Source code for langchain.agents.output_parsers.react_single_input
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.mrkl.prompt import FORMAT_INSTRUCTIONS
FINAL_ANSWER_ACTION = "Final Answer:"
MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE = (
"Invalid Format: Missing 'Action:' after 'Thought:"
)
MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE = (
"Invalid Format: Missing 'Action Input:' after 'Action:'"
)
FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE = (
"Parsing LLM output produced both a final answer and a parse-able action:"
)
[docs]class ReActSingleInputOutputParser(AgentOutputParser):
"""Parses ReAct-style LLM calls that have a single tool input.
Expects output to be in one of two formats.
If the output signals that an action should be taken,
should be in the below format. This will result in an AgentAction
being returned.
```
Thought: agent thought here
Action: search
Action Input: what is the temperature in SF?
```
If the output signals that a final answer should be given,
should be in the below format. This will result in an AgentFinish
being returned.
```
Thought: agent thought here
Final Answer: The temperature is 100 degrees
```
"""
[docs] def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
includes_answer = FINAL_ANSWER_ACTION in text
regex = (
r"Action\s*\d*\s*:[\s]*(.*?)[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
)
action_match = re.search(regex, text, re.DOTALL)
if action_match:
if includes_answer:
raise OutputParserException(
f"{FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE}: {text}"
)
action = action_match.group(1).strip()
action_input = action_match.group(2)
tool_input = action_input.strip(" ")
tool_input = tool_input.strip('"')
return AgentAction(action, tool_input, text)
elif includes_answer:
return AgentFinish(
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()}, text
)
if not re.search(r"Action\s*\d*\s*:[\s]*(.*?)", text, re.DOTALL):
raise OutputParserException(
f"Could not parse LLM output: `{text}`",
observation=MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE,
llm_output=text,
send_to_llm=True,
)
elif not re.search(
r"[\s]*Action\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)", text, re.DOTALL
):
raise OutputParserException(
f"Could not parse LLM output: `{text}`",
observation=MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
llm_output=text,
send_to_llm=True,
)
else:
raise OutputParserException(f"Could not parse LLM output: `{text}`")
@property
def _type(self) -> str:
return "react-single-input"