You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
langchain/langchain/prompts/prompt.py

134 lines
4.1 KiB
Python

"""Prompt schema definition."""
from __future__ import annotations
from string import Formatter
from typing import Any, Dict, List
from pydantic import BaseModel, Extra, root_validator
from langchain.prompts.base import (
DEFAULT_FORMATTER_MAPPING,
BasePromptTemplate,
check_valid_template,
)
class PromptTemplate(BasePromptTemplate, BaseModel):
"""Schema to represent a prompt for an LLM.
Example:
.. code-block:: python
from langchain import PromptTemplate
prompt = PromptTemplate(input_variables=["foo"], template="Say {foo}")
"""
input_variables: List[str]
"""A list of the names of the variables the prompt template expects."""
template: str
"""The prompt template."""
template_format: str = "f-string"
"""The format of the prompt template. Options are: 'f-string', 'jinja2'."""
validate_template: bool = True
"""Whether or not to try validating the template."""
@property
def _prompt_type(self) -> str:
"""Return the prompt type key."""
return "prompt"
class Config:
"""Configuration for this pydantic object."""
extra = Extra.forbid
def format(self, **kwargs: Any) -> str:
"""Format the prompt with the inputs.
Args:
kwargs: Any arguments to be passed to the prompt template.
Returns:
A formatted string.
Example:
.. code-block:: python
prompt.format(variable1="foo")
"""
kwargs = self._merge_partial_and_user_variables(**kwargs)
return DEFAULT_FORMATTER_MAPPING[self.template_format](self.template, **kwargs)
@root_validator()
def template_is_valid(cls, values: Dict) -> Dict:
"""Check that template and input variables are consistent."""
if values["validate_template"]:
all_inputs = values["input_variables"] + list(values["partial_variables"])
check_valid_template(
values["template"], values["template_format"], all_inputs
)
return values
@classmethod
def from_examples(
cls,
examples: List[str],
suffix: str,
input_variables: List[str],
example_separator: str = "\n\n",
prefix: str = "",
) -> PromptTemplate:
"""Take examples in list format with prefix and suffix to create a prompt.
Intended be used as a way to dynamically create a prompt from examples.
Args:
examples: List of examples to use in the prompt.
suffix: String to go after the list of examples. Should generally
set up the user's input.
input_variables: A list of variable names the final prompt template
will expect.
example_separator: The separator to use in between examples. Defaults
to two new line characters.
prefix: String that should go before any examples. Generally includes
examples. Default to an empty string.
Returns:
The final prompt generated.
"""
template = example_separator.join([prefix, *examples, suffix])
return cls(input_variables=input_variables, template=template)
@classmethod
def from_file(
cls, template_file: str, input_variables: List[str]
) -> PromptTemplate:
"""Load a prompt from a file.
Args:
template_file: The path to the file containing the prompt template.
input_variables: A list of variable names the final prompt template
will expect.
Returns:
The prompt loaded from the file.
"""
with open(template_file, "r") as f:
template = f.read()
return cls(input_variables=input_variables, template=template)
@classmethod
def from_template(cls, template: str) -> PromptTemplate:
"""Load a prompt template from a template."""
input_variables = {
v for _, v, _, _ in Formatter().parse(template) if v is not None
}
return cls(input_variables=list(sorted(input_variables)), template=template)
# For backwards compatibility.
Prompt = PromptTemplate