name you chose for your deployment
            when you deployed a model. This value can be found under
            Resource Management > Deployments in the Azure portal or, alternatively,
            under Management > Deployments in Azure AI Foundry.
-            (Env var AZURE_OPENAI_CHAT_DEPLOYMENT_NAME)
+            Can be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
        responses_deployment_name: The name of the Azure Responses deployment. This value
            will correspond to the custom name you chose for your deployment
            when you deployed a model. This value can be found under
            Resource Management > Deployments in the Azure portal or, alternatively,
            under Management > Deployments in Azure AI Foundry.
-            (Env var AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME)
+            Can be set via environment variable AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
        api_key: The API key for the Azure deployment. This value can be
            found in the Keys & Endpoint section when examining your resource in
            the Azure portal. You can use either KEY1 or KEY2.
-            (Env var AZURE_OPENAI_API_KEY)
+            Can be set via environment variable AZURE_OPENAI_API_KEY.
        api_version: The API version to use. The default value is `default_api_version`.
-            (Env var AZURE_OPENAI_API_VERSION)
+            Can be set via environment variable AZURE_OPENAI_API_VERSION.
        base_url: The url of the Azure deployment. This value
            can be found in the Keys & Endpoint section when examining
            your resource from the Azure portal, the base_url consists of the endpoint,
            followed by /openai/deployments/{deployment_name}/,
            use endpoint if you only want to supply the endpoint.
-            (Env var AZURE_OPENAI_BASE_URL)
+            Can be set via environment variable AZURE_OPENAI_BASE_URL.
        token_endpoint: The token endpoint to use to retrieve the authentication token.
            The default value is `default_token_endpoint`.
-            (Env var AZURE_OPENAI_TOKEN_ENDPOINT)
+            Can be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
        default_api_version: The default API version to use if not specified.
            The default value is "2024-10-21".
        default_token_endpoint: The default token endpoint to use if not specified.
            The default value is "https://cognitiveservices.azure.com/.default".
        env_file_path: The path to the .env file to load settings from.
        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework.azure import AzureOpenAISettings
+
+            # Using environment variables
+            # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
+            # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=gpt-4
+            # Set AZURE_OPENAI_API_KEY=your-key
+            settings = AzureOpenAISettings()
+
+            # Or passing parameters directly
+            settings = AzureOpenAISettings(
+                endpoint="https://your-endpoint.openai.azure.com", chat_deployment_name="gpt-4", api_key="your-key"
+            )
+
+            # Or loading from a .env file
+            settings = AzureOpenAISettings(env_file_path="path/to/.env")
    """

    env_prefix: ClassVar[str] = "AZURE_OPENAI_"
@@ -349,18 +349,33 @@ class ObservabilitySettings(AFBaseSettings):
    Warning:
        Sensitive events should only be enabled on test and development environments.

-    Args:
+    Keyword Args:
        enable_otel: Enable OpenTelemetry diagnostics. Default is False.
-                    (Env var ENABLE_OTEL)
+            Can be set via environment variable ENABLE_OTEL.
        enable_sensitive_data: Enable OpenTelemetry sensitive events. Default is False.
-                    (Env var ENABLE_SENSITIVE_DATA)
+            Can be set via environment variable ENABLE_SENSITIVE_DATA.
        applicationinsights_connection_string: The Azure Monitor connection string. Default is None.
-                    (Env var APPLICATIONINSIGHTS_CONNECTION_STRING)
-        otlp_endpoint:  The OpenTelemetry Protocol (OTLP) endpoint. Default is None.
-                    (Env var OTLP_ENDPOINT)
-        vs_code_extension_port: The port the AI Toolkit or AzureAI Foundry VS Code extensions are listening on.
-                    Default is None.
-                    (Env var VS_CODE_EXTENSION_PORT)
+            Can be set via environment variable APPLICATIONINSIGHTS_CONNECTION_STRING.
+        otlp_endpoint: The OpenTelemetry Protocol (OTLP) endpoint. Default is None.
+            Can be set via environment variable OTLP_ENDPOINT.
+        vs_code_extension_port: The port the AI Toolkit or Azure AI Foundry VS Code extensions are listening on.
+            Default is None.
+            Can be set via environment variable VS_CODE_EXTENSION_PORT.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework import ObservabilitySettings
+
+            # Using environment variables
+            # Set ENABLE_OTEL=true
+            # Set APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=...
+            settings = ObservabilitySettings()
+
+            # Or passing parameters directly
+            settings = ObservabilitySettings(
+                enable_otel=True, applicationinsights_connection_string="InstrumentationKey=..."
+            )
    """

    env_prefix: ClassVar[str] = ""
@@ -60,6 +60,7 @@ class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient):

    def __init__(
        self,
+        *,
        model_id: str | None = None,
        assistant_id: str | None = None,
        assistant_name: str | None = None,
@@ -75,27 +76,44 @@ class OpenAIAssistantsClient(OpenAIConfigMixin, BaseChatClient):
    ) -> None:
        """Initialize an OpenAI Assistants client.

