Class swarmauri_middleware_session.SessionMiddleware.SessionMiddleware

swarmauri_middleware_session.SessionMiddleware.SessionMiddleware

SessionMiddleware(
    session_storage=None,
    session_header="X-Session-ID",
    session_cookie="session_id",
    max_age=3600,
    **kwargs,
)

Bases: MiddlewareBase, ComponentBase

Session middleware for maintaining session state across requests.

This middleware tracks sessions using headers or cookies. It ensures that session state is maintained across multiple requests from the same client.

ATTRIBUTE	DESCRIPTION
session_storage	Dict[str, Dict] = {} # Storage for session data TYPE: Dict[str, Dict]
session_header	str = "X-Session-ID" # Header name for session ID TYPE: str
session_cookie	str = "session_id" # Cookie name for session ID TYPE: str
max_age	int = 3600 # Default session expiration in seconds TYPE: int

METHOD	DESCRIPTION
dispatch	Implements the core middleware dispatch logic

Source code in swarmauri_middleware_session/SessionMiddleware.py

def __init__(
    self,
    session_storage: Optional[Dict[str, Dict]] = None,
    session_header: Optional[str] = "X-Session-ID",
    session_cookie: Optional[str] = "session_id",
    max_age: int = 3600,
    **kwargs: Any,
) -> None:
    super().__init__(**kwargs)
    self.session_storage = session_storage if session_storage is not None else {}
    self.session_header = session_header or "X-Session-ID"
    self.session_cookie = session_cookie or "session_id"
    self.max_age = max_age

session_storage class-attribute instance-attribute

session_storage = (
    session_storage if session_storage is not None else {}
)

session_header class-attribute instance-attribute

session_header = session_header or 'X-Session-ID'

session_cookie class-attribute instance-attribute

session_cookie = session_cookie or 'session_id'

max_age class-attribute instance-attribute

max_age = max_age

type class-attribute instance-attribute

type = 'ComponentBase'

model_config class-attribute instance-attribute

model_config = ConfigDict(
    extra="allow", arbitrary_types_allowed=True
)

id class-attribute instance-attribute

id = Field(default_factory=generate_id)

members class-attribute instance-attribute

members = None

owners class-attribute instance-attribute

owners = None

host class-attribute instance-attribute

host = None

default_logger class-attribute

default_logger = None

logger class-attribute instance-attribute

logger = None

name class-attribute instance-attribute

name = None

resource class-attribute instance-attribute

resource = MIDDLEWARE.value

version class-attribute instance-attribute

version = '0.1.0'

app property

app

dispatch async

dispatch(request, call_next)

Dispatches the request to the next middleware in the chain while maintaining session state.

This method processes the request to check for an existing session or create a new one. It ensures that session state is maintained across requests by setting appropriate headers or cookies.

PARAMETER	DESCRIPTION
request	The incoming request object TYPE: Request
call_next	A callable that invokes the next middleware in the chain TYPE: Callable[[Request], Any]

RETURNS	DESCRIPTION
Any	The response object after processing the request

Source code in swarmauri_middleware_session/SessionMiddleware.py

async def dispatch(
    self, request: Request, call_next: Callable[[Request], Any]
) -> Any:
    """Dispatches the request to the next middleware in the chain while maintaining session state.

    This method processes the request to check for an existing session or create a new one.
    It ensures that session state is maintained across requests by setting appropriate
    headers or cookies.

    Args:
        request: The incoming request object
        call_next: A callable that invokes the next middleware in the chain

    Returns:
        The response object after processing the request

    Raises:
        None
    """
    # Check if session ID exists in request headers
    session_id: Optional[str] = request.headers.get(self.session_header)

    if session_id:
        # Session exists - update session storage
        if session_id not in self.session_storage:
            logger.warning(
                f"Session ID {session_id} exists in header but not in storage"
            )
            # Create new session data
            self.session_storage[session_id] = {}
        else:
            logger.debug(f"Session {session_id} found in storage")
    else:
        # Create new session
        session_id = self._generate_session_id()
        logger.info(f"Created new session: {session_id}")
        self.session_storage[session_id] = {}

    # Add session ID to request state
    request.state.session_id = session_id

    # Process the request with next middleware
    response = await call_next(request)

    # Ensure session ID is set in response headers
    response.headers[self.session_header] = session_id

    # Set session cookie if not present
    if self.session_cookie not in response.headers:
        response.headers[self.session_cookie] = session_id
        response.headers["Set-Cookie"] = (
            f"{self.session_cookie}={session_id}; Max-Age={self.max_age}"
        )

    return response

register_model classmethod

register_model()

Decorator to register a base model in the unified registry.

