mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-07-21 00:35:23 -04:00
Sunish Sheth
812e5f43f5
Used for serialization. Also add test that recurses through our subclasses to check they have them implemented Would fix https://github.com/hwchase17/langchain/issues/3217 Blocking: https://github.com/mlflow/mlflow/pull/8297 --------- Signed-off-by: Sunish Sheth <sunishsheth2009@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
"""request parser."""
|
|
|
|
import json
|
|
import re
|
|
from typing import Any
|
|
|
|
from langchain.base_language import BaseLanguageModel
|
|
from langchain.chains.api.openapi.prompts import REQUEST_TEMPLATE
|
|
from langchain.chains.llm import LLMChain
|
|
from langchain.prompts.prompt import PromptTemplate
|
|
from langchain.schema import BaseOutputParser
|
|
|
|
|
|
class APIRequesterOutputParser(BaseOutputParser):
|
|
"""Parse the request and error tags."""
|
|
|
|
def _load_json_block(self, serialized_block: str) -> str:
|
|
try:
|
|
return json.dumps(json.loads(serialized_block, strict=False))
|
|
except json.JSONDecodeError:
|
|
return "ERROR serializing request."
|
|
|
|
def parse(self, llm_output: str) -> str:
|
|
"""Parse the request and error tags."""
|
|
|
|
json_match = re.search(r"```json(.*?)```", llm_output, re.DOTALL)
|
|
if json_match:
|
|
return self._load_json_block(json_match.group(1).strip())
|
|
message_match = re.search(r"```text(.*?)```", llm_output, re.DOTALL)
|
|
if message_match:
|
|
return f"MESSAGE: {message_match.group(1).strip()}"
|
|
return "ERROR making request"
|
|
|
|
@property
|
|
def _type(self) -> str:
|
|
return "api_requester"
|
|
|
|
|
|
class APIRequesterChain(LLMChain):
|
|
"""Get the request parser."""
|
|
|
|
@classmethod
|
|
def from_llm_and_typescript(
|
|
cls,
|
|
llm: BaseLanguageModel,
|
|
typescript_definition: str,
|
|
verbose: bool = True,
|
|
**kwargs: Any,
|
|
) -> LLMChain:
|
|
"""Get the request parser."""
|
|
output_parser = APIRequesterOutputParser()
|
|
prompt = PromptTemplate(
|
|
template=REQUEST_TEMPLATE,
|
|
output_parser=output_parser,
|
|
partial_variables={"schema": typescript_definition},
|
|
input_variables=["instructions"],
|
|
)
|
|
return cls(prompt=prompt, llm=llm, verbose=verbose, **kwargs)
|