forked from Archives/langchain
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.
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
from __future__ import annotations
|
|
|
|
from typing import Any, Dict, List
|
|
|
|
from pydantic import root_validator
|
|
|
|
from langchain.schema import BaseOutputParser
|
|
|
|
|
|
class CombiningOutputParser(BaseOutputParser):
|
|
"""Class to combine multiple output parsers into one."""
|
|
|
|
parsers: List[BaseOutputParser]
|
|
|
|
@root_validator()
|
|
def validate_parsers(cls, values: Dict[str, Any]) -> Dict[str, Any]:
|
|
"""Validate the parsers."""
|
|
parsers = values["parsers"]
|
|
if len(parsers) < 2:
|
|
raise ValueError("Must have at least two parsers")
|
|
for parser in parsers:
|
|
if parser._type == "combining":
|
|
raise ValueError("Cannot nest combining parsers")
|
|
if parser._type == "list":
|
|
raise ValueError("Cannot comine list parsers")
|
|
return values
|
|
|
|
@property
|
|
def _type(self) -> str:
|
|
"""Return the type key."""
|
|
return "combining"
|
|
|
|
def get_format_instructions(self) -> str:
|
|
"""Instructions on how the LLM output should be formatted."""
|
|
|
|
initial = f"For your first output: {self.parsers[0].get_format_instructions()}"
|
|
subsequent = "\n".join(
|
|
f"Complete that output fully. Then produce another output, separated by two newline characters: {p.get_format_instructions()}" # noqa: E501
|
|
for p in self.parsers[1:]
|
|
)
|
|
return f"{initial}\n{subsequent}"
|
|
|
|
def parse(self, text: str) -> Dict[str, Any]:
|
|
"""Parse the output of an LLM call."""
|
|
texts = text.split("\n\n")
|
|
output = dict()
|
|
for txt, parser in zip(texts, self.parsers):
|
|
output.update(parser.parse(txt.strip()))
|
|
return output
|