RETURNS	DESCRIPTION
Callable	A decorator function that registers the model class. TYPE: Callable[[Type[BaseModel]], Type[BaseModel]]

Source code in swarmauri_base/DynamicBase.py

@classmethod
def register_model(cls) -> Callable[[Type[BaseModel]], Type[BaseModel]]:
    """
    Decorator to register a base model in the unified registry.

    Returns:
        Callable: A decorator function that registers the model class.
    """

    def decorator(model_cls: Type[BaseModel]):
        """Register ``model_cls`` as a base model."""
        model_name = model_cls.__name__
        if model_name in cls._registry:
            glogger.warning(
                "Model '%s' is already registered; skipping duplicate.", model_name
            )
            return model_cls

        cls._registry[model_name] = {"model_cls": model_cls, "subtypes": {}}
        glogger.debug("Registered base model '%s'.", model_name)
        DynamicBase._recreate_models()
        return model_cls

    return decorator

register_type classmethod

register_type(resource_type=None, type_name=None)

Decorator to register a subtype under one or more base models in the unified registry.

PARAMETER	DESCRIPTION
resource_type	The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase) are used. TYPE: Optional[Union[Type[T], List[Type[T]]]] DEFAULT: None
type_name	An optional custom type name for the subtype. TYPE: Optional[str] DEFAULT: None

RETURNS	DESCRIPTION
Callable	A decorator function that registers the subtype. TYPE: Callable[[Type[DynamicBase]], Type[DynamicBase]]

Source code in swarmauri_base/DynamicBase.py

@classmethod
def register_type(
    cls,
    resource_type: Optional[Union[Type[T], List[Type[T]]]] = None,
    type_name: Optional[str] = None,
) -> Callable[[Type["DynamicBase"]], Type["DynamicBase"]]:
    """
    Decorator to register a subtype under one or more base models in the unified registry.

    Parameters:
        resource_type (Optional[Union[Type[T], List[Type[T]]]]):
            The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase)
            are used.
        type_name (Optional[str]): An optional custom type name for the subtype.

    Returns:
        Callable: A decorator function that registers the subtype.
    """

    def decorator(subclass: Type["DynamicBase"]):
        """Register ``subclass`` as a subtype."""
        if resource_type is None:
            resource_types = [
                base for base in subclass.__bases__ if base is not cls
            ]
        elif not isinstance(resource_type, list):
            resource_types = [resource_type]
        else:
            resource_types = resource_type

        for rt in resource_types:
            if not issubclass(subclass, rt):
                raise TypeError(
                    f"'{subclass.__name__}' must be a subclass of '{rt.__name__}'."
                )
            final_type_name = type_name or getattr(
                subclass, "_type", subclass.__name__
            )
            base_model_name = rt.__name__

            if base_model_name not in cls._registry:
                cls._registry[base_model_name] = {"model_cls": rt, "subtypes": {}}
                glogger.debug(
                    "Created new registry entry for base model '%s'.",
                    base_model_name,
                )

            subtypes_dict = cls._registry[base_model_name]["subtypes"]
            if final_type_name in subtypes_dict:
                glogger.warning(
                    "Type '%s' already exists under '%s'; skipping duplicate.",
                    final_type_name,
                    base_model_name,
                )
                continue

            subtypes_dict[final_type_name] = subclass
            glogger.debug(
                "Registered '%s' as '%s' under '%s'.",
                subclass.__name__,
                final_type_name,
                base_model_name,
            )

        DynamicBase._recreate_models()
        return subclass

    return decorator

model_validate_toml classmethod

model_validate_toml(toml_data)

Validate a model from a TOML string.

Source code in swarmauri_base/TomlMixin.py

@classmethod
def model_validate_toml(cls, toml_data: str):
    """Validate a model from a TOML string."""
    try:
        # Parse TOML into a Python dictionary
        toml_content = tomllib.loads(toml_data)

        # Convert the dictionary to JSON and validate using Pydantic
        return cls.model_validate_json(json.dumps(toml_content))
    except tomllib.TOMLDecodeError as e:
        raise ValueError(f"Invalid TOML data: {e}")
    except ValidationError as e:
        raise ValueError(f"Validation failed: {e}")

model_dump_toml

model_dump_toml(
    fields_to_exclude=None, api_key_placeholder=None
)

Return a TOML representation of the model.

