Index

Pipeline schema.

InputKeys

Bases: BaseModel

Input keys.

Parameters:

Name	Type	Description	Default
required_keys	Set[str]		set()
optional_keys	Set[str]		set()

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class InputKeys(BaseModel):
    """Input keys."""

    required_keys: Set[str] = Field(default_factory=set)
    optional_keys: Set[str] = Field(default_factory=set)

    @classmethod
    def from_keys(
        cls, required_keys: Set[str], optional_keys: Optional[Set[str]] = None
    ) -> "InputKeys":
        """Create InputKeys from tuple."""
        return cls(required_keys=required_keys, optional_keys=optional_keys or set())

    def validate_keys(self, input_keys: Set[str]) -> None:
        """Validate input keys."""
        # check if required keys are present, and that keys all are in required or optional
        if not self.required_keys.issubset(input_keys):
            raise ValueError(
                f"Required keys {self.required_keys} are not present in input keys {input_keys}"
            )
        if not input_keys.issubset(self.required_keys.union(self.optional_keys)):
            raise ValueError(
                f"Input keys {input_keys} contain keys not in required or optional keys {self.required_keys.union(self.optional_keys)}"
            )

    def __len__(self) -> int:
        """Length of input keys."""
        return len(self.required_keys) + len(self.optional_keys)

    def all(self) -> Set[str]:
        """Get all input keys."""
        return self.required_keys.union(self.optional_keys)

from_keys classmethod

from_keys(required_keys: Set[str], optional_keys: Optional[Set[str]] = None) -> InputKeys

Create InputKeys from tuple.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

@classmethod
def from_keys(
    cls, required_keys: Set[str], optional_keys: Optional[Set[str]] = None
) -> "InputKeys":
    """Create InputKeys from tuple."""
    return cls(required_keys=required_keys, optional_keys=optional_keys or set())

validate_keys

validate_keys(input_keys: Set[str]) -> None

Validate input keys.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def validate_keys(self, input_keys: Set[str]) -> None:
    """Validate input keys."""
    # check if required keys are present, and that keys all are in required or optional
    if not self.required_keys.issubset(input_keys):
        raise ValueError(
            f"Required keys {self.required_keys} are not present in input keys {input_keys}"
        )
    if not input_keys.issubset(self.required_keys.union(self.optional_keys)):
        raise ValueError(
            f"Input keys {input_keys} contain keys not in required or optional keys {self.required_keys.union(self.optional_keys)}"
        )

all

all() -> Set[str]

Get all input keys.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def all(self) -> Set[str]:
    """Get all input keys."""
    return self.required_keys.union(self.optional_keys)

OutputKeys

Bases: BaseModel

Output keys.

Parameters:

Name	Type	Description	Default
required_keys	Set[str]		set()

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class OutputKeys(BaseModel):
    """Output keys."""

    required_keys: Set[str] = Field(default_factory=set)

    @classmethod
    def from_keys(
        cls,
        required_keys: Set[str],
    ) -> "OutputKeys":
        """Create OutputKeys from tuple."""
        return cls(required_keys=required_keys)

    def validate_keys(self, input_keys: Set[str]) -> None:
        """Validate input keys."""
        # validate that input keys exactly match required keys
        if input_keys != self.required_keys:
            raise ValueError(
                f"Input keys {input_keys} do not match required keys {self.required_keys}"
            )

from_keys classmethod

from_keys(required_keys: Set[str]) -> OutputKeys

Create OutputKeys from tuple.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

@classmethod
def from_keys(
    cls,
    required_keys: Set[str],
) -> "OutputKeys":
    """Create OutputKeys from tuple."""
    return cls(required_keys=required_keys)

validate_keys

validate_keys(input_keys: Set[str]) -> None

Validate input keys.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def validate_keys(self, input_keys: Set[str]) -> None:
    """Validate input keys."""
    # validate that input keys exactly match required keys
    if input_keys != self.required_keys:
        raise ValueError(
            f"Input keys {input_keys} do not match required keys {self.required_keys}"
        )

ChainableMixin

Bases: ABC

Chainable mixin.

A module that can produce a QueryComponent from a set of inputs through as_query_component.

If plugged in directly into a QueryPipeline, the ChainableMixin will be converted into a QueryComponent with default parameters.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class ChainableMixin(ABC):
    """Chainable mixin.

    A module that can produce a `QueryComponent` from a set of inputs through
    `as_query_component`.

    If plugged in directly into a `QueryPipeline`, the `ChainableMixin` will be
    converted into a `QueryComponent` with default parameters.

    """

    @abstractmethod
    def _as_query_component(self, **kwargs: Any) -> "QueryComponent":
        """Get query component."""

    def as_query_component(
        self, partial: Optional[Dict[str, Any]] = None, **kwargs: Any
    ) -> "QueryComponent":
        """Get query component."""
        component = self._as_query_component(**kwargs)
        component.partial(**(partial or {}))
        return component

as_query_component

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) -> QueryComponent

Get query component.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def as_query_component(
    self, partial: Optional[Dict[str, Any]] = None, **kwargs: Any
) -> "QueryComponent":
    """Get query component."""
    component = self._as_query_component(**kwargs)
    component.partial(**(partial or {}))
    return component

QueryComponent

Bases: BaseModel

Query component.