-        Args:
-            model_id: OpenAI model name, see
-                https://platform.openai.com/docs/models
+        Keyword Args:
+            model_id: OpenAI model name, see https://platform.openai.com/docs/models.
+                Can also be set via environment variable OPENAI_CHAT_MODEL_ID.
            assistant_id: The ID of an OpenAI assistant to use.
                If not provided, a new assistant will be created (and deleted after the request).
            assistant_name: The name to use when creating new assistants.
            thread_id: Default thread ID to use for conversations. Can be overridden by
-                conversation_id property, when making a request.
+                conversation_id property when making a request.
                If not provided, a new thread will be created (and deleted after the request).
-            api_key: The optional API key to use. If provided will override,
-                the env vars or .env file value.
-            org_id: The optional org ID to use. If provided will override,
-                the env vars or .env file value.
-            base_url: The optional base URL to use. If provided will override,
+            api_key: The API key to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_API_KEY.
+            org_id: The org ID to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_ORG_ID.
+            base_url: The base URL to use. If provided will override the standard value.
+                Can also be set via environment variable OPENAI_BASE_URL.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            env_file_path: Use the environment settings file as a fallback
-                to environment variables. (Optional)
-            env_file_encoding: The encoding of the environment settings file. (Optional)
+                to environment variables.
+            env_file_encoding: The encoding of the environment settings file.
            kwargs: Other keyword parameters.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.openai import OpenAIAssistantsClient
+
+                # Using environment variables
+                # Set OPENAI_API_KEY=sk-...
+                # Set OPENAI_CHAT_MODEL_ID=gpt-4
+                client = OpenAIAssistantsClient()
+
+                # Or passing parameters directly
+                client = OpenAIAssistantsClient(model_id="gpt-4", api_key="sk-...")
+
+                # Or loading from a .env file
+                client = OpenAIAssistantsClient(env_file_path="path/to/.env")
        """
        try:
            openai_settings = OpenAISettings(
@@ -465,6 +465,7 @@ class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient):

    def __init__(
        self,
+        *,
        model_id: str | None = None,
        api_key: str | None = None,
        org_id: str | None = None,
@@ -475,26 +476,42 @@ class OpenAIChatClient(OpenAIConfigMixin, OpenAIBaseChatClient):
        env_file_path: str | None = None,
        env_file_encoding: str | None = None,
    ) -> None:
-        """Initialize an OpenAIChatCompletion service.
+        """Initialize an OpenAI Chat completion client.

-        Args:
-            model_id: OpenAI model name, see
-                https://platform.openai.com/docs/models
-            api_key: The optional API key to use. If provided will override,
-                the env vars or .env file value.
-            org_id: The optional org ID to use. If provided will override,
-                the env vars or .env file value.
+        Keyword Args:
+            model_id: OpenAI model name, see https://platform.openai.com/docs/models.
+                Can also be set via environment variable OPENAI_CHAT_MODEL_ID.
+            api_key: The API key to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_API_KEY.
+            org_id: The org ID to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_ORG_ID.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            instruction_role: The role to use for 'instruction' messages, for example,
                "system" or "developer". If not provided, the default is "system".
-            base_url: The optional base URL to use. If provided will override
-                the standard value for a OpenAI connector,
-                the env vars or .env file value.
+            base_url: The base URL to use. If provided will override
+                the standard value for an OpenAI connector, the env vars or .env file value.
+                Can also be set via environment variable OPENAI_BASE_URL.
            env_file_path: Use the environment settings file as a fallback
-                to environment variables. (Optional)
-            env_file_encoding: The encoding of the environment settings file. (Optional)
+                to environment variables.
+            env_file_encoding: The encoding of the environment settings file.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.openai import OpenAIChatClient
+
+                # Using environment variables
+                # Set OPENAI_API_KEY=sk-...
+                # Set OPENAI_CHAT_MODEL_ID=gpt-4
+                client = OpenAIChatClient()
+
+                # Or passing parameters directly
+                client = OpenAIChatClient(model_id="gpt-4", api_key="sk-...")
+
+                # Or loading from a .env file
+                client = OpenAIChatClient(env_file_path="path/to/.env")
        """
        try:
            openai_settings = OpenAISettings(
@@ -945,6 +945,7 @@ class OpenAIResponsesClient(OpenAIConfigMixin, OpenAIBaseResponsesClient):

