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fix(agent): format problem (#2275)

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Co-authored-by: cinjospeh <joseph.cjn@alibaba-inc.com>
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cinjoseph 2025-01-06 14:06:52 +08:00 committed by GitHub
parent 56670f0084
commit 1a1fec02ef
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5 changed files with 193 additions and 144 deletions
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127
dbgpt/agent/resource/app.py
View File

@ -1,20 +1,23 @@
"""Application Resources for the agent."""
import dataclasses import dataclasses
import uuid import uuid
from typing import Optional, Tuple, Dict, Type, Any, List, cast from typing import Any, Dict, List, Optional, Tuple, Type, cast
from dbgpt.agent import ConversableAgent, AgentMessage, AgentContext from dbgpt.agent import AgentMessage, ConversableAgent
from dbgpt.serve.agent.agents.app_agent_manage import get_app_manager from dbgpt.serve.agent.agents.app_agent_manage import get_app_manager
from dbgpt.util import ParameterDescription from dbgpt.util import ParameterDescription
from .base import Resource, ResourceParameters, ResourceType from .base import Resource, ResourceParameters, ResourceType
def get_app_list(): def _get_app_list():
apps = get_app_manager().get_dbgpts() apps = get_app_manager().get_dbgpts()
results = [ results = [
{ {
"label": f"{app.app_name}({app.app_code})", "label": f"{app.app_name}({app.app_code})",
"key": app.app_code, "key": app.app_code,
"description": app.app_describe "description": app.app_describe,
} }
for app in apps for app in apps
] ]
@ -23,20 +26,21 @@ def get_app_list():
@dataclasses.dataclass @dataclasses.dataclass
class AppResourceParameters(ResourceParameters): class AppResourceParameters(ResourceParameters):
"""Application resource class."""
app_code: str = dataclasses.field( app_code: str = dataclasses.field(
default=None,
metadata={ metadata={
"help": "app code", "help": "app code",
"valid_values": get_app_list(), "valid_values": _get_app_list(),
}, },
) )
@classmethod @classmethod
def to_configurations( def to_configurations(
cls, cls,
parameters: Type["AppResourceParameters"], parameters: Type["AppResourceParameters"],
version: Optional[str] = None, version: Optional[str] = None,
**kwargs, **kwargs,
) -> Any: ) -> Any:
"""Convert the parameters to configurations.""" """Convert the parameters to configurations."""
conf: List[ParameterDescription] = cast( conf: List[ParameterDescription] = cast(
@ -53,7 +57,7 @@ class AppResourceParameters(ResourceParameters):
@classmethod @classmethod
def from_dict( def from_dict(
cls, data: dict, ignore_extra_fields: bool = True cls, data: dict, ignore_extra_fields: bool = True
) -> ResourceParameters: ) -> ResourceParameters:
"""Create a new instance from a dictionary.""" """Create a new instance from a dictionary."""
copied_data = data.copy() copied_data = data.copy()
@ -66,6 +70,7 @@ class AppResource(Resource[AppResourceParameters]):
"""AppResource resource class.""" """AppResource resource class."""
def __init__(self, name: str, app_code: str, **kwargs): def __init__(self, name: str, app_code: str, **kwargs):
"""Initialize AppResource resource."""
self._resource_name = name self._resource_name = name
self._app_code = app_code self._app_code = app_code
@ -73,12 +78,24 @@ class AppResource(Resource[AppResourceParameters]):
self._app_name = app.app_name self._app_name = app.app_name
self._app_desc = app.app_describe self._app_desc = app.app_describe
@property
def app_desc(self):
"""Return the app description."""
return self._app_desc
@property
def app_name(self):
"""Return the app name."""
return self._app_name
@classmethod @classmethod
def type(cls) -> ResourceType: def type(cls) -> ResourceType:
"""Return the resource type."""
