Class swarmauri_standard.key_providers.InMemoryKeyProvider.InMemoryKeyProvider

swarmauri_standard.key_providers.InMemoryKeyProvider.InMemoryKeyProvider

InMemoryKeyProvider(**kwargs)

Bases: KeyProviderBase

Simple in-memory key provider for testing or ephemeral usage.

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

def __init__(self, **kwargs) -> None:
    super().__init__(**kwargs)
    self._store: Dict[str, Dict[int, KeyRef]] = {}

type class-attribute instance-attribute

type = 'InMemoryKeyProvider'

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 = Field(default=CRYPTO.value, frozen=True)

version class-attribute instance-attribute

version = '0.1.0'

supports

supports()

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

def supports(self) -> Mapping[str, Iterable[str]]:
    return {
        "class": ("sym", "asym"),
        "algs": (),
        "features": ("create", "import", "rotate"),
    }

create_key async

create_key(spec)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def create_key(self, spec: KeySpec) -> KeyRef:
    kid = secrets.token_hex(8)
    version = 1
    material = secrets.token_bytes(32)
    ref = KeyRef(
        kid=kid,
        version=version,
        type=(
            KeyType.SYMMETRIC
            if spec.klass == KeyClass.symmetric
            else KeyType.OPAQUE
        ),
        uses=tuple(spec.uses),
        export_policy=spec.export_policy,
        material=(material if spec.export_policy != ExportPolicy.NONE else None),
        tags={"label": spec.label or "", **(spec.tags or {})},
    )
    self._store.setdefault(kid, {})[version] = ref
    return ref

import_key async

import_key(spec, material, *, public=None)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def import_key(
    self,
    spec: KeySpec,
    material: bytes,
    *,
    public: Optional[bytes] = None,
) -> KeyRef:
    kid = secrets.token_hex(8)
    version = 1
    ref = KeyRef(
        kid=kid,
        version=version,
        type=(
            KeyType.SYMMETRIC
            if spec.klass == KeyClass.symmetric
            else KeyType.OPAQUE
        ),
        uses=tuple(spec.uses),
        export_policy=spec.export_policy,
        material=(material if spec.export_policy != ExportPolicy.NONE else None),
        public=public,
        tags={"label": spec.label or "", **(spec.tags or {})},
    )
    self._store.setdefault(kid, {})[version] = ref
    return ref

rotate_key async

rotate_key(kid, *, spec_overrides=None)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def rotate_key(
    self, kid: str, *, spec_overrides: Optional[dict] = None
) -> KeyRef:
    bucket = self._store.get(kid)
    if not bucket:
        raise KeyError(f"Unknown kid: {kid}")
    latest = max(bucket)
    base = bucket[latest]
    material = secrets.token_bytes(len(base.material or b"\x00" * 32))
    version = latest + 1
    ref = KeyRef(
        kid=kid,
        version=version,
        type=base.type,
        uses=base.uses,
        export_policy=base.export_policy,
        material=(material if base.export_policy != ExportPolicy.NONE else None),
        public=base.public,
        tags=base.tags,
        uri=base.uri,
    )
    bucket[version] = ref
    return ref

destroy_key async

destroy_key(kid, version=None)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def destroy_key(self, kid: str, version: Optional[int] = None) -> bool:
    bucket = self._store.get(kid)
    if not bucket:
        return False
    if version is None:
        del self._store[kid]
        return True
    bucket.pop(version, None)
    if not bucket:
        del self._store[kid]
    return True

get_key async

get_key(kid, version=None, *, include_secret=False)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def get_key(
    self,
    kid: str,
    version: Optional[int] = None,
    *,
    include_secret: bool = False,
) -> KeyRef:
    bucket = self._store[kid]
    v = version or max(bucket)
    return bucket[v]

list_versions async

list_versions(kid)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def list_versions(self, kid: str) -> Tuple[int, ...]:
    bucket = self._store.get(kid)
    if not bucket:
        raise KeyError(f"Unknown kid: {kid}")
    return tuple(sorted(bucket.keys()))

get_public_jwk async

get_public_jwk(kid, version=None)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def get_public_jwk(self, kid: str, version: Optional[int] = None) -> dict:
    raise NotImplementedError("JWK export not supported")

jwks async

jwks(*, prefix_kids=None)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def jwks(self, *, prefix_kids: Optional[str] = None) -> dict:
    raise NotImplementedError("JWKS export not supported")

random_bytes async

random_bytes(n)

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def random_bytes(self, n: int) -> bytes:
    return secrets.token_bytes(n)

hkdf async

hkdf(ikm, *, salt, info, length)

Derive key material using HKDF-SHA256.

Source code in swarmauri_standard/key_providers/InMemoryKeyProvider.py

async def hkdf(self, ikm: bytes, *, salt: bytes, info: bytes, length: int) -> bytes:
    """Derive key material using HKDF-SHA256."""
    prk = hmac.new(salt, ikm, hashlib.sha256).digest()
    t = b""
    okm = b""
    counter = 1
    while len(okm) < length:
        t = hmac.new(prk, t + info + bytes([counter]), hashlib.sha256).digest()
        okm += t
        counter += 1
    return okm[:length]

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

get_key_by_ref async

get_key_by_ref(key_ref, *, include_secret=False)

Resolve simple URI-style key references into :class:KeyRef objects.

Subclasses must implement provider-specific resolution logic.

Source code in swarmauri_base/keys/KeyProviderBase.py

async def get_key_by_ref(
    self,
    key_ref: str,
    *,
    include_secret: bool = False,
) -> KeyRef:
    """Resolve simple URI-style key references into :class:`KeyRef` objects.

    Subclasses must implement provider-specific resolution logic.
    """

    raise NotImplementedError("get_key_by_ref must be implemented by subclasses")