Source code in swarmauri_base/TomlMixin.py

def model_dump_toml(self, fields_to_exclude=None, api_key_placeholder=None):
    """Return a TOML representation of the model."""
    if fields_to_exclude is None:
        fields_to_exclude = []

    # Load the JSON string into a Python dictionary
    json_data = json.loads(self.model_dump_json())

    # Function to recursively remove specific keys and handle api_key placeholders
    def process_fields(data, fields_to_exclude):
        """Recursively filter fields and apply placeholders."""
        if isinstance(data, dict):
            return {
                key: (
                    api_key_placeholder
                    if key == "api_key" and api_key_placeholder is not None
                    else process_fields(value, fields_to_exclude)
                )
                for key, value in data.items()
                if key not in fields_to_exclude
            }
        elif isinstance(data, list):
            return [process_fields(item, fields_to_exclude) for item in data]
        else:
            return data

    # Filter the JSON data
    filtered_data = process_fields(json_data, fields_to_exclude)

    # Convert the filtered data into TOML
    return toml.dumps(filtered_data)

model_validate_yaml classmethod

model_validate_yaml(yaml_data)

Validate a model from a YAML string.

Source code in swarmauri_base/YamlMixin.py

@classmethod
def model_validate_yaml(cls, yaml_data: str):
    """Validate a model from a YAML string."""
    try:
        # Parse YAML into a Python dictionary
        yaml_content = yaml.safe_load(yaml_data)

        # Convert the dictionary to JSON and validate using Pydantic
        return cls.model_validate_json(json.dumps(yaml_content))
    except yaml.YAMLError as e:
        raise ValueError(f"Invalid YAML data: {e}")
    except ValidationError as e:
        raise ValueError(f"Validation failed: {e}")

model_dump_yaml

model_dump_yaml(
    fields_to_exclude=None, api_key_placeholder=None
)

Return a YAML representation of the model.

Source code in swarmauri_base/YamlMixin.py

def model_dump_yaml(self, fields_to_exclude=None, api_key_placeholder=None):
    """Return a YAML representation of the model."""
    if fields_to_exclude is None:
        fields_to_exclude = []

    # Load the JSON string into a Python dictionary
    json_data = json.loads(self.model_dump_json())

    # Function to recursively remove specific keys and handle api_key placeholders
    def process_fields(data, fields_to_exclude):
        """Recursively filter fields and apply placeholders."""
        if isinstance(data, dict):
            return {
                key: (
                    api_key_placeholder
                    if key == "api_key" and api_key_placeholder is not None
                    else process_fields(value, fields_to_exclude)
                )
                for key, value in data.items()
                if key not in fields_to_exclude
            }
        elif isinstance(data, list):
            return [process_fields(item, fields_to_exclude) for item in data]
        else:
            return data

    # Filter the JSON data
    filtered_data = process_fields(json_data, fields_to_exclude)

    # Convert the filtered data into YAML using safe mode
    return yaml.safe_dump(filtered_data, default_flow_style=False)

model_post_init

model_post_init(logger=None)

Assign a logger instance after model initialization.

Source code in swarmauri_base/LoggerMixin.py

def model_post_init(self, logger: Optional[FullUnion[LoggerBase]] = None) -> None:
    """Assign a logger instance after model initialization."""

    # Directly assign the provided FullUnion[LoggerBase] or fallback to the
    # class-level default.
    self.logger = self.logger or logger or self.default_logger

on_scope async

on_scope(scope)

Hook executed when the middleware receives a scope.

Source code in swarmauri_base/middlewares/MiddlewareBase.py

async def on_scope(self, scope: Scope) -> Scope:
    """Hook executed when the middleware receives a scope."""

    return scope

on_receive async

on_receive(scope, message)

Hook executed for every message received from the client.

Source code in swarmauri_base/middlewares/MiddlewareBase.py

async def on_receive(self, scope: Scope, message: Message) -> Message:
    """Hook executed for every message received from the client."""

    return message

on_send async

on_send(scope, message)

Hook executed before messages are sent to the client.

Source code in swarmauri_base/middlewares/MiddlewareBase.py

async def on_send(self, scope: Scope, message: Message) -> Message:
    """Hook executed before messages are sent to the client."""

    return message

bind

bind(app)

Bind the downstream ASGI application to the middleware.

Source code in swarmauri_base/middlewares/MiddlewareBase.py

def bind(self, app: ASGIApp) -> None:
    """Bind the downstream ASGI application to the middleware."""

    self._app = app

call_next async

call_next(scope, receive, send)

Invoke the next ASGI application in the chain.

Source code in swarmauri_base/middlewares/MiddlewareBase.py

async def call_next(
    self, scope: Scope, receive: ReceiveCallable, send: SendCallable
) -> None:
    """Invoke the next ASGI application in the chain."""

    await self.app(scope, receive, send)