return ResourceType.App return ResourceType.App
@property @property
def name(self) -> str: def name(self) -> str:
"""Return the resource name."""
return self._resource_name return self._resource_name
@classmethod @classmethod
@ -86,13 +103,18 @@ class AppResource(Resource[AppResourceParameters]):
"""Return the resource parameters class.""" """Return the resource parameters class."""
return AppResourceParameters return AppResourceParameters
async def get_prompt(self, *, lang: str = "en", prompt_type: str = "default", question: Optional[str] = None, async def get_prompt(
resource_name: Optional[str] = None, **kwargs) -> Tuple[str, Optional[Dict]]: self,
*,
lang: str = "en",
prompt_type: str = "default",
question: Optional[str] = None,
resource_name: Optional[str] = None,
**kwargs,
) -> Tuple[str, Optional[Dict]]:
"""Get the prompt.""" """Get the prompt."""
prompt_template_zh = ( prompt_template_zh = (
"{name}：调用此资源与应用 {app_name} 进行交互。" "{name}：调用此资源与应用 {app_name} 进行交互。" "应用 {app_name} 有什么用？{description}"
"应用 {app_name} 有什么用？{description}"
) )
prompt_template_en = ( prompt_template_en = (
"{name}：Call this resource to interact with the application {app_name} ." "{name}：Call this resource to interact with the application {app_name} ."
@ -102,9 +124,7 @@ class AppResource(Resource[AppResourceParameters]):
return ( return (
template.format( template.format(
name=self.name, name=self.name, app_name=self._app_name, description=self._app_desc
app_name=self._app_name,
description=self._app_desc
), ),
None, None,
) )
@ -114,15 +134,16 @@ class AppResource(Resource[AppResourceParameters]):
"""Return whether the tool is asynchronous.""" """Return whether the tool is asynchronous."""
return True return True
async def execute(self, *args, resource_name: Optional[str] = None, **kwargs) -> Any: def execute(self, *args, resource_name: Optional[str] = None, **kwargs) -> Any:
"""Execute the resource."""
if self.is_async: if self.is_async:
raise RuntimeError("Async execution is not supported") raise RuntimeError("Sync execution is not supported")
async def async_execute( async def async_execute(
self, self,
*args, *args,
resource_name: Optional[str] = None, resource_name: Optional[str] = None,
**kwargs, **kwargs,
) -> Any: ) -> Any:
"""Execute the tool asynchronously. """Execute the tool asynchronously.
@ -132,35 +153,41 @@ class AppResource(Resource[AppResourceParameters]):
specific tool). specific tool).
**kwargs: The keyword arguments. **kwargs: The keyword arguments.
""" """
user_input: Optional[str] = kwargs.get("user_input")
parent_agent: Optional[ConversableAgent] = kwargs.get("parent_agent")
user_input = kwargs.get("user_input") if user_input is None:
parent_agent = kwargs.get("parent_agent") raise RuntimeError("AppResource async execution user_input is None")
if parent_agent is None:
raise RuntimeError("AppResource async execution parent_agent is None")
reply_message = await self.chat_2_app_once(self._app_code, user_input=user_input, sender=parent_agent) reply_message = await _start_app(self._app_code, user_input, parent_agent)
return reply_message.content return reply_message.content
async def chat_2_app_once(self,
app_code: str,
user_input: str,
conv_uid: str = None,
sender: ConversableAgent = None) -> AgentMessage:
# create a new conv_uid
conv_uid = str(uuid.uuid4()) if conv_uid is None else conv_uid
gpts_app = get_app_manager().get_app(app_code) async def _start_app(
app_code: str,
user_input: str,
sender: ConversableAgent,
conv_uid: Optional[str] = None,
) -> AgentMessage:
"""Start App By AppResource."""
