13699279219

Committed 06 Mar 2025 01:00PM UTC coverage: 89.962% (-0.1%) from 90.074%

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Merge 2a28d2f23 into c4fafd9b0

Pull Request Pull Request #8981: feat: async support for the `HuggingFaceLocalChatGenerator`

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haystack/core/component/component.py

# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
#
# SPDX-License-Identifier: Apache-2.0

"""
Attributes:

    component: Marks a class as a component. Any class decorated with `@component` can be used by a Pipeline.

All components must follow the contract below. This docstring is the source of truth for components contract.

<hr>

`@component` decorator

All component classes must be decorated with the `@component` decorator. This allows Haystack to discover them.

<hr>

`__init__(self, **kwargs)`

Optional method.

Components may have an `__init__` method where they define:

- `self.init_parameters = {same parameters that the __init__ method received}`:
    In this dictionary you can store any state the components wish to be persisted when they are saved.
    These values will be given to the `__init__` method of a new instance when the pipeline is loaded.
    Note that by default the `@component` decorator saves the arguments automatically.
    However, if a component sets their own `init_parameters` manually in `__init__()`, that will be used instead.
    Note: all of the values contained here **must be JSON serializable**. Serialize them manually if needed.

Components should take only "basic" Python types as parameters of their `__init__` function, or iterables and
dictionaries containing only such values. Anything else (objects, functions, etc) will raise an exception at init
time. If there's the need for such values, consider serializing them to a string.

_(TODO explain how to use classes and functions in init. In the meantime see `test/components/test_accumulate.py`)_

The `__init__` must be extremely lightweight, because it's a frequent operation during the construction and
validation of the pipeline. If a component has some heavy state to initialize (models, backends, etc...) refer to
the `warm_up()` method.

<hr>

`warm_up(self)`

Optional method.

This method is called by Pipeline before the graph execution. Make sure to avoid double-initializations,
because Pipeline will not keep track of which components it called `warm_up()` on.

<hr>

`run(self, data)`

Mandatory method.

This is the method where the main functionality of the component should be carried out. It's called by
`Pipeline.run()`.

When the component should run, Pipeline will call this method with an instance of the dataclass returned by the
method decorated with `@component.input`. This dataclass contains:

- all the input values coming from other components connected to it,
- if any is missing, the corresponding value defined in `self.defaults`, if it exists.

`run()` must return a single instance of the dataclass declared through the method decorated with
`@component.output`.

"""

import inspect
from collections.abc import Callable
from contextlib import contextmanager
from contextvars import ContextVar
from copy import deepcopy
from dataclasses import dataclass
from types import new_class
from typing import Any, Dict, Optional, Protocol, Type, runtime_checkable

from haystack import logging
from haystack.core.errors import ComponentError

from .sockets import Sockets
from .types import InputSocket, OutputSocket, _empty

logger = logging.getLogger(__name__)


@dataclass
class PreInitHookPayload:
    """
    Payload for the hook called before a component instance is initialized.

    :param callback:
        Receives the following inputs: component class and init parameter keyword args.
    :param in_progress:
        Flag to indicate if the hook is currently being executed.
        Used to prevent it from being called recursively (if the component's constructor
        instantiates another component).
    """

    callback: Callable
    in_progress: bool = False


_COMPONENT_PRE_INIT_HOOK: ContextVar[Optional[PreInitHookPayload]] = ContextVar("component_pre_init_hook", default=None)


@contextmanager
def _hook_component_init(callback: Callable):
    """
    Context manager to set a callback that will be invoked before a component's constructor is called.

    The callback receives the component class and the init parameters (as keyword arguments) and can modify the init
    parameters in place.

    :param callback:
        Callback function to invoke.
    """
    token = _COMPONENT_PRE_INIT_HOOK.set(PreInitHookPayload(callback))
    try:
        yield
    finally:
        _COMPONENT_PRE_INIT_HOOK.reset(token)


@runtime_checkable
class Component(Protocol):
    """
    Note this is only used by type checking tools.

    In order to implement the `Component` protocol, custom components need to
    have a `run` method. The signature of the method and its return value
    won't be checked, i.e. classes with the following methods:

        def run(self, param: str) -> Dict[str, Any]:
            ...

    and

        def run(self, **kwargs):
            ...

    will be both considered as respecting the protocol. This makes the type
    checking much weaker, but we have other places where we ensure code is
    dealing with actual Components.

