mirror of https://github.com/hwchase17/langchain
move base prompt to schema (#6995)
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>pull/7316/head
Harrison Chase
1 year ago
committed by
GitHub
parent
200be43da6
commit
60b05511d3
@ -0,0 +1,139 @@
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from __future__ import annotations
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import json
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from abc import ABC, abstractmethod
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from pathlib import Path
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from typing import Any, Callable, Dict, List, Mapping, Optional, Union
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import yaml
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from pydantic import Field, root_validator
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from langchain.load.serializable import Serializable
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from langchain.schema import BaseOutputParser, PromptValue
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class BasePromptTemplate(Serializable, ABC):
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"""Base class for all prompt templates, returning a prompt."""
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input_variables: List[str]
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"""A list of the names of the variables the prompt template expects."""
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output_parser: Optional[BaseOutputParser] = None
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"""How to parse the output of calling an LLM on this formatted prompt."""
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partial_variables: Mapping[str, Union[str, Callable[[], str]]] = Field(
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default_factory=dict
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)
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@property
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def lc_serializable(self) -> bool:
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return True
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class Config:
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"""Configuration for this pydantic object."""
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arbitrary_types_allowed = True
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@abstractmethod
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def format_prompt(self, **kwargs: Any) -> PromptValue:
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"""Create Chat Messages."""
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@root_validator()
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def validate_variable_names(cls, values: Dict) -> Dict:
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"""Validate variable names do not include restricted names."""
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if "stop" in values["input_variables"]:
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raise ValueError(
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"Cannot have an input variable named 'stop', as it is used internally,"
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" please rename."
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)
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if "stop" in values["partial_variables"]:
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raise ValueError(
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"Cannot have an partial variable named 'stop', as it is used "
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"internally, please rename."
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)
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overall = set(values["input_variables"]).intersection(
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values["partial_variables"]
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)
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if overall:
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raise ValueError(
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f"Found overlapping input and partial variables: {overall}"
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)
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return values
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def partial(self, **kwargs: Union[str, Callable[[], str]]) -> BasePromptTemplate:
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"""Return a partial of the prompt template."""
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prompt_dict = self.__dict__.copy()
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prompt_dict["input_variables"] = list(
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set(self.input_variables).difference(kwargs)
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)
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prompt_dict["partial_variables"] = {**self.partial_variables, **kwargs}
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return type(self)(**prompt_dict)
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def _merge_partial_and_user_variables(self, **kwargs: Any) -> Dict[str, Any]:
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# Get partial params:
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partial_kwargs = {
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k: v if isinstance(v, str) else v()
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for k, v in self.partial_variables.items()
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}
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return {**partial_kwargs, **kwargs}
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@abstractmethod
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def format(self, **kwargs: Any) -> str:
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"""Format the prompt with the inputs.
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Args:
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kwargs: Any arguments to be passed to the prompt template.
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Returns:
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A formatted string.
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Example:
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.. code-block:: python
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prompt.format(variable1="foo")
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"""
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@property
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def _prompt_type(self) -> str:
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"""Return the prompt type key."""
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raise NotImplementedError
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def dict(self, **kwargs: Any) -> Dict:
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"""Return dictionary representation of prompt."""
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prompt_dict = super().dict(**kwargs)
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prompt_dict["_type"] = self._prompt_type
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return prompt_dict
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def save(self, file_path: Union[Path, str]) -> None:
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"""Save the prompt.
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Args:
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file_path: Path to directory to save prompt to.
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Example:
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.. code-block:: python
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prompt.save(file_path="path/prompt.yaml")
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"""
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if self.partial_variables:
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raise ValueError("Cannot save prompt with partial variables.")
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# Convert file to Path object.
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if isinstance(file_path, str):
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save_path = Path(file_path)
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else:
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save_path = file_path
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directory_path = save_path.parent
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directory_path.mkdir(parents=True, exist_ok=True)
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# Fetch dictionary to save
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prompt_dict = self.dict()
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if save_path.suffix == ".json":
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with open(file_path, "w") as f:
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json.dump(prompt_dict, f, indent=4)
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elif save_path.suffix == ".yaml":
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with open(file_path, "w") as f:
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yaml.dump(prompt_dict, f, default_flow_style=False)
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else:
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raise ValueError(f"{save_path} must be json or yaml")
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