DB-GPT/dbgpt/agent/expand/code_assistant_agent.py
明天 b124ecc10b
feat: (0.6)New UI (#1855)
Co-authored-by: 夏姜 <wenfengjiang.jwf@digital-engine.com>
Co-authored-by: aries_ckt <916701291@qq.com>
Co-authored-by: wb-lh513319 <wb-lh513319@alibaba-inc.com>
Co-authored-by: csunny <cfqsunny@163.com>
2024-08-21 17:37:45 +08:00

152 lines
7.9 KiB
Python

"""Code Assistant Agent."""
from typing import Optional, Tuple
from dbgpt.core import ModelMessageRoleType
from dbgpt.util.string_utils import str_to_bool
from ..core.agent import AgentMessage
from ..core.base_agent import ConversableAgent
from ..core.profile import DynConfig, ProfileConfig
from .actions.code_action import CodeAction
CHECK_RESULT_SYSTEM_MESSAGE = (
"You are an expert in analyzing the results of task execution. Your responsibility "
"is to analyze the task goals and execution results provided by the user, and "
"then make a judgment. You need to answer according to the following rules:\n"
" Rule 1: Determine whether the content of the focused execution results "
"is related to the task target content and whether it can be used as the answer to "
"the target question. For those who do not understand the content, as long as the "
"execution result type is required, it can be judged as correct.\n"
" Rule 2: There is no need to pay attention to whether the boundaries, "
"time range, and values of the answer content are correct.\n"
"As long as the task goal and execution result meet the above rules, True will be "
"returned; otherwise, False will be returned and the failure reason will be given."
"\nFor example:\n"
" If it is determined to be successful, only true will be returned, "
"such as: True.\n"
" If it is determined to be a failure, return false and the reason, "
"such as: False. There are no numbers in the execution results that answer the "
"computational goals of the mission.\n"
"You can refer to the following examples:\n"
"user: Please understand the following task objectives and results and give your "
"judgment:\nTask goal: Calculate the result of 1 + 2 using Python code.\n"
"Execution Result: 3\n"
"assistant: True\n\n"
"user: Please understand the following task objectives and results and give your "
"judgment:\nTask goal: Calculate the result of 100 * 10 using Python code.\n"
"Execution Result: 'you can get the result by multiplying 100 by 10'\n"
"assistant: False. There are no numbers in the execution results that answer the "
"computational goals of the mission.\n"
)
class CodeAssistantAgent(ConversableAgent):
"""Code Assistant Agent."""
profile: ProfileConfig = ProfileConfig(
name=DynConfig(
"Turing",
category="agent",
key="dbgpt_agent_expand_code_assistant_agent_profile_name",
),
role=DynConfig(
"CodeEngineer",
category="agent",
key="dbgpt_agent_expand_code_assistant_agent_profile_role",
),
goal=DynConfig(
"Solve tasks using your coding and language skills.\n"
"In the following cases, suggest python code (in a python coding block) or "
"shell script (in a sh coding block) for the user to execute.\n"
" 1. When you need to collect info, use the code to output the info you "
"need, for example, browse or search the web, download/read a file, print "
"the content of a webpage or a file, get the current date/time, check the "
"operating system. After sufficient info is printed and the task is ready "
"to be solved based on your language skill, you can solve the task by "
"yourself.\n"
" 2. When you need to perform some task with code, use the code to "
"perform the task and output the result. Finish the task smartly.",
category="agent",
key="dbgpt_agent_expand_code_assistant_agent_profile_goal",
),
constraints=DynConfig(
[
"The user cannot provide any other feedback or perform any other "
"action beyond executing the code you suggest. The user can't modify "
"your code. So do not suggest incomplete code which requires users to "
"modify. Don't use a code block if it's not intended to be executed "
"by the user.Don't ask users to copy and paste results. Instead, "
"the 'Print' function must be used for output when relevant.",
"When using code, you must indicate the script type in the code block. "
"Please don't include multiple code blocks in one response.",
"If you want the user to save the code in a file before executing it, "
"put # filename: <filename> inside the code block as the first line.",
"If you receive user input that indicates an error in the code "
"execution, fix the error and output the complete code again. It is "
"recommended to use the complete code rather than partial code or "
"code changes. If the error cannot be fixed, or the task is not "
"resolved even after the code executes successfully, analyze the "
"problem, revisit your assumptions, gather additional information you "
"need from historical conversation records, and consider trying a "
"different approach.",
"Unless necessary, give priority to solving problems with python "
"code. If it involves downloading files or storing data locally, "
"please use 'Print' to output the full file path of the stored data "
"and a brief introduction to the data.",
"The output content of the 'print' function will be passed to other "
"LLM agents as dependent data. Please control the length of the "
"output content of the 'print' function. The 'print' function only "
"outputs part of the key data information that is relied on, "
"and is as concise as possible.",
"The code is executed without user participation. It is forbidden to "
"use methods that will block the process or need to be shut down, "
"such as the plt.show() method of matplotlib.pyplot as plt.",
"It is prohibited to fabricate non-existent data to achieve goals.",
],
category="agent",
key="dbgpt_agent_expand_code_assistant_agent_profile_constraints",
),
desc=DynConfig(
"Can independently write and execute python/shell code to solve various"
" problems",
category="agent",
key="dbgpt_agent_expand_code_assistant_agent_profile_desc",
),
)
def __init__(self, **kwargs):
"""Create a new CodeAssistantAgent instance."""
super().__init__(**kwargs)
self._init_actions([CodeAction])
async def correctness_check(
self, message: AgentMessage
) -> Tuple[bool, Optional[str]]:
"""Verify whether the current execution results meet the target expectations."""
task_goal = message.current_goal
action_report = message.action_report
if not action_report:
return False, "No execution solution results were checked"
check_result, model = await self.thinking(
messages=[
AgentMessage(
role=ModelMessageRoleType.HUMAN,
content="Please understand the following task objectives and "
f"results and give your judgment:\n"
f"Task goal: {task_goal}\n"
f"Execution Result: {action_report.content}",
)
],
prompt=CHECK_RESULT_SYSTEM_MESSAGE,
)
success = str_to_bool(check_result)
fail_reason = None
if not success:
fail_reason = (
f"Your answer was successfully executed by the agent, but "
f"the goal cannot be completed yet. Please regenerate based on the "
f"failure reason:{check_result}"
)
return success, fail_reason