langchain_core.prompts.chat.HumanMessagePromptTemplate

class langchain_core.prompts.chat.HumanMessagePromptTemplate[source]

Bases: BaseStringMessagePromptTemplate

Human message prompt template. This is a message sent from the user.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

param additional_kwargs: dict [Optional]

Additional keyword arguments to pass to the prompt template.

param prompt: StringPromptTemplate [Required]

String prompt template.

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

format(**kwargs: Any) → BaseMessage[source]

Format the prompt template.

Parameters

**kwargs – Keyword arguments to use for formatting.

Returns

Formatted message.

format_messages(**kwargs: Any) → List[BaseMessage]

Format messages from kwargs.

Parameters

**kwargs – Keyword arguments to use for formatting.

Returns

List of BaseMessages.

classmethod from_orm(obj: Any) → Model
classmethod from_template(template: str, template_format: str = 'f-string', partial_variables: Optional[Dict[str, Any]] = None, **kwargs: Any) → MessagePromptTemplateT

Create a class from a string template.

Parameters

  • template – a template.

  • template_format – format of the template.

  • partial_variables –

    A dictionary of variables that can be used to partially

    fill in the template. For example, if the template is

    ”{variable1} {variable2}”, and partial_variables is {“variable1”: “foo”}, then the final prompt will be “foo {variable2}”.

  • **kwargs – keyword arguments to pass to the constructor.

Returns

A new instance of this class.

classmethod from_template_file(template_file: Union[str, Path], input_variables: List[str], **kwargs: Any) → MessagePromptTemplateT

Create a class from a template file.

Parameters

  • template_file – path to a template file. String or Path.

  • input_variables – list of input variables.

  • **kwargs – keyword arguments to pass to the constructor.

Returns

A new instance of this class.

classmethod get_lc_namespace() → List[str][source]

Get the namespace of the langchain object.

classmethod is_lc_serializable() → bool

Return whether or not the class is serializable.

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod lc_id() → List[str]

A unique identifier for this class for serialization purposes.

The unique identifier is a list of strings that describes the path to the object.

classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
classmethod parse_obj(obj: Any) → Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model
pretty_print() → None
pretty_repr(html: bool = False) → str

Human-readable representation.

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode
to_json() → Union[SerializedConstructor, SerializedNotImplemented]
to_json_not_implemented() → SerializedNotImplemented
classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model
property input_variables: List[str]

Input variables for this prompt template.

Returns

List of input variable names.

property lc_attributes: Dict

List of attribute names that should be included in the serialized kwargs.

These attributes must be accepted by the constructor.

property lc_secrets: Dict[str, str]

A map of constructor argument names to secret ids.

For example,

{“openai_api_key”: “OPENAI_API_KEY”}

Examples using HumanMessagePromptTemplate