conv_uid = str(uuid.uuid4()) if conv_uid is None else conv_uid
gpts_app = get_app_manager().get_app(app_code)
app_agent = await get_app_manager().create_agent_by_app_code(
gpts_app, conv_uid=conv_uid
)
app_agent = await get_app_manager().create_agent_by_app_code(gpts_app, conv_uid=conv_uid) agent_message = AgentMessage(
content=user_input,
current_goal=user_input,
context={
"conv_uid": conv_uid,
},
rounds=0,
)
reply_message: AgentMessage = await app_agent.generate_reply(
received_message=agent_message, sender=sender
)
agent_message = AgentMessage( return reply_message
content=user_input,
current_goal=user_input,
context={
"conv_uid": conv_uid,
},
rounds=0,
)
reply_message: AgentMessage = await app_agent.generate_reply(received_message=agent_message,
sender=sender)
return reply_message

2
dbgpt/app/component_configs.py
View File

@ -106,12 +106,12 @@ def _initialize_resource_manager(system_app: SystemApp):
get_current_host_system_load, get_current_host_system_load,
) )
from dbgpt.agent.expand.resources.search_tool import baidu_search from dbgpt.agent.expand.resources.search_tool import baidu_search
from dbgpt.agent.resource.app import AppResource
from dbgpt.agent.resource.base import ResourceType from dbgpt.agent.resource.base import ResourceType
from dbgpt.agent.resource.manage import get_resource_manager, initialize_resource from dbgpt.agent.resource.manage import get_resource_manager, initialize_resource
from dbgpt.serve.agent.resource.datasource import DatasourceResource from dbgpt.serve.agent.resource.datasource import DatasourceResource
from dbgpt.serve.agent.resource.knowledge import KnowledgeSpaceRetrieverResource from dbgpt.serve.agent.resource.knowledge import KnowledgeSpaceRetrieverResource
from dbgpt.serve.agent.resource.plugin import PluginToolPack from dbgpt.serve.agent.resource.plugin import PluginToolPack
from dbgpt.agent.resource.app import AppResource
initialize_resource(system_app) initialize_resource(system_app)
rm = get_resource_manager(system_app) rm = get_resource_manager(system_app)

137
dbgpt/serve/agent/agents/app_agent_manage.py
View File

@ -6,28 +6,29 @@ from typing import List, Type
from dbgpt.agent import ( from dbgpt.agent import (
AgentContext, AgentContext,
AgentMemory, AgentMemory,
AutoPlanChatManager,
ConversableAgent, ConversableAgent,
DefaultAWELLayoutManager, DefaultAWELLayoutManager,
GptsMemory, GptsMemory,
LLMConfig, LLMConfig,
UserProxyAgent, get_agent_manager, UserProxyAgent,
get_agent_manager,
) )
from dbgpt.agent.core.schema import Status from dbgpt.agent.core.schema import Status
from dbgpt.agent.resource import get_resource_manager from dbgpt.agent.resource import get_resource_manager
from dbgpt.agent.util.llm.llm import LLMStrategyType from dbgpt.agent.util.llm.llm import LLMStrategyType
from dbgpt.app.component_configs import CFG from dbgpt.app.component_configs import CFG
from dbgpt.component import BaseComponent, ComponentType, SystemApp from dbgpt.component import BaseComponent, ComponentType, SystemApp
from dbgpt.core import LLMClient from dbgpt.core import LLMClient, PromptTemplate
from dbgpt.core import PromptTemplate
from dbgpt.model.cluster import WorkerManagerFactory from dbgpt.model.cluster import WorkerManagerFactory
from dbgpt.model.cluster.client import DefaultLLMClient from dbgpt.model.cluster.client import DefaultLLMClient
from dbgpt.serve.prompt.api.endpoints import get_service from dbgpt.serve.prompt.api.endpoints import get_service
