Class swarmauri_middleware_llamaguard.LlamaGuardMiddleware.LlamaGuardMiddleware

swarmauri_middleware_llamaguard.LlamaGuardMiddleware.LlamaGuardMiddleware

LlamaGuardMiddleware(llm=None, api_key=None, **kwargs)

Bases: MiddlewareBase, ComponentBase

Middleware for inspecting and filtering unsafe content using Groq's llama-guard-3-8b model.

This middleware integrates the :class:~swarmauri_standard.llms.GroqModel running the llama-guard-3-8b model to ensure that both incoming requests and outgoing responses are free from unsafe or malicious content. It provides a robust layer of security by inspecting both request and response payloads.

ATTRIBUTE	DESCRIPTION
type	Literal["LlamaGuardMiddleware"] = "LlamaGuardMiddleware" TYPE: Literal['LlamaGuardMiddleware']
llm	Optional[GroqModel] -- Instance of GroqModel for content inspection TYPE: Optional[GroqModel]

Initialize the LlamaGuardMiddleware with a GroqModel instance. Reads GROQ_API_KEY from environment if api_key not provided.

Source code in swarmauri_middleware_llamaguard/LlamaGuardMiddleware.py

def __init__(
    self,
    llm: Optional[GroqModel] = None,
    api_key: Optional[str] = None,
    **kwargs: Any,
) -> None:
    """Initialize the LlamaGuardMiddleware with a GroqModel instance.
    Reads GROQ_API_KEY from environment if api_key not provided."""
    super().__init__(**kwargs)

    key = api_key or getenv("GROQ_API_KEY")

    if llm is not None:
        self.llm = llm
    elif key:
        self.llm = GroqModel(
            api_key=key,
            allowed_models=["llama-guard-3-8b"],
            name="llama-guard-3-8b",
        )
    else:
        self.llm = None
        logger.warning(
            "LlamaGuardMiddleware initialized without LLM - safety checks disabled"
        )

    self.logger = logger

type class-attribute instance-attribute

type = 'LlamaGuardMiddleware'

llm class-attribute instance-attribute

llm = None

logger instance-attribute

logger = logger

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

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 after inspection.

Source code in swarmauri_middleware_llamaguard/LlamaGuardMiddleware.py

async def dispatch(
    self, request: Request, call_next: Callable[[Request], Any]
) -> Any:
    """Dispatches the request to the next middleware in the chain after inspection."""
    # Inspect incoming request body for unsafe content
    if request.method in ["POST", "PUT", "PATCH"]:
        request_body = await request.body()
        if not self._is_safe(request_body):
            return JSONResponse(
                status_code=400,
                content={"error": "Unsafe content detected in request"},
            )

    try:
        # Proceed with the request chain
        response = await call_next(request)

        # Inspect JSONResponse content
        if isinstance(response, JSONResponse):
            if hasattr(response, "body") and response.body:
                response_body = response.body
            else:
                import json

                response_body = (
                    json.dumps(response.content).encode()
                    if response.content
                    else b""
                )

            if response_body and not self._is_safe(response_body):
                return JSONResponse(
                    status_code=400,
                    content={"error": "Unsafe content detected in response"},
                )

        # Inspect StreamingResponse content
        if isinstance(response, StreamingResponse):
            try:
                chunks = []
                async for chunk in response.body_iterator:
                    chunks.append(chunk)
                full_body = b"".join(chunks)
                logger.info(f" {full_body}")

                if full_body and not self._is_safe(full_body):
                    logger.info("Unsafe content detected in streaming response")
                    return JSONResponse(
                        status_code=400,
                        content={"error": "Unsafe streaming content detected"},
                    )

                async def new_body_iterator():
                    for chunk in chunks:
                        yield chunk

                response.body_iterator = new_body_iterator()
            except Exception:
                # If streaming fails, skip inspection
                pass

        return response

    except Exception as e:
        self.logger.error(f"Error in LlamaGuardMiddleware: {str(e)}")
        return JSONResponse(
            status_code=500,
            content={"error": "Internal server error during content inspection"},
        )

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)