    def __init__(
        self,
+        *,
        model_id: str | None = None,
        api_key: str | None = None,
        org_id: str | None = None,
@@ -956,25 +957,42 @@ class OpenAIResponsesClient(OpenAIConfigMixin, OpenAIBaseResponsesClient):
        env_file_encoding: str | None = None,
        **kwargs: Any,
    ) -> None:
-        """Initialize an OpenAIChatCompletion service.
+        """Initialize an OpenAI Responses client.

-        Args:
-            model_id: OpenAI model name, see
-                https://platform.openai.com/docs/models
-            api_key: The optional API key to use. If provided will override,
-                the env vars or .env file value.
-            org_id: The optional org ID to use. If provided will override,
-                the env vars or .env file value.
-            base_url: The optional base URL to use. If provided will override,
+        Keyword Args:
+            model_id: OpenAI model name, see https://platform.openai.com/docs/models.
+                Can also be set via environment variable OPENAI_RESPONSES_MODEL_ID.
+            api_key: The API key to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_API_KEY.
+            org_id: The org ID to use. If provided will override the env vars or .env file value.
+                Can also be set via environment variable OPENAI_ORG_ID.
+            base_url: The base URL to use. If provided will override the standard value.
+                Can also be set via environment variable OPENAI_BASE_URL.
            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests. (Optional)
-            async_client: An existing client to use. (Optional)
+                string values for HTTP requests.
+            async_client: An existing client to use.
            instruction_role: The role to use for 'instruction' messages, for example,
                "system" or "developer". If not provided, the default is "system".
            env_file_path: Use the environment settings file as a fallback
-                to environment variables. (Optional)
-            env_file_encoding: The encoding of the environment settings file. (Optional)
+                to environment variables.
+            env_file_encoding: The encoding of the environment settings file.
            kwargs: Other keyword parameters.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.openai import OpenAIResponsesClient
+
+                # Using environment variables
+                # Set OPENAI_API_KEY=sk-...
+                # Set OPENAI_RESPONSES_MODEL_ID=gpt-4o
+                client = OpenAIResponsesClient()
+
+                # Or passing parameters directly
+                client = OpenAIResponsesClient(model_id="gpt-4o", api_key="sk-...")
+
+                # Or loading from a .env file
+                client = OpenAIResponsesClient(env_file_path="path/to/.env")
        """
        try:
            openai_settings = OpenAISettings(
@@ -57,19 +57,35 @@ class OpenAISettings(AFBaseSettings):
    encoding 'utf-8'. If the settings are not found in the .env file, the settings are ignored;
    however, validation will fail alerting that the settings are missing.

-    Args:
-        api_key: OpenAI API key, see https://platform.openai.com/account/api-keys
-            (Env var OPENAI_API_KEY)
+    Keyword Args:
+        api_key: OpenAI API key, see https://platform.openai.com/account/api-keys.
+            Can be set via environment variable OPENAI_API_KEY.
        base_url: The base URL for the OpenAI API.
-            (Env var OPENAI_BASE_URL)
+            Can be set via environment variable OPENAI_BASE_URL.
        org_id: This is usually optional unless your account belongs to multiple organizations.
-            (Env var OPENAI_ORG_ID)
+            Can be set via environment variable OPENAI_ORG_ID.
        chat_model_id: The OpenAI chat model ID to use, for example, gpt-3.5-turbo or gpt-4.
-            (Env var OPENAI_CHAT_MODEL_ID)
+            Can be set via environment variable OPENAI_CHAT_MODEL_ID.
        responses_model_id: The OpenAI responses model ID to use, for example, gpt-4o or o1.
-            (Env var OPENAI_RESPONSES_MODEL_ID)
+            Can be set via environment variable OPENAI_RESPONSES_MODEL_ID.
        env_file_path: The path to the .env file to load settings from.
        env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework.openai import OpenAISettings
+
+            # Using environment variables
+            # Set OPENAI_API_KEY=sk-...
+            # Set OPENAI_CHAT_MODEL_ID=gpt-4
+            settings = OpenAISettings()
+
+            # Or passing parameters directly
+            settings = OpenAISettings(api_key="sk-...", chat_model_id="gpt-4")
+
+            # Or loading from a .env file
+            settings = OpenAISettings(env_file_path="path/to/.env")
    """

    env_prefix: ClassVar[str] = "OPENAI_"
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