mirror of https://github.com/hwchase17/langchain
Nc/combining output parser (#3014)
Co-authored-by: vowelparrot <130414180+vowelparrot@users.noreply.github.com>pull/3051/head
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from __future__ import annotations
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from typing import Any, Dict, List
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from pydantic import root_validator
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from langchain.schema import BaseOutputParser
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class CombiningOutputParser(BaseOutputParser):
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"""Class to combine multiple output parsers into one."""
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parsers: List[BaseOutputParser]
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@root_validator()
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def validate_parsers(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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"""Validate the parsers."""
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parsers = values["parsers"]
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if len(parsers) < 2:
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raise ValueError("Must have at least two parsers")
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for parser in parsers:
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if parser._type == "combining":
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raise ValueError("Cannot nest combining parsers")
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if parser._type == "list":
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raise ValueError("Cannot comine list parsers")
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return values
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@property
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def _type(self) -> str:
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"""Return the type key."""
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return "combining"
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def get_format_instructions(self) -> str:
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"""Instructions on how the LLM output should be formatted."""
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initial = f"For your first output: {self.parsers[0].get_format_instructions()}"
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subsequent = "\n".join(
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[
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f"Complete that output fully. Then produce another output, separated by two newline characters: {p.get_format_instructions()}" # noqa: E501
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for p in self.parsers[1:]
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]
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)
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return f"{initial}\n{subsequent}"
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def parse(self, text: str) -> Dict[str, Any]:
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"""Parse the output of an LLM call."""
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texts = text.split("\n\n")
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output = dict()
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for i, parser in enumerate(self.parsers):
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output.update(parser.parse(texts[i].strip()))
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return output
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"""Test in memory docstore."""
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from langchain.output_parsers.combining import CombiningOutputParser
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from langchain.output_parsers.regex import RegexParser
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from langchain.output_parsers.structured import ResponseSchema, StructuredOutputParser
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DEF_EXPECTED_RESULT = {
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"answer": "Paris",
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"source": "https://en.wikipedia.org/wiki/France",
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"confidence": "A",
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"explanation": "Paris is the capital of France according to Wikipedia.",
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}
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DEF_README = """```json
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{
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"answer": "Paris",
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"source": "https://en.wikipedia.org/wiki/France"
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}
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```
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//Confidence: A, Explanation: Paris is the capital of France according to Wikipedia."""
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def test_combining_dict_result() -> None:
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"""Test combining result."""
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parsers = [
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StructuredOutputParser(
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response_schemas=[
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ResponseSchema(
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name="answer", description="answer to the user's question"
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),
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ResponseSchema(
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name="source",
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description="source used to answer the user's question",
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),
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]
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),
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RegexParser(
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regex=r"Confidence: (A|B|C), Explanation: (.*)",
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output_keys=["confidence", "explanation"],
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default_output_key="noConfidence",
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),
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]
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combining_parser = CombiningOutputParser(parsers=parsers)
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result_dict = combining_parser.parse(DEF_README)
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assert DEF_EXPECTED_RESULT == result_dict
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