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    Pythonlangchain-corepromptsfew_shotFewShotPromptTemplate
    Class●Since v0.1

    FewShotPromptTemplate

    Prompt template that contains few shot examples.

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

    Bases

    _FewShotPromptTemplateMixinStringPromptTemplate

    Constructors

    constructor
    __init__

    Attributes

    attribute
    validate_template: bool

    Whether or not to try validating the template.

    attribute
    example_prompt: PromptTemplate

    PromptTemplate used to format an individual example.

    attribute
    suffix: str

    A prompt template string to put after the examples.

    attribute
    example_separator: str

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

    attribute
    prefix: str

    A prompt template string to put before the examples.

    attribute
    template_format: Literal['f-string', 'jinja2']

    The format of the prompt template.

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

    attribute
    model_config

    Methods

    method
    is_lc_serializable

    Return False as this class is not serializable.

    method
    template_is_valid

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

    method
    format

    Format the prompt with inputs generating a string.

    Use this method to generate a string representation of a prompt.

    method
    aformat

    Async format the prompt with inputs generating a string.

    Use this method to generate a string representation of a prompt.

    method
    save

    Save the prompt template to a file.

    Inherited fromStringPromptTemplate

    Methods

    Mget_lc_namespace
    —

    Get the namespace of the LangChain object.

    Mformat_prompt
    —

    Format prompt.

    Maformat_prompt
    —

    Async format prompt.

    Mpretty_repr
    —

    Return a pretty representation of the message for display.

    Mpretty_print
    —

    Print a pretty representation of the message.

    Inherited fromBasePromptTemplate

    Attributes

    Ainput_variables: list[str]
    —

    Template input variables.

    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: dict[str, Any] | None
    —

    Optional metadata associated with the retriever.

    Atags: list[str] | None
    —

    Optional list of tags associated with the retriever.

    AOutputType: Any

    Methods

    Mvalidate_variable_names
    —

    Validate variable names do not include restricted names.

    Mget_lc_namespace
    —

    Get the namespace of the LangChain object.

    Mget_input_schemaMinvoke
    —

    Invoke the retriever to get relevant documents.

    Mainvoke
    —

    Asynchronously invoke the retriever to get relevant documents.

    Mformat_prompt
    —

    Format prompt.

    Maformat_prompt
    —

    Async format prompt.

    Mpartial
    —

    Get a new ChatPromptTemplate with some input variables already filled in.

    Mdict
    —

    Return dictionary representation of output parser.

    Inherited fromRunnableSerializable

    Attributes

    Aname: str
    —

    The name of the function.

    Methods

    Mto_json
    —

    Convert the graph to a JSON-serializable format.

    Mconfigurable_fieldsMconfigurable_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

    Mget_lc_namespace
    —

    Get the namespace of the LangChain object.

    Mlc_id
    —

    Return a unique identifier for this class for serialization purposes.

    Mto_json
    —

    Convert the graph to a JSON-serializable format.

    Mto_json_not_implemented
    —

    Serialize a "not implemented" object.

    Inherited fromRunnable

    Attributes

    Aname: str
    —

    The name of the function.

    AInputType: AnyAOutputType: AnyAinput_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]

    Methods

    Mget_nameMget_input_schemaMget_input_jsonschema
    —

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

    Mget_output_schemaMget_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_graphMget_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
    —

    Merge the Dict input with the output produced by the mapping argument.

    Minvoke
    —

    Invoke the retriever to get relevant documents.

    Mainvoke
    —

    Asynchronously invoke the retriever to get relevant documents.

    MbatchMbatch_as_completed
    —

    Run invoke in parallel on a list of inputs.

    MabatchMabatch_as_completed
    —

    Run ainvoke in parallel on a list of inputs.

    MstreamMastreamMastream_log
    —

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

    Mastream_events
    —

    Generate a stream of events.

    MtransformMatransformMbind
    —

    Bind arguments to a Runnable, returning a new Runnable.

    Mwith_configMwith_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
    —

    Map a function to multiple iterables.

    Mwith_fallbacks
    —

    Add fallbacks to a Runnable, returning a new Runnable.

    Mas_tool
    —

    Create a BaseTool from a Runnable.

    View source on GitHub