    The protocol is runtime checkable so it'll be possible to assert:

        isinstance(MyComponent, Component)
    """

    # This is the most reliable way to define the protocol for the `run` method.
    # Defining a method doesn't work as different Components will have different
    # arguments. Even defining here a method with `**kwargs` doesn't work as the
    # expected signature must be identical.
    # This makes most Language Servers and type checkers happy and shows less errors.
    run: Callable[..., Dict[str, Any]]


class ComponentMeta(type):
    @staticmethod
    def _positional_to_kwargs(cls_type, args) -> Dict[str, Any]:
        """
        Convert positional arguments to keyword arguments based on the signature of the `__init__` method.
        """
        init_signature = inspect.signature(cls_type.__init__)
        init_params = {name: info for name, info in init_signature.parameters.items() if name != "self"}

        out = {}
        for arg, (name, info) in zip(args, init_params.items()):
            if info.kind == inspect.Parameter.VAR_POSITIONAL:
                raise ComponentError(
                    "Pre-init hooks do not support components with variadic positional args in their init method"
                )

            assert info.kind in (inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.POSITIONAL_ONLY)
            out[name] = arg
        return out

    @staticmethod
    def _parse_and_set_output_sockets(instance: Any):
        has_async_run = hasattr(instance, "run_async")

        # If `component.set_output_types()` was called in the component constructor,
        # `__haystack_output__` is already populated, no need to do anything.
        if not hasattr(instance, "__haystack_output__"):
            # If that's not the case, we need to populate `__haystack_output__`
            #
            # If either of the run methods were decorated, they'll have a field assigned that
            # stores the output specification. If both run methods were decorated, we ensure that
            # outputs are the same. We deepcopy the content of the cache to transfer ownership from
            # the class method to the actual instance, so that different instances of the same class
            # won't share this data.

            run_output_types = getattr(instance.run, "_output_types_cache", {})
            async_run_output_types = getattr(instance.run_async, "_output_types_cache", {}) if has_async_run else {}

            if has_async_run and run_output_types != async_run_output_types:
                raise ComponentError("Output type specifications of 'run' and 'run_async' methods must be the same")
            output_types_cache = run_output_types

            instance.__haystack_output__ = Sockets(instance, deepcopy(output_types_cache), OutputSocket)

    @staticmethod
    def _parse_and_set_input_sockets(component_cls: Type, instance: Any):
        def inner(method, sockets):
            from inspect import Parameter

            run_signature = inspect.signature(method)

            for param_name, param_info in run_signature.parameters.items():
                if param_name == "self" or param_info.kind in (Parameter.VAR_POSITIONAL, Parameter.VAR_KEYWORD):
                    continue

                socket_kwargs = {"name": param_name, "type": param_info.annotation}
                if param_info.default != Parameter.empty:
                    socket_kwargs["default_value"] = param_info.default

                new_socket = InputSocket(**socket_kwargs)

                # Also ensure that new sockets don't override existing ones.
                existing_socket = sockets.get(param_name)
                if existing_socket is not None and existing_socket != new_socket:
                    raise ComponentError(
                        "set_input_types()/set_input_type() cannot override the parameters of the 'run' method"
                    )

                sockets[param_name] = new_socket

            return run_signature

        # Create the sockets if set_input_types() wasn't called in the constructor.
        if not hasattr(instance, "__haystack_input__"):
            instance.__haystack_input__ = Sockets(instance, {}, InputSocket)

        inner(getattr(component_cls, "run"), instance.__haystack_input__)

        # Ensure that the sockets are the same for the async method, if it exists.
        async_run = getattr(component_cls, "run_async", None)
        if async_run is not None:
            run_sockets = Sockets(instance, {}, InputSocket)
            async_run_sockets = Sockets(instance, {}, InputSocket)

            # Can't use the sockets from above as they might contain
            # values set with set_input_types().
            run_sig = inner(getattr(component_cls, "run"), run_sockets)
            async_run_sig = inner(async_run, async_run_sockets)

            if async_run_sockets != run_sockets or run_sig != async_run_sig:
                raise ComponentError("Parameters of 'run' and 'run_async' methods must be the same")

    def __call__(cls, *args, **kwargs):
        """
        This method is called when clients instantiate a Component and runs before __new__ and __init__.
        """
        # This will call __new__ then __init__, giving us back the Component instance
        pre_init_hook = _COMPONENT_PRE_INIT_HOOK.get()
        if pre_init_hook is None or pre_init_hook.in_progress:
            instance = super().__call__(*args, **kwargs)
        else:
            try:
                pre_init_hook.in_progress = True
                named_positional_args = ComponentMeta._positional_to_kwargs(cls, args)
                assert set(named_positional_args.keys()).intersection(kwargs.keys()) == set(), (
                    "positional and keyword arguments overlap"
                )
                kwargs.update(named_positional_args)
                pre_init_hook.callback(cls, kwargs)
                instance = super().__call__(**kwargs)
            finally:
                pre_init_hook.in_progress = False

        # Before returning, we have the chance to modify the newly created
        # Component instance, so we take the chance and set up the I/O sockets
        has_async_run = hasattr(instance, "run_async")
        if has_async_run and not inspect.iscoroutinefunction(instance.run_async):
            raise ComponentError(f"Method 'run_async' of component '{cls.__name__}' must be a coroutine")
        instance.__haystack_supports_async__ = has_async_run

        ComponentMeta._parse_and_set_input_sockets(cls, instance)
        ComponentMeta._parse_and_set_output_sockets(instance)

        # Since a Component can't be used in multiple Pipelines at the same time
        # we need to know if it's already owned by a Pipeline when adding it to one.
        # We use this flag to check that.
        instance.__haystack_added_to_pipeline__ = None

        return instance


def _component_repr(component: Component) -> str:
    """
    All Components override their __repr__ method with this one.

