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    Pythonlangchain-corepromptsfew_shot_with_templatesFewShotPromptWithTemplates
    Class●Since v0.1

    FewShotPromptWithTemplates

    Copy
    FewShotPromptWithTemplates(
      self,
      *args: Any = (),
      **kwargs: Any = {}
    )

    Bases

    StringPromptTemplate

    Attributes

    Methods

    Inherited fromStringPromptTemplate

    Methods

    Mformat_prompt
    —

    Format the prompt with the inputs.

    Maformat_prompt
    —

    Async format the prompt with the inputs.

    Mpretty_repr
    —

    Get a pretty representation of the prompt.

    M
    View source on GitHub
    pretty_print
    —

    Print a pretty representation of the prompt.

    Inherited fromBasePromptTemplate

    Attributes

    Ainput_variables: list[str]
    —

    A list of the names of the variables whose values are required as inputs to the

    Aoptional_variables: list[str]
    —

    A list of the names of the variables for placeholder or MessagePlaceholder that

    Ainput_types: builtins.dict[str, Any]
    —

    A dictionary of the types of the variables the prompt template expects.

    Aoutput_parser: BaseOutputParser | None
    —

    How to parse the output of calling an LLM on this formatted prompt.

    Apartial_variables: Mapping[str, Any]
    —

    A dictionary of the partial variables the prompt template carries.

    Ametadata: builtins.dict[str, Any] | None
    —

    Metadata to be used for tracing.

    Atags: list[str] | None
    —

    Tags to be used for tracing.

    AOutputType: Any
    —

    Return the output type of the prompt.

    Methods

    Mvalidate_variable_names
    —

    Validate variable names do not include restricted names.

    Mis_lc_serializable
    —

    Return True as this class is serializable.

    Mget_input_schema
    —

    Get the input schema for the prompt.

    Minvoke
    —

    Invoke the prompt.

    Inherited fromRunnableSerializable

    Attributes

    Aname: str | None
    —

    The name of the Runnable.

    Methods

    Mto_json
    —

    Serialize the Runnable to JSON.

    Mconfigurable_fields
    —

    Configure particular Runnable fields at runtime.

    Mconfigurable_alternatives
    —

    Configure alternatives for Runnable objects that can be set at runtime.

    Inherited fromSerializable

    Attributes

    Alc_secrets: dict[str, str]
    —

    A map of constructor argument names to secret ids.

    Alc_attributes: dict
    —

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

    Methods

    Mis_lc_serializable
    —

    Is this class serializable?

    Mlc_id
    —

    Return a unique identifier for this class for serialization purposes.

    Mto_json
    —

    Serialize the object to JSON.

    Mto_json_not_implemented
    —

    Serialize a "not implemented" object.

    Inherited fromRunnable

    Attributes

    Aname: str | None
    —

    The name of the Runnable. Used for debugging and tracing.

    AInputType: type[Input]
    —

    Input type.

    AOutputType: type[Output]
    —

    Output Type.

    Ainput_schema: type[BaseModel]
    —

    The type of input this Runnable accepts specified as a Pydantic model.

    Aoutput_schema: type[BaseModel]
    —

    Output schema.

    Aconfig_specs: list[ConfigurableFieldSpec]
    —

    List configurable fields for this Runnable.

    Methods

    Mget_name
    —

    Get the name of the Runnable.

    Mget_input_schema
    —

    Get a Pydantic model that can be used to validate input to the Runnable.

    Mget_input_jsonschema
    —

    Get a JSON schema that represents the input to the Runnable.

    Mget_output_schema
    —

    Get a Pydantic model that can be used to validate output to the Runnable.

    attribute
    examples: list[dict] | None

    Examples to format into the prompt.

    Either this or example_selector should be provided.

    attribute
    example_selector: BaseExampleSelector | None

    ExampleSelector to choose the examples to format into the prompt.

    Either this or examples should be provided.

    attribute
    example_prompt: PromptTemplate

    PromptTemplate used to format an individual example.

    attribute
    suffix: StringPromptTemplate

    A PromptTemplate to put after the examples.

    attribute
    example_separator: str

    String separator used to join the prefix, the examples, and suffix.

    attribute
    prefix: StringPromptTemplate | None

    A PromptTemplate to put before the examples.

    attribute
    template_format: PromptTemplateFormat

    The format of the prompt template.

    Options are: 'f-string', 'jinja2', 'mustache'.

    attribute
    validate_template: bool

    Whether or not to try validating the template.

    attribute
    model_config
    method
    get_lc_namespace

    Get the namespace of the LangChain object.

    method
    check_examples_and_selector

    Check that one and only one of examples/example_selector are provided.

    method
    template_is_valid

    Check that prefix, suffix, and input variables are consistent.

    method
    format

    Format the prompt with the inputs.

    method
    aformat

    Async format the prompt with the inputs.

    deprecatedmethod
    save

    Save the prompt to a file.

    Prompt template that contains few shot examples.

    M
    ainvoke
    —

    Async invoke the prompt.

    Mformat_prompt
    —

    Create PromptValue.

    Maformat_prompt
    —

    Async create PromptValue.

    Mpartial
    —

    Return a partial of the prompt template.

    Mdict
    —

    Return dictionary representation of prompt.

    M
    get_output_jsonschema
    —

    Get a JSON schema that represents the output of the Runnable.

    Mconfig_schema
    —

    The type of config this Runnable accepts specified as a Pydantic model.

    Mget_config_jsonschema
    —

    Get a JSON schema that represents the config of the Runnable.

    Mget_graph
    —

    Return a graph representation of this Runnable.

    Mget_prompts
    —

    Return a list of prompts used by this Runnable.

    Mpipe
    —

    Pipe Runnable objects.

    Mpick
    —

    Pick keys from the output dict of this Runnable.

    Massign
    —

    Assigns new fields to the dict output of this Runnable.

    Minvoke
    —

    Transform a single input into an output.

    Mainvoke
    —

    Transform a single input into an output.

    Mbatch
    —

    Default implementation runs invoke in parallel using a thread pool executor.

    Mbatch_as_completed
    —

    Run invoke in parallel on a list of inputs.

    Mabatch
    —

    Default implementation runs ainvoke in parallel using asyncio.gather.

    Mabatch_as_completed
    —

    Run ainvoke in parallel on a list of inputs.

    Mstream
    —

    Default implementation of stream, which calls invoke.

    Mastream
    —

    Default implementation of astream, which calls ainvoke.

    Mastream_log
    —

    Stream all output from a Runnable, as reported to the callback system.

    Mastream_events
    —

    Generate a stream of events.

    Mtransform
    —

    Transform inputs to outputs.

    Matransform
    —

    Transform inputs to outputs.

    Mbind
    —

    Bind arguments to a Runnable, returning a new Runnable.

    Mwith_config
    —

    Bind config to a Runnable, returning a new Runnable.

    Mwith_listeners
    —

    Bind lifecycle listeners to a Runnable, returning a new Runnable.

    Mwith_alisteners
    —

    Bind async lifecycle listeners to a Runnable.

    Mwith_types
    —

    Bind input and output types to a Runnable, returning a new Runnable.

    Mwith_retry
    —

    Create a new Runnable that retries the original Runnable on exceptions.

    Mmap
    —

    Return a new Runnable that maps a list of inputs to a list of outputs.

    Mwith_fallbacks
    —

    Add fallbacks to a Runnable, returning a new Runnable.

    Mas_tool
    —

    Create a BaseTool from a Runnable.