Represents a component that can be run in a QueryPipeline.

Parameters:

Name	Type	Description	Default
partial_dict	Dict[str, Any]	Partial arguments to run_component	{}

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class QueryComponent(BaseModel):
    """Query component.

    Represents a component that can be run in a `QueryPipeline`.

    """

    partial_dict: Dict[str, Any] = Field(
        default_factory=dict, description="Partial arguments to run_component"
    )

    # TODO: make this a subclass of BaseComponent (e.g. use Pydantic)

    def partial(self, **kwargs: Any) -> None:
        """Update with partial arguments."""
        self.partial_dict.update(kwargs)

    @abstractmethod
    def set_callback_manager(self, callback_manager: CallbackManager) -> None:
        """Set callback manager."""
        # TODO: refactor so that callback_manager is always passed in during runtime.

    @property
    def free_req_input_keys(self) -> Set[str]:
        """Get free input keys."""
        return self.input_keys.required_keys.difference(self.partial_dict.keys())

    @abstractmethod
    def _validate_component_inputs(self, input: Dict[str, Any]) -> Dict[str, Any]:
        """Validate component inputs during run_component."""

    def _validate_component_outputs(self, output: Dict[str, Any]) -> Dict[str, Any]:
        """Validate component outputs during run_component."""
        # override if needed
        return output

    def validate_component_inputs(self, input: Dict[str, Any]) -> Dict[str, Any]:
        """Validate component inputs."""
        # make sure set of input keys == self.input_keys
        self.input_keys.validate_keys(set(input.keys()))
        return self._validate_component_inputs(input)

    def validate_component_outputs(self, output: Dict[str, Any]) -> Dict[str, Any]:
        """Validate component outputs."""
        # make sure set of output keys == self.output_keys
        self.output_keys.validate_keys(set(output.keys()))
        return self._validate_component_outputs(output)

    def run_component(self, **kwargs: Any) -> Dict[str, Any]:
        """Run component."""
        kwargs.update(self.partial_dict)
        kwargs = self.validate_component_inputs(kwargs)
        component_outputs = self._run_component(**kwargs)
        return self.validate_component_outputs(component_outputs)

    async def arun_component(self, **kwargs: Any) -> Dict[str, Any]:
        """Run component."""
        kwargs.update(self.partial_dict)
        kwargs = self.validate_component_inputs(kwargs)
        component_outputs = await self._arun_component(**kwargs)
        return self.validate_component_outputs(component_outputs)

    @abstractmethod
    def _run_component(self, **kwargs: Any) -> Dict:
        """Run component."""

    @abstractmethod
    async def _arun_component(self, **kwargs: Any) -> Any:
        """Run component (async)."""

    @property
    @abstractmethod
    def input_keys(self) -> InputKeys:
        """Input keys."""

    @property
    @abstractmethod
    def output_keys(self) -> OutputKeys:
        """Output keys."""

    @property
    def sub_query_components(self) -> List["QueryComponent"]:
        """Get sub query components.

        Certain query components may have sub query components, e.g. a
        query pipeline will have sub query components, and so will
        an IfElseComponent.

        """
        return []

free_req_input_keys property

free_req_input_keys: Set[str]

Get free input keys.

input_keys abstractmethod property

input_keys: InputKeys

Input keys.

output_keys abstractmethod property

output_keys: OutputKeys

Output keys.

sub_query_components property

sub_query_components: List[QueryComponent]

Get sub query components.

Certain query components may have sub query components, e.g. a query pipeline will have sub query components, and so will an IfElseComponent.

partial

partial(**kwargs: Any) -> None

Update with partial arguments.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def partial(self, **kwargs: Any) -> None:
    """Update with partial arguments."""
    self.partial_dict.update(kwargs)

set_callback_manager abstractmethod

set_callback_manager(callback_manager: CallbackManager) -> None

Set callback manager.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

@abstractmethod
def set_callback_manager(self, callback_manager: CallbackManager) -> None:
    """Set callback manager."""

validate_component_inputs

validate_component_inputs(input: Dict[str, Any]) -> Dict[str, Any]

Validate component inputs.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def validate_component_inputs(self, input: Dict[str, Any]) -> Dict[str, Any]:
    """Validate component inputs."""
    # make sure set of input keys == self.input_keys
    self.input_keys.validate_keys(set(input.keys()))
    return self._validate_component_inputs(input)

validate_component_outputs

validate_component_outputs(output: Dict[str, Any]) -> Dict[str, Any]

Validate component outputs.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def validate_component_outputs(self, output: Dict[str, Any]) -> Dict[str, Any]:
    """Validate component outputs."""
    # make sure set of output keys == self.output_keys
    self.output_keys.validate_keys(set(output.keys()))
    return self._validate_component_outputs(output)

run_component

run_component(**kwargs: Any) -> Dict[str, Any]

