Feature/use converter instead of manually trimming (#894)

* Exploring output being passed to tool selector to see if we can better format data

* WIP. Adding JSON repair functionality

* Almost done implementing JSON repair. Testing fixes vs current base case.

* More action cleanup with additional tests

* WIP. Trying to figure out what is going on with tool descriptions

* Update tool description generation

* WIP. Trying to find out what is causing the tools to duplicate

* Replacing tools properly instead of duplicating them accidentally

* Fixing issues for MR

* Update dependencies for JSON_REPAIR

* More cleaning up pull request

* preppering for call

* Fix type-checking issues

---------

Co-authored-by: João Moura <joaomdmoura@gmail.com>
This commit is contained in:
Brandon Hancock (bhancock_ai)
2024-07-15 07:53:41 -04:00
committed by GitHub
parent 4eb4073661
commit 7acf0b2107
13 changed files with 552 additions and 68 deletions

View File

@@ -24,6 +24,7 @@ class BaseAgentTools(BaseModel, ABC):
is_list = coworker.startswith("[") and coworker.endswith("]")
if is_list:
coworker = coworker[1:-1].split(",")[0]
return coworker
def delegate_work(
@@ -40,11 +41,13 @@ class BaseAgentTools(BaseModel, ABC):
coworker = self._get_coworker(coworker, **kwargs)
return self._execute(coworker, question, context)
def _execute(self, agent: Union[str, None], task: str, context: Union[str, None]):
def _execute(
self, agent_name: Union[str, None], task: str, context: Union[str, None]
):
"""Execute the command."""
try:
if agent is None:
agent = ""
if agent_name is None:
agent_name = ""
# It is important to remove the quotes from the agent name.
# The reason we have to do this is because less-powerful LLM's
@@ -53,7 +56,7 @@ class BaseAgentTools(BaseModel, ABC):
# {"task": "....", "coworker": "....
# when it should look like this:
# {"task": "....", "coworker": "...."}
agent_name = agent.casefold().replace('"', "").replace("\n", "")
agent_name = agent_name.casefold().replace('"', "").replace("\n", "")
agent = [ # type: ignore # Incompatible types in assignment (expression has type "list[BaseAgent]", variable has type "str | None")
available_agent
@@ -75,9 +78,9 @@ class BaseAgentTools(BaseModel, ABC):
)
agent = agent[0]
task = Task( # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
task_with_assigned_agent = Task( # type: ignore # Incompatible types in assignment (expression has type "Task", variable has type "str")
description=task,
agent=agent,
expected_output="Your best answer to your coworker asking you this, accounting for the context shared.",
)
return agent.execute_task(task, context) # type: ignore # "str" has no attribute "execute_task"
return agent.execute_task(task_with_assigned_agent, context)

View File

@@ -1,7 +1,7 @@
from abc import ABC, abstractmethod
from typing import Any, Optional
from pydantic import BaseModel, Field, PrivateAttr
from pydantic import BaseModel, Field
class OutputConverter(BaseModel, ABC):
@@ -21,7 +21,6 @@ class OutputConverter(BaseModel, ABC):
max_attempts (int): Maximum number of conversion attempts (default: 3).
"""
_is_gpt: bool = PrivateAttr(default=True)
text: str = Field(description="Text to be converted.")
llm: Any = Field(description="The language model to be used to convert the text.")
model: Any = Field(description="The model to be used to convert the text.")
@@ -41,7 +40,8 @@ class OutputConverter(BaseModel, ABC):
"""Convert text to json."""
pass
@abstractmethod # type: ignore # Name "_is_gpt" already defined on line 25
def _is_gpt(self, llm): # type: ignore # Name "_is_gpt" already defined on line 25
@property
@abstractmethod
def is_gpt(self) -> bool:
"""Return if llm provided is of gpt from openai."""
pass

View File

@@ -1,14 +1,6 @@
import threading
import time
from typing import (
Any,
Dict,
Iterator,
List,
Optional,
Tuple,
Union,
)
from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
from langchain.agents import AgentExecutor
from langchain.agents.agent import ExceptionTool
@@ -19,9 +11,7 @@ from langchain_core.tools import BaseTool
from langchain_core.utils.input import get_color_mapping
from pydantic import InstanceOf
from crewai.agents.agent_builder.base_agent_executor_mixin import (
CrewAgentExecutorMixin,
)
from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
from crewai.agents.tools_handler import ToolsHandler
from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
from crewai.utilities import I18N

View File

@@ -1,6 +1,7 @@
import re
from typing import Any, Union
from json_repair import repair_json
from langchain.agents.output_parsers import ReActSingleInputOutputParser
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException
@@ -48,11 +49,15 @@ class CrewAgentParser(ReActSingleInputOutputParser):
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)
action = action_match.group(1)
clean_action = self._clean_action(action)
action_input = action_match.group(2).strip()
tool_input = action_input.strip(" ").strip('"')
safe_tool_input = self._safe_repair_json(tool_input)
return AgentAction(clean_action, safe_tool_input, text)
elif includes_answer:
return AgentFinish(
@@ -87,3 +92,30 @@ class CrewAgentParser(ReActSingleInputOutputParser):
llm_output=text,
send_to_llm=True,
)
def _clean_action(self, text: str) -> str:
"""Clean action string by removing non-essential formatting characters."""
return re.sub(r"^\s*\*+\s*|\s*\*+\s*$", "", text).strip()
def _safe_repair_json(self, tool_input: str) -> str:
UNABLE_TO_REPAIR_JSON_RESULTS = ['""', "{}"]
# Skip repair if the input starts and ends with square brackets
# Explanation: The JSON parser has issues handling inputs that are enclosed in square brackets ('[]').
# These are typically valid JSON arrays or strings that do not require repair. Attempting to repair such inputs
# might lead to unintended alterations, such as wrapping the entire input in additional layers or modifying
# the structure in a way that changes its meaning. By skipping the repair for inputs that start and end with
# square brackets, we preserve the integrity of these valid JSON structures and avoid unnecessary modifications.
if tool_input.startswith("[") and tool_input.endswith("]"):
return tool_input
# Before repair, handle common LLM issues:
# 1. Replace """ with " to avoid JSON parser errors
tool_input = tool_input.replace('"""', '"')
result = repair_json(tool_input)
if result in UNABLE_TO_REPAIR_JSON_RESULTS:
return tool_input
return str(result)