from .db_gpts_memory import MetaDbGptsMessageMemory, MetaDbGptsPlansMemory
from ..db import GptsMessagesDao from ..db import GptsMessagesDao
from ..db.gpts_app import GptsApp, GptsAppDao, GptsAppQuery from ..db.gpts_app import GptsApp, GptsAppDao, GptsAppDetail, GptsAppQuery
from ..db.gpts_app import GptsAppDetail
from ..db.gpts_conversations_db import GptsConversationsDao from ..db.gpts_conversations_db import GptsConversationsDao
from ..team.base import TeamMode from ..team.base import TeamMode
from .db_gpts_memory import MetaDbGptsMessageMemory, MetaDbGptsPlansMemory
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -63,16 +64,16 @@ class AppManager(BaseComponent, ABC):
return self.gpts_app.app_detail(app_code) return self.gpts_app.app_detail(app_code)
async def user_chat_2_app( async def user_chat_2_app(
self, self,
user_query: str, user_query: str,
conv_uid: str, conv_uid: str,
gpts_app: GptsApp, gpts_app: GptsApp,
agent_memory: AgentMemory, agent_memory: AgentMemory,
is_retry_chat: bool = False, is_retry_chat: bool = False,
last_speaker_name: str = None, last_speaker_name: str = None,
init_message_rounds: int = 0, init_message_rounds: int = 0,
enable_verbose: bool = True, enable_verbose: bool = True,
**ext_info, **ext_info,
) -> Status: ) -> Status:
context: AgentContext = AgentContext( context: AgentContext = AgentContext(
conv_id=conv_uid, conv_id=conv_uid,
@ -107,41 +108,41 @@ class AppManager(BaseComponent, ABC):
return Status.COMPLETE return Status.COMPLETE
async def create_app_agent( async def create_app_agent(
self, self,
gpts_app: GptsApp, gpts_app: GptsApp,
agent_memory: AgentMemory, agent_memory: AgentMemory,
context: AgentContext, context: AgentContext,
) -> ConversableAgent: ) -> ConversableAgent:
# init default llm provider # init default llm provider
llm_provider = DefaultLLMClient( llm_provider = DefaultLLMClient(
self.system_app.get_component(ComponentType.WORKER_MANAGER_FACTORY, WorkerManagerFactory).create(), self.system_app.get_component(
auto_convert_message=True ComponentType.WORKER_MANAGER_FACTORY, WorkerManagerFactory
).create(),
auto_convert_message=True,
) )
# init team employees # init team employees
# TODO employee has it own llm provider # TODO employee has it own llm provider
employees: List[ConversableAgent] = [] employees: List[ConversableAgent] = []
for record in gpts_app.details: for record in gpts_app.details:
agent = (await create_agent_from_gpt_detail(record, llm_provider, context, agent_memory)) agent = await create_agent_from_gpt_detail(
record, llm_provider, context, agent_memory
)
agent.name_prefix = gpts_app.app_name agent.name_prefix = gpts_app.app_name
employees.append(agent) employees.append(agent)
app_agent: ConversableAgent = ( app_agent: ConversableAgent = await create_agent_of_gpts_app(
await create_agent_of_gpts_app(gpts_app, gpts_app, llm_provider, context, agent_memory, employees
llm_provider,
context,
agent_memory,
employees)
) )
app_agent.name_prefix = gpts_app.app_name app_agent.name_prefix = gpts_app.app_name
return app_agent return app_agent
async def create_agent_by_app_code( async def create_agent_by_app_code(
self, self,
gpts_app: GptsApp, gpts_app: GptsApp,
conv_uid: str = None, conv_uid: str = None,
agent_memory: AgentMemory = None, agent_memory: AgentMemory = None,
context: AgentContext = None, context: AgentContext = None,
) -> ConversableAgent: ) -> ConversableAgent:
""" """
Create a conversable agent by application code. Create a conversable agent by application code.
