Source code for langchain.chains.api.openapi.response_chain

"""Response parser."""

import json
import re
from typing import Any

from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from langchain_core.prompts.prompt import PromptTemplate

from langchain.chains.api.openapi.prompts import RESPONSE_TEMPLATE
from langchain.chains.llm import LLMChain

[docs]class APIResponderOutputParser(BaseOutputParser): """Parse the response and error tags.""" def _load_json_block(self, serialized_block: str) -> str: try: response_content = json.loads(serialized_block, strict=False) return response_content.get("response", "ERROR parsing response.") except json.JSONDecodeError: return "ERROR parsing response." except: raise
[docs] def parse(self, llm_output: str) -> str: """Parse the response and error tags.""" json_match ="```json(.*?)```", llm_output, re.DOTALL) if json_match: return self._load_json_block( else: raise ValueError(f"No response found in output: {llm_output}.")
@property def _type(self) -> str: return "api_responder"
[docs]class APIResponderChain(LLMChain): """Get the response parser."""
[docs] @classmethod def is_lc_serializable(cls) -> bool: return False
[docs] @classmethod def from_llm( cls, llm: BaseLanguageModel, verbose: bool = True, **kwargs: Any ) -> LLMChain: """Get the response parser.""" output_parser = APIResponderOutputParser() prompt = PromptTemplate( template=RESPONSE_TEMPLATE, output_parser=output_parser, input_variables=["response", "instructions"], ) return cls(prompt=prompt, llm=llm, verbose=verbose, **kwargs)