    It prints the component name and the input/output sockets.
    """
    result = object.__repr__(component)
    if pipeline := getattr(component, "__haystack_added_to_pipeline__", None):
        # This Component has been added in a Pipeline, let's get the name from there.
        result += f"\n{pipeline.get_component_name(component)}"

    # We're explicitly ignoring the type here because we're sure that the component
    # has the __haystack_input__ and __haystack_output__ attributes at this point
    return (
        f"{result}\n{getattr(component, '__haystack_input__', '<invalid_input_sockets>')}"
        f"\n{getattr(component, '__haystack_output__', '<invalid_output_sockets>')}"
    )


def _component_run_has_kwargs(component_cls: Type) -> bool:
    run_method = getattr(component_cls, "run", None)
    if run_method is None:
        return False
    else:
        return any(
            param.kind == inspect.Parameter.VAR_KEYWORD for param in inspect.signature(run_method).parameters.values()
        )


class _Component:
    """
    See module's docstring.

    Args:
        cls: the class that should be used as a component.

    Returns:
        A class that can be recognized as a component.

    Raises:
        ComponentError: if the class provided has no `run()` method or otherwise doesn't respect the component contract.
    """

    def __init__(self):
        self.registry = {}

    def set_input_type(
        self,
        instance,
        name: str,
        type: Any,  # noqa: A002
        default: Any = _empty,
    ):
        """
        Add a single input socket to the component instance.

        Replaces any existing input socket with the same name.

        :param instance: Component instance where the input type will be added.
        :param name: name of the input socket.
        :param type: type of the input socket.
        :param default: default value of the input socket, defaults to _empty
        """
        if not _component_run_has_kwargs(instance.__class__):
            raise ComponentError(
                "Cannot set input types on a component that doesn't have a kwargs parameter in the 'run' method"
            )

        if not hasattr(instance, "__haystack_input__"):
            instance.__haystack_input__ = Sockets(instance, {}, InputSocket)
        instance.__haystack_input__[name] = InputSocket(name=name, type=type, default_value=default)

    def set_input_types(self, instance, **types):
        """
        Method that specifies the input types when 'kwargs' is passed to the run method.

        Use as:

        ```python
        @component
        class MyComponent:

            def __init__(self, value: int):
                component.set_input_types(self, value_1=str, value_2=str)
                ...

            @component.output_types(output_1=int, output_2=str)
            def run(self, **kwargs):
                return {"output_1": kwargs["value_1"], "output_2": ""}
        ```

        Note that if the `run()` method also specifies some parameters, those will take precedence.

        For example:

        ```python
        @component
        class MyComponent:

            def __init__(self, value: int):
                component.set_input_types(self, value_1=str, value_2=str)
                ...

            @component.output_types(output_1=int, output_2=str)
            def run(self, value_0: str, value_1: Optional[str] = None, **kwargs):
                return {"output_1": kwargs["value_1"], "output_2": ""}
        ```

        would add a mandatory `value_0` parameters, make the `value_1`
        parameter optional with a default None, and keep the `value_2`
        parameter mandatory as specified in `set_input_types`.

        """
        if not _component_run_has_kwargs(instance.__class__):
            raise ComponentError(
                "Cannot set input types on a component that doesn't have a kwargs parameter in the 'run' method"
            )

        instance.__haystack_input__ = Sockets(
            instance, {name: InputSocket(name=name, type=type_) for name, type_ in types.items()}, InputSocket
        )

    def set_output_types(self, instance, **types):
        """
        Method that specifies the output types when the 'run' method is not decorated with 'component.output_types'.

        Use as:

        ```python
        @component
        class MyComponent:

            def __init__(self, value: int):
                component.set_output_types(self, output_1=int, output_2=str)
                ...

            # no decorators here
            def run(self, value: int):
                return {"output_1": 1, "output_2": "2"}
        ```
        """
        has_decorator = hasattr(instance.run, "_output_types_cache")
        if has_decorator:
            raise ComponentError(
                "Cannot call `set_output_types` on a component that already has "
                "the 'output_types' decorator on its `run` method"
            )

        instance.__haystack_output__ = Sockets(
            instance, {name: OutputSocket(name=name, type=type_) for name, type_ in types.items()}, OutputSocket
        )

    def output_types(self, **types):
        """
        Decorator factory that specifies the output types of a component.