@ -157,7 +158,10 @@ class AppManager(BaseComponent, ABC):
""" """
conv_uid = str(uuid.uuid4()) if conv_uid is None else conv_uid conv_uid = str(uuid.uuid4()) if conv_uid is None else conv_uid
from dbgpt.agent.core.memory.gpts import DefaultGptsPlansMemory, DefaultGptsMessageMemory from dbgpt.agent.core.memory.gpts import (
DefaultGptsMessageMemory,
DefaultGptsPlansMemory,
)
if agent_memory is None: if agent_memory is None:
gpt_memory = GptsMemory( gpt_memory = GptsMemory(
@ -179,24 +183,23 @@ class AppManager(BaseComponent, ABC):
context.gpts_app_name = gpts_app.app_name context.gpts_app_name = gpts_app.app_name
context.language = gpts_app.language context.language = gpts_app.language
agent: ConversableAgent = ( agent: ConversableAgent = await self.create_app_agent(
await self.create_app_agent(gpts_app, agent_memory, context) gpts_app, agent_memory, context
) )
return agent return agent
async def create_agent_from_gpt_detail( async def create_agent_from_gpt_detail(
record: GptsAppDetail, record: GptsAppDetail,
llm_client: LLMClient, llm_client: LLMClient,
agent_context: AgentContext, agent_context: AgentContext,
agent_memory: AgentMemory) -> ConversableAgent: agent_memory: AgentMemory,
) -> ConversableAgent:
""" """
Get the agent object from the GPTsAppDetail object. Get the agent object from the GPTsAppDetail object.
""" """
agent_manager = get_agent_manager() agent_manager = get_agent_manager()
agent_cls: Type[ConversableAgent] = agent_manager.get_by_name( agent_cls: Type[ConversableAgent] = agent_manager.get_by_name(record.agent_name)
record.agent_name
)
llm_config = LLMConfig( llm_config = LLMConfig(
llm_client=llm_client, llm_client=llm_client,
llm_strategy=LLMStrategyType(record.llm_strategy), llm_strategy=LLMStrategyType(record.llm_strategy),
@ -208,25 +211,29 @@ async def create_agent_from_gpt_detail(
prompt_code=record.prompt_template prompt_code=record.prompt_template
) )
depend_resource = get_resource_manager().build_resource(record.resources, version="v1") depend_resource = get_resource_manager().build_resource(
record.resources, version="v1"
)
agent = (await agent_cls() agent = (
.bind(agent_context) await agent_cls()
.bind(agent_memory) .bind(agent_context)
.bind(llm_config) .bind(agent_memory)
.bind(depend_resource) .bind(llm_config)
.bind(prompt_template) .bind(depend_resource)
.build()) .bind(prompt_template)
.build()
)
return agent return agent
async def create_agent_of_gpts_app( async def create_agent_of_gpts_app(
gpts_app: GptsApp, gpts_app: GptsApp,
llm_client: LLMClient, llm_client: LLMClient,
context: AgentContext, context: AgentContext,
memory: AgentMemory, memory: AgentMemory,
employees: List[ConversableAgent], employees: List[ConversableAgent],
) -> ConversableAgent: ) -> ConversableAgent:
llm_config = LLMConfig( llm_config = LLMConfig(
llm_client=llm_client, llm_client=llm_client,
@ -240,13 +247,10 @@ async def create_agent_of_gpts_app(
agent_of_app: ConversableAgent = employees[0] agent_of_app: ConversableAgent = employees[0]
else: else:
if TeamMode.AUTO_PLAN == team_mode: if TeamMode.AUTO_PLAN == team_mode:
if not employees or len(employees) < 0: if not gpts_app.details or len(gpts_app.details) < 0:
raise ValueError("APP exception no available agent！") raise ValueError("APP exception no available agent！")
from dbgpt.agent.v2 import AutoPlanChatManagerV2, MultiAgentTeamPlanner llm_config = employees[0].llm_config
planner = MultiAgentTeamPlanner() manager = AutoPlanChatManager()
planner.name_prefix = gpts_app.app_name
manager = AutoPlanChatManagerV2(planