Source code for langchain.agents.conversational.output_parser
import re
from typing import Union
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException
from langchain.agents.agent import AgentOutputParser
from langchain.agents.conversational.prompt import FORMAT_INSTRUCTIONS
[docs]
class ConvoOutputParser(AgentOutputParser):
"""Output parser for the conversational agent."""
ai_prefix: str = "AI"
"""Prefix to use before AI output."""
format_instructions: str = FORMAT_INSTRUCTIONS
"""Default formatting instructions"""
[docs]
def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
"""Parse the output from the agent into
an AgentAction or AgentFinish object.
Args:
text: The text to parse.
Returns:
An AgentAction or AgentFinish object.
"""
if f"{self.ai_prefix}:" in text:
return AgentFinish(
{"output": text.split(f"{self.ai_prefix}:")[-1].strip()}, text
)
regex = r"Action: (.*?)[\n]*Action Input: ([\s\S]*)"
match = re.search(regex, text, re.DOTALL)
if not match:
raise OutputParserException(f"Could not parse LLM output: `{text}`")
action = match.group(1)
action_input = match.group(2)
return AgentAction(action.strip(), action_input.strip(" ").strip('"'), text)
@property
def _type(self) -> str:
return "conversational"