andre/crewAI
1
0
Fork 0
mirror of https://github.com/crewAIInc/crewAI.git synced 2026-01-09 08:08:32 +00:00
Code Issues Actions 3 Packages Projects Releases Wiki Activity

Update inner tool usage logic to support both regular and function calling

Browse Source
This commit is contained in:
João Moura
2024-03-02 13:54:23 -03:00
parent c12283bb16
commit 42eeec5897
10 changed files with 208 additions and 142 deletions
Download Patch File Download Diff File Expand all files Collapse all files

73
src/crewai/agents/parser.py
View File

@@ -1,3 +1,4 @@
import re
from typing import Any, Union
from langchain.agents.output_parsers import ReActSingleInputOutputParser
@@ -6,13 +7,14 @@ from langchain_core.exceptions import OutputParserException
from crewai.utilities import I18N
TOOL_USAGE_SECTION = "Use Tool:"
FINAL_ANSWER_ACTION = "Final Answer:"
FINAL_ANSWER_AND_TOOL_ERROR_MESSAGE = "I tried to use a tool and give a final answer at the same time, I must choose only one."
MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE = "I did it wrong. Invalid Format: I missed the 'Action:' after 'Thought:'. I will do right next, and don't use a tool I have already used.\n"
MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE = "I did it wrong. Invalid Format: I missed the 'Action Input:' after 'Action:'. I will do right next, and don't use a tool I have already used.\n"
FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE = "I did it wrong. Tried to both perform Action and give a Final Answer at the same time, I must do one or the other"
class CrewAgentParser(ReActSingleInputOutputParser):
"""Parses Crew-style LLM calls that have a single tool input.
"""Parses ReAct-style LLM calls that have a single tool input.
Expects output to be in one of two formats.
@@ -20,17 +22,16 @@ class CrewAgentParser(ReActSingleInputOutputParser):
should be in the below format. This will result in an AgentAction
being returned.
```
Use Tool: All context for using the tool here
```
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
```
"""
_i18n: I18N = I18N()
@@ -38,26 +39,52 @@ class CrewAgentParser(ReActSingleInputOutputParser):
def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
includes_answer = FINAL_ANSWER_ACTION in text
includes_tool = TOOL_USAGE_SECTION in text
if includes_tool:
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:
self.agent.increment_formatting_errors()
raise OutputParserException(f"{FINAL_ANSWER_AND_TOOL_ERROR_MESSAGE}")
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("", "", text)
return AgentAction(action, tool_input, text)
elif includes_answer:
return AgentFinish(
{"output": text.split(FINAL_ANSWER_ACTION)[-1].strip()}, text
)
format = self._i18n.slice("format_without_tools")
error = f"{format}"
self.agent.increment_formatting_errors()
raise OutputParserException(
error,
observation=error,
llm_output=text,
send_to_llm=True,
)
if not re.search(r"Action\s*\d*\s*:[\s]*(.*?)", text, re.DOTALL):
self.agent.increment_formatting_errors()
raise OutputParserException(
f"Could not parse LLM output: `{text}`",
observation=f"{MISSING_ACTION_AFTER_THOUGHT_ERROR_MESSAGE}\n{self._i18n.slice('final_answer_format')}",
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
):
self.agent.increment_formatting_errors()
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:
format = self._i18n.slice("format_without_tools")
error = f"{format}"
self.agent.increment_formatting_errors()
raise OutputParserException(
error,
observation=error,
llm_output=text,
send_to_llm=True,
)