Run component.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def run_component(self, **kwargs: Any) -> Dict[str, Any]:
    """Run component."""
    kwargs.update(self.partial_dict)
    kwargs = self.validate_component_inputs(kwargs)
    component_outputs = self._run_component(**kwargs)
    return self.validate_component_outputs(component_outputs)

arun_component async

arun_component(**kwargs: Any) -> Dict[str, Any]

Run component.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

async def arun_component(self, **kwargs: Any) -> Dict[str, Any]:
    """Run component."""
    kwargs.update(self.partial_dict)
    kwargs = self.validate_component_inputs(kwargs)
    component_outputs = await self._arun_component(**kwargs)
    return self.validate_component_outputs(component_outputs)

CustomQueryComponent

Bases: QueryComponent

Custom query component.

Parameters:

Name	Type	Description	Default
callback_manager	CallbackManager	Callback manager	<llama_index.core.callbacks.base.CallbackManager object at 0x7f3b5c1231a0>

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class CustomQueryComponent(QueryComponent):
    """Custom query component."""

    model_config = ConfigDict(arbitrary_types_allowed=True)
    callback_manager: CallbackManager = Field(
        default_factory=CallbackManager, description="Callback manager"
    )

    def set_callback_manager(self, callback_manager: CallbackManager) -> None:
        """Set callback manager."""
        self.callback_manager = callback_manager

    def _validate_component_inputs(self, input: Dict[str, Any]) -> Dict[str, Any]:
        """Validate component inputs during run_component."""
        # NOTE: user can override this method to validate inputs
        # but we do this by default for convenience
        return input

    async def _arun_component(self, **kwargs: Any) -> Any:
        """Run component (async)."""
        raise NotImplementedError("This component does not support async run.")

    @property
    def _input_keys(self) -> Set[str]:
        """Input keys dict."""
        raise NotImplementedError("Not implemented yet. Please override this method.")

    @property
    def _optional_input_keys(self) -> Set[str]:
        """Optional input keys dict."""
        return set()

    @property
    def _output_keys(self) -> Set[str]:
        """Output keys dict."""
        raise NotImplementedError("Not implemented yet. Please override this method.")

    @property
    def input_keys(self) -> InputKeys:
        """Input keys."""
        # NOTE: user can override this too, but we have them implement an
        # abstract method to make sure they do it

        return InputKeys.from_keys(
            required_keys=self._input_keys, optional_keys=self._optional_input_keys
        )

    @property
    def output_keys(self) -> OutputKeys:
        """Output keys."""
        # NOTE: user can override this too, but we have them implement an
        # abstract method to make sure they do it
        return OutputKeys.from_keys(self._output_keys)

input_keys property

input_keys: InputKeys

Input keys.

output_keys property

output_keys: OutputKeys

Output keys.

set_callback_manager

set_callback_manager(callback_manager: CallbackManager) -> None

Set callback manager.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

def set_callback_manager(self, callback_manager: CallbackManager) -> None:
    """Set callback manager."""
    self.callback_manager = callback_manager

Link

Bases: BaseModel

Link between two components.

Parameters:

Name	Type	Description	Default
src	str	Source component name	required
dest	str	Destination component name	required
src_key	str | None	Source component output key	None
dest_key	str | None	Destination component input key	None
condition_fn	Callable | None	Condition to determine if link should be followed	None
input_fn	Callable | None	Input to destination component	None

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class Link(BaseModel):
    """Link between two components."""

    src: str = Field(..., description="Source component name")
    dest: str = Field(..., description="Destination component name")
    src_key: Optional[str] = Field(
        default=None, description="Source component output key"
    )
    dest_key: Optional[str] = Field(
        default=None, description="Destination component input key"
    )

    condition_fn: Optional[Callable] = Field(
        default=None, description="Condition to determine if link should be followed"
    )
    input_fn: Optional[Callable] = Field(
        default=None, description="Input to destination component"
    )

    def __init__(
        self,
        src: str,
        dest: str,
        src_key: Optional[str] = None,
        dest_key: Optional[str] = None,
        condition_fn: Optional[Callable] = None,
        input_fn: Optional[Callable] = None,
    ) -> None:
        """Init params."""
        # NOTE: This is to enable positional args.
        super().__init__(
            src=src,
            dest=dest,
            src_key=src_key,
            dest_key=dest_key,
            condition_fn=condition_fn,
            input_fn=input_fn,
        )

ComponentIntermediates

Component intermediate inputs and outputs.

Source code in llama-index-core/llama_index/core/base/query_pipeline/query.py

class ComponentIntermediates:
    """Component intermediate inputs and outputs."""

    def __init__(
        self,
        inputs: Dict[str, Any],
        outputs: Dict[str, Any],
    ) -> None:
        """Initialize."""
        self.inputs = inputs
        self.outputs = outputs

    def __repr__(self) -> str:
        return (
            f"ComponentIntermediates(inputs={self.inputs!s}, "
            f"outputs={self.outputs!s})"
        )

    def __str__(self) -> str:
        return self.__repr__()