mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-07-25 12:35:29 -04:00
William FH
629fda3957
Evaluation so far has shown that agents do a reasonable job of emitting `json` blocks as arguments when cued (instead of typescript), and `json` permits the `strict=False` flag to permit control characters, which are likely to appear in the response in particular. This PR makes this change to the request and response synthesizer chains, and fixes the temperature to the OpenAI agent in the eval notebook. It also adds a `raise_error = False` flag in the notebook to facilitate debugging
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""request parser."""
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import json
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import re
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from langchain.chains.api.openapi.prompts import REQUEST_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 APIRequesterOutputParser(BaseOutputParser):
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"""Parse the request and error tags."""
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def _load_json_block(self, serialized_block: str) -> str:
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try:
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return json.dumps(json.loads(serialized_block, strict=False))
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except json.JSONDecodeError:
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return "ERROR serializing request."
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def parse(self, llm_output: str) -> str:
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"""Parse the request and error tags."""
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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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return self._load_json_block(json_match.group(1).strip())
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message_match = re.search(r"```text(.*?)```", llm_output, re.DOTALL)
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if message_match:
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return f"MESSAGE: {message_match.group(1).strip()}"
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return "ERROR making request"
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class APIRequesterChain(LLMChain):
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"""Get the request parser."""
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@classmethod
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def from_llm_and_typescript(
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cls, llm: BaseLLM, typescript_definition: str, verbose: bool = True
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) -> LLMChain:
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"""Get the request parser."""
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output_parser = APIRequesterOutputParser()
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prompt = PromptTemplate(
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template=REQUEST_TEMPLATE,
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output_parser=output_parser,
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partial_variables={"schema": typescript_definition},
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input_variables=["instructions"],
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)
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return cls(prompt=prompt, llm=llm, verbose=verbose)
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