        Use as:

        ```python
        @component
        class MyComponent:
            @component.output_types(output_1=int, output_2=str)
            def run(self, value: int):
                return {"output_1": 1, "output_2": "2"}
        ```
        """

        def output_types_decorator(run_method):
            """
            Decorator that sets the output types of the decorated method.

            This happens at class creation time, and since we don't have the decorated
            class available here, we temporarily store the output types as an attribute of
            the decorated method. The ComponentMeta metaclass will use this data to create
            sockets at instance creation time.
            """
            method_name = run_method.__name__
            if method_name not in ("run", "run_async"):
                raise ComponentError("'output_types' decorator can only be used on 'run' and 'run_async' methods")

            setattr(
                run_method,
                "_output_types_cache",
                {name: OutputSocket(name=name, type=type_) for name, type_ in types.items()},
            )
            return run_method

        return output_types_decorator

    def _component(self, cls: Any):
        """
        Decorator validating the structure of the component and registering it in the components registry.
        """
        logger.debug("Registering {component} as a component", component=cls)

        # Check for required methods and fail as soon as possible
        if not hasattr(cls, "run"):
            raise ComponentError(f"{cls.__name__} must have a 'run()' method. See the docs for more information.")

        def copy_class_namespace(namespace):
            """
            This is the callback that `typing.new_class` will use to populate the newly created class.

            Simply copy the whole namespace from the decorated class.
            """
            for key, val in dict(cls.__dict__).items():
                # __dict__ and __weakref__ are class-bound, we should let Python recreate them.
                if key in ("__dict__", "__weakref__"):
                    continue
                namespace[key] = val

        # Recreate the decorated component class so it uses our metaclass.
        # We must explicitly redefine the type of the class to make sure language servers
        # and type checkers understand that the class is of the correct type.
        # mypy doesn't like that we do this though so we explicitly ignore the type check.
        new_cls: cls.__name__ = new_class(
            cls.__name__, cls.__bases__, {"metaclass": ComponentMeta}, copy_class_namespace
        )  # type: ignore[no-redef]

        # Save the component in the class registry (for deserialization)
        class_path = f"{new_cls.__module__}.{new_cls.__name__}"
        if class_path in self.registry:
            # Corner case, but it may occur easily in notebooks when re-running cells.
            logger.debug(
                "Component {component} is already registered. Previous imported from '{module_name}', \
                new imported from '{new_module_name}'",
                component=class_path,
                module_name=self.registry[class_path],
                new_module_name=new_cls,
            )
        self.registry[class_path] = new_cls
        logger.debug("Registered Component {component}", component=new_cls)

        # Override the __repr__ method with a default one
        new_cls.__repr__ = _component_repr

        return new_cls

    def __call__(self, cls: Optional[type] = None):
        # We must wrap the call to the decorator in a function for it to work
        # correctly with or without parens
        def wrap(cls):
            return self._component(cls)

        if cls:
            # Decorator is called without parens
            return wrap(cls)

        # Decorator is called with parens
        return wrap


component = _Component()

1	# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
2	#
3	# SPDX-License-Identifier: Apache-2.0
4
5	"""
6	Attributes:
7
8	component: Marks a class as a component. Any class decorated with `@component` can be used by a Pipeline.
9
10	All components must follow the contract below. This docstring is the source of truth for components contract.
11
12	<hr>
13
14	`@component` decorator
15
16	All component classes must be decorated with the `@component` decorator. This allows Haystack to discover them.
17
18	<hr>
19
20	`__init__(self, **kwargs)`
21
22	Optional method.
23
24	Components may have an `__init__` method where they define:
25
26	- `self.init_parameters = {same parameters that the __init__ method received}`:
27	In this dictionary you can store any state the components wish to be persisted when they are saved.
28	These values will be given to the `__init__` method of a new instance when the pipeline is loaded.
29	Note that by default the `@component` decorator saves the arguments automatically.
30	However, if a component sets their own `init_parameters` manually in `__init__()`, that will be used instead.
31	Note: all of the values contained here must be JSON serializable. Serialize them manually if needed.
32
33	Components should take only "basic" Python types as parameters of their `__init__` function, or iterables and
34	dictionaries containing only such values. Anything else (objects, functions, etc) will raise an exception at init
35	time. If there's the need for such values, consider serializing them to a string.
36
37	_(TODO explain how to use classes and functions in init. In the meantime see `test/components/test_accumulate.py`)_
38
39	The `__init__` must be extremely lightweight, because it's a frequent operation during the construction and
40	validation of the pipeline. If a component has some heavy state to initialize (models, backends, etc...) refer to
41	the `warm_up()` method.
42
43	<hr>
44
45	`warm_up(self)`
46
47	Optional method.
48
49	This method is called by Pipeline before the graph execution. Make sure to avoid double-initializations,
50	because Pipeline will not keep track of which components it called `warm_up()` on.
51
52	<hr>
53
54	`run(self, data)`
55
56	Mandatory method.
57
58	This is the method where the main functionality of the component should be carried out. It's called by
59	`Pipeline.run()`.
60
61	When the component should run, Pipeline will call this method with an instance of the dataclass returned by the
62	method decorated with `@component.input`. This dataclass contains:
63
64	- all the input values coming from other components connected to it,
65	- if any is missing, the corresponding value defined in `self.defaults`, if it exists.
66
67	`run()` must return a single instance of the dataclass declared through the method decorated with
68	`@component.output`.
69
70	"""
71
72	import inspect	1✔
73	from collections.abc import Callable	1✔
74	from contextlib import contextmanager	1✔
75	from contextvars import ContextVar	1✔
76	from copy import deepcopy	1✔
77	from dataclasses import dataclass	1✔
78	from types import new_class	1✔
79	from typing import Any, Dict, Optional, Protocol, Type, runtime_checkable	1✔
80
81	from haystack import logging	1✔
82	from haystack.core.errors import ComponentError	1✔
83
84	from .sockets import Sockets	1✔
85	from .types import InputSocket, OutputSocket, _empty	1✔
86
87	logger = logging.getLogger(__name__)	1✔
88
89
90	@dataclass	1✔
91	class PreInitHookPayload:	1✔
92	"""
93	Payload for the hook called before a component instance is initialized.
94
95	:param callback:
96	Receives the following inputs: component class and init parameter keyword args.
97	:param in_progress:
98	Flag to indicate if the hook is currently being executed.
99	Used to prevent it from being called recursively (if the component's constructor
100	instantiates another component).
101	"""
102
103	callback: Callable	1✔
104	in_progress: bool = False	1✔
105
106
107	_COMPONENT_PRE_INIT_HOOK: ContextVar[Optional[PreInitHookPayload]] = ContextVar("component_pre_init_hook", default=None)	1✔
108
109
110	@contextmanager	1✔
111	def _hook_component_init(callback: Callable):	1✔
112	"""
113	Context manager to set a callback that will be invoked before a component's constructor is called.
114
115	The callback receives the component class and the init parameters (as keyword arguments) and can modify the init
116	parameters in place.
117
118	:param callback:
119	Callback function to invoke.
120	"""
121	token = _COMPONENT_PRE_INIT_HOOK.set(PreInitHookPayload(callback))	1✔
122	try:	1✔
123	yield	1✔
124	finally:
125	_COMPONENT_PRE_INIT_HOOK.reset(token)	1✔
126
127
128	@runtime_checkable	1✔
129	class Component(Protocol):	1✔
130	"""
131	Note this is only used by type checking tools.
132
133	In order to implement the `Component` protocol, custom components need to
134	have a `run` method. The signature of the method and its return value
135	won't be checked, i.e. classes with the following methods:
136
137	def run(self, param: str) -> Dict[str, Any]:
138	...
139
140	and
141
142	def run(self, **kwargs):
143	...
144
145	will be both considered as respecting the protocol. This makes the type
146	checking much weaker, but we have other places where we ensure code is
147	dealing with actual Components.
148
149	The protocol is runtime checkable so it'll be possible to assert:
150
151	isinstance(MyComponent, Component)
152	"""
153
154	# This is the most reliable way to define the protocol for the `run` method.
155	# Defining a method doesn't work as different Components will have different
156	# arguments. Even defining here a method with `**kwargs` doesn't work as the
157	# expected signature must be identical.
158	# This makes most Language Servers and type checkers happy and shows less errors.
159	run: Callable[..., Dict[str, Any]]	1✔
160
161
162	class ComponentMeta(type):	1✔
163	@staticmethod	1✔
164	def _positional_to_kwargs(cls_type, args) -> Dict[str, Any]:	1✔
165	"""
166	Convert positional arguments to keyword arguments based on the signature of the `__init__` method.
167	"""
168	init_signature = inspect.signature(cls_type.__init__)	1✔
169	init_params = {name: info for name, info in init_signature.parameters.items() if name != "self"}	1✔
170
171	out = {}	1✔
172	for arg, (name, info) in zip(args, init_params.items()):	1✔
173	if info.kind == inspect.Parameter.VAR_POSITIONAL:	1✔
174	raise ComponentError(	1✔
175	"Pre-init hooks do not support components with variadic positional args in their init method"
176	)
177
178	assert info.kind in (inspect.Parameter.POSITIONAL_OR_KEYWORD, inspect.Parameter.POSITIONAL_ONLY)	1✔
179	out[name] = arg	1✔
180	return out	1✔
181
182	@staticmethod	1✔
183	def _parse_and_set_output_sockets(instance: Any):	1✔
184	has_async_run = hasattr(instance, "run_async")	1✔
185
186	# If `component.set_output_types()` was called in the component constructor,
187	# `__haystack_output__` is already populated, no need to do anything.
188	if not hasattr(instance, "__haystack_output__"):	1✔
189	# If that's not the case, we need to populate `__haystack_output__`
190	#
191	# If either of the run methods were decorated, they'll have a field assigned that
192	# stores the output specification. If both run methods were decorated, we ensure that
193	# outputs are the same. We deepcopy the content of the cache to transfer ownership from
194	# the class method to the actual instance, so that different instances of the same class
195	# won't share this data.
196
197	run_output_types = getattr(instance.run, "_output_types_cache", {})	1✔
198	async_run_output_types = getattr(instance.run_async, "_output_types_cache", {}) if has_async_run else {}	1✔
199
200	if has_async_run and run_output_types != async_run_output_types:	1✔
201	raise ComponentError("Output type specifications of 'run' and 'run_async' methods must be the same")	1✔
202	output_types_cache = run_output_types	1✔
203
204	instance.__haystack_output__ = Sockets(instance, deepcopy(output_types_cache), OutputSocket)	1✔
205
206	@staticmethod	1✔
207	def _parse_and_set_input_sockets(component_cls: Type, instance: Any):	1✔
208	def inner(method, sockets):	1✔
209	from inspect import Parameter	1✔
210
211	run_signature = inspect.signature(method)	1✔
212
213	for param_name, param_info in run_signature.parameters.items():	1✔
214	if param_name == "self" or param_info.kind in (Parameter.VAR_POSITIONAL, Parameter.VAR_KEYWORD):	1✔
215	continue	1✔
216
217	socket_kwargs = {"name": param_name, "type": param_info.annotation}	1✔
218	if param_info.default != Parameter.empty:	1✔
219	socket_kwargs["default_value"] = param_info.default	1✔
220
221	new_socket = InputSocket(**socket_kwargs)	1✔
222
223	# Also ensure that new sockets don't override existing ones.
224	existing_socket = sockets.get(param_name)	1✔
225	if existing_socket is not None and existing_socket != new_socket:	1✔
226	raise ComponentError(	1✔
227	"set_input_types()/set_input_type() cannot override the parameters of the 'run' method"
228	)
229
230	sockets[param_name] = new_socket	1✔
231
232	return run_signature	1✔
233
234	# Create the sockets if set_input_types() wasn't called in the constructor.
235	if not hasattr(instance, "__haystack_input__"):	1✔
236	instance.__haystack_input__ = Sockets(instance, {}, InputSocket)	1✔
237
238	inner(getattr(component_cls, "run"), instance.__haystack_input__)	1✔
239
240	# Ensure that the sockets are the same for the async method, if it exists.
241	async_run = getattr(component_cls, "run_async", None)	1✔
242	if async_run is not None:	1✔
243	run_sockets = Sockets(instance, {}, InputSocket)	1✔
244	async_run_sockets = Sockets(instance, {}, InputSocket)	1✔
245
246	# Can't use the sockets from above as they might contain
247	# values set with set_input_types().
248	run_sig = inner(getattr(component_cls, "run"), run_sockets)	1✔
249	async_run_sig = inner(async_run, async_run_sockets)	1✔
250
251	if async_run_sockets != run_sockets or run_sig != async_run_sig:	1✔
252	raise ComponentError("Parameters of 'run' and 'run_async' methods must be the same")	1✔
253
254	def __call__(cls, args, *kwargs):	1✔
255	"""
256	This method is called when clients instantiate a Component and runs before __new__ and __init__.
257	"""
258	# This will call __new__ then __init__, giving us back the Component instance
259	pre_init_hook = _COMPONENT_PRE_INIT_HOOK.get()	1✔
260	if pre_init_hook is None or pre_init_hook.in_progress:	1✔
261	instance = super().__call__(args, *kwargs)	1✔
262	else:
263	try:	1✔
264	pre_init_hook.in_progress = True	1✔
265	named_positional_args = ComponentMeta._positional_to_kwargs(cls, args)	1✔
266	assert set(named_positional_args.keys()).intersection(kwargs.keys()) == set(), (	1✔
267	"positional and keyword arguments overlap"
268	)
269	kwargs.update(named_positional_args)	1✔
270	pre_init_hook.callback(cls, kwargs)	1✔
271	instance = super().__call__(**kwargs)	1✔
272	finally:
273	pre_init_hook.in_progress = False	1✔
274
275	# Before returning, we have the chance to modify the newly created
276	# Component instance, so we take the chance and set up the I/O sockets
277	has_async_run = hasattr(instance, "run_async")	1✔
278	if has_async_run and not inspect.iscoroutinefunction(instance.run_async):	1✔
279	raise ComponentError(f"Method 'run_async' of component '{cls.__name__}' must be a coroutine")	1✔
280	instance.__haystack_supports_async__ = has_async_run	1✔
281
282	ComponentMeta._parse_and_set_input_sockets(cls, instance)	1✔
283	ComponentMeta._parse_and_set_output_sockets(instance)	1✔
284
285	# Since a Component can't be used in multiple Pipelines at the same time
286	# we need to know if it's already owned by a Pipeline when adding it to one.
287	# We use this flag to check that.
288	instance.__haystack_added_to_pipeline__ = None	1✔
289
290	return instance	1✔
291
292
293	def _component_repr(component: Component) -> str:	1✔
294	"""
295	All Components override their __repr__ method with this one.
296
297	It prints the component name and the input/output sockets.
298	"""
299	result = object.__repr__(component)	1✔
300	if pipeline := getattr(component, "__haystack_added_to_pipeline__", None):	1✔
301	# This Component has been added in a Pipeline, let's get the name from there.
302	result += f"\n{pipeline.get_component_name(component)}"	1✔
303
304	# We're explicitly ignoring the type here because we're sure that the component
305	# has the __haystack_input__ and __haystack_output__ attributes at this point
306	return (	1✔
307	f"{result}\n{getattr(component, '__haystack_input__', '<invalid_input_sockets>')}"
308	f"\n{getattr(component, '__haystack_output__', '<invalid_output_sockets>')}"
309	)
310
311
312	def _component_run_has_kwargs(component_cls: Type) -> bool:	1✔
313	run_method = getattr(component_cls, "run", None)	1✔
314	if run_method is None:	1✔
315	return False	×
316	else:
317	return any(	1✔
318	param.kind == inspect.Parameter.VAR_KEYWORD for param in inspect.signature(run_method).parameters.values()
319	)
320
321
322	class _Component:	1✔
323	"""
324	See module's docstring.
325
326	Args:
327	cls: the class that should be used as a component.
328
329	Returns:
330	A class that can be recognized as a component.
331
332	Raises:
333	ComponentError: if the class provided has no `run()` method or otherwise doesn't respect the component contract.
334	"""
335
336	def __init__(self):	1✔
337	self.registry = {}	1✔
338
339	def set_input_type(	1✔
340	self,
341	instance,
342	name: str,
343	type: Any, # noqa: A002
344	default: Any = _empty,
345	):
346	"""
347	Add a single input socket to the component instance.
348
349	Replaces any existing input socket with the same name.
350
351	:param instance: Component instance where the input type will be added.
352	:param name: name of the input socket.
353	:param type: type of the input socket.
354	:param default: default value of the input socket, defaults to _empty
355	"""
356	if not _component_run_has_kwargs(instance.__class__):	1✔
357	raise ComponentError(	1✔
358	"Cannot set input types on a component that doesn't have a kwargs parameter in the 'run' method"
359	)
360
361	if not hasattr(instance, "__haystack_input__"):	1✔
362	instance.__haystack_input__ = Sockets(instance, {}, InputSocket)	1✔
363	instance.__haystack_input__[name] = InputSocket(name=name, type=type, default_value=default)	1✔
364
365	def set_input_types(self, instance, **types):	1✔
366	"""
367	Method that specifies the input types when 'kwargs' is passed to the run method.
368
369	Use as:
370
371	```python
372	@component
373	class MyComponent:
374
375	def __init__(self, value: int):
376	component.set_input_types(self, value_1=str, value_2=str)
377	...
378
379	@component.output_types(output_1=int, output_2=str)
380	def run(self, **kwargs):
381	return {"output_1": kwargs["value_1"], "output_2": ""}
382	```
383
384	Note that if the `run()` method also specifies some parameters, those will take precedence.
385
386	For example:
387
388	```python
389	@component
390	class MyComponent:
391
392	def __init__(self, value: int):
393	component.set_input_types(self, value_1=str, value_2=str)
394	...
395
396	@component.output_types(output_1=int, output_2=str)
397	def run(self, value_0: str, value_1: Optional[str] = None, **kwargs):
398	return {"output_1": kwargs["value_1"], "output_2": ""}
399	```
400
401	would add a mandatory `value_0` parameters, make the `value_1`
402	parameter optional with a default None, and keep the `value_2`
