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62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
"""Response parser."""
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import json
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import re
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from typing import Dict
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from pydantic import root_validator
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from langchain.chains.api.openapi.prompts import RESPONSE_TEMPLATE
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from langchain.chains.llm import LLMChain
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from langchain.llms.base import BaseLLM
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from langchain.prompts.prompt import PromptTemplate
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from langchain.schema import BaseOutputParser
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class APIResponderOutputParser(BaseOutputParser):
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"""Parse the response and error tags."""
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that json5 package exists."""
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try:
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import json5 # noqa: F401
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except ImportError:
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raise ValueError(
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"Could not import json5 python package. "
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"Please it install it with `pip install json5`."
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)
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return values
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def parse(self, llm_output: str) -> str:
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"""Parse the response and error tags."""
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import json5
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json_match = re.search(r"```json(.*?)```", llm_output, re.DOTALL)
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if json_match:
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try:
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response_content = json5.loads(json_match.group(1).strip())
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return response_content.get("response", "ERROR parsing response.")
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except json.JSONDecodeError:
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return "ERROR parsing response."
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except:
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raise
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else:
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raise ValueError("No response found in output.")
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class APIResponderChain(LLMChain):
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"""Get the response parser."""
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@classmethod
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def from_llm(cls, llm: BaseLLM, verbose: bool = True) -> LLMChain:
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"""Get the response parser."""
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output_parser = APIResponderOutputParser()
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prompt = PromptTemplate(
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template=RESPONSE_TEMPLATE,
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output_parser=output_parser,
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input_variables=["response", "instructions"],
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)
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return cls(prompt=prompt, llm=llm, verbose=verbose)
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