403	parameter mandatory as specified in `set_input_types`.
404
405	"""
406	if not _component_run_has_kwargs(instance.__class__):	1✔
407	raise ComponentError(	1✔
408	"Cannot set input types on a component that doesn't have a kwargs parameter in the 'run' method"
409	)
410
411	instance.__haystack_input__ = Sockets(	1✔
412	instance, {name: InputSocket(name=name, type=type_) for name, type_ in types.items()}, InputSocket
413	)
414
415	def set_output_types(self, instance, **types):	1✔
416	"""
417	Method that specifies the output types when the 'run' method is not decorated with 'component.output_types'.
418
419	Use as:
420
421	```python
422	@component
423	class MyComponent:
424
425	def __init__(self, value: int):
426	component.set_output_types(self, output_1=int, output_2=str)
427	...
428
429	# no decorators here
430	def run(self, value: int):
431	return {"output_1": 1, "output_2": "2"}
432	```
433	"""
434	has_decorator = hasattr(instance.run, "_output_types_cache")	1✔
435	if has_decorator:	1✔
436	raise ComponentError(	1✔
437	"Cannot call `set_output_types` on a component that already has "
438	"the 'output_types' decorator on its `run` method"
439	)
440
441	instance.__haystack_output__ = Sockets(	1✔
442	instance, {name: OutputSocket(name=name, type=type_) for name, type_ in types.items()}, OutputSocket
443	)
444
445	def output_types(self, **types):	1✔
446	"""
447	Decorator factory that specifies the output types of a component.
448
449	Use as:
450
451	```python
452	@component
453	class MyComponent:
454	@component.output_types(output_1=int, output_2=str)
455	def run(self, value: int):
456	return {"output_1": 1, "output_2": "2"}
457	```
458	"""
459
460	def output_types_decorator(run_method):	1✔
461	"""
462	Decorator that sets the output types of the decorated method.
463
464	This happens at class creation time, and since we don't have the decorated
465	class available here, we temporarily store the output types as an attribute of
466	the decorated method. The ComponentMeta metaclass will use this data to create
467	sockets at instance creation time.
468	"""
469	method_name = run_method.__name__	1✔
470	if method_name not in ("run", "run_async"):	1✔
471	raise ComponentError("'output_types' decorator can only be used on 'run' and 'run_async' methods")	1✔
472
473	setattr(	1✔
474	run_method,
475	"_output_types_cache",
476	{name: OutputSocket(name=name, type=type_) for name, type_ in types.items()},
477	)
478	return run_method	1✔
479
480	return output_types_decorator	1✔
481
482	def _component(self, cls: Any):	1✔
483	"""
484	Decorator validating the structure of the component and registering it in the components registry.
485	"""
486	logger.debug("Registering {component} as a component", component=cls)	1✔
487
488	# Check for required methods and fail as soon as possible
489	if not hasattr(cls, "run"):	1✔
490	raise ComponentError(f"{cls.__name__} must have a 'run()' method. See the docs for more information.")	1✔
491
492	def copy_class_namespace(namespace):	1✔
493	"""
494	This is the callback that `typing.new_class` will use to populate the newly created class.
495
496	Simply copy the whole namespace from the decorated class.
497	"""
498	for key, val in dict(cls.__dict__).items():	1✔
499	# __dict__ and __weakref__ are class-bound, we should let Python recreate them.
500	if key in ("__dict__", "__weakref__"):	1✔
501	continue	1✔
502	namespace[key] = val	1✔
503
504	# Recreate the decorated component class so it uses our metaclass.
505	# We must explicitly redefine the type of the class to make sure language servers
506	# and type checkers understand that the class is of the correct type.
507	# mypy doesn't like that we do this though so we explicitly ignore the type check.
508	new_cls: cls.__name__ = new_class(	1✔
509	cls.__name__, cls.__bases__, {"metaclass": ComponentMeta}, copy_class_namespace
510	) # type: ignore[no-redef]
511
512	# Save the component in the class registry (for deserialization)
513	class_path = f"{new_cls.__module__}.{new_cls.__name__}"	1✔
514	if class_path in self.registry:	1✔
515	# Corner case, but it may occur easily in notebooks when re-running cells.
516	logger.debug(	1✔
517	"Component {component} is already registered. Previous imported from '{module_name}', \
518	new imported from '{new_module_name}'",
519	component=class_path,
520	module_name=self.registry[class_path],
521	new_module_name=new_cls,
522	)
523	self.registry[class_path] = new_cls	1✔
524	logger.debug("Registered Component {component}", component=new_cls)	1✔
525
526	# Override the __repr__ method with a default one
527	new_cls.__repr__ = _component_repr	1✔
528
529	return new_cls	1✔
530
531	def __call__(self, cls: Optional[type] = None):	1✔
532	# We must wrap the call to the decorator in a function for it to work
533	# correctly with or without parens
534	def wrap(cls):	1✔
535	return self._component(cls)	1✔
536
537	if cls:	1✔
538	# Decorator is called without parens
539	return wrap(cls)	1✔
540
541	# Decorator is called with parens
542	return wrap	1✔
543
544
545	component = _Component()	1✔

deepset-ai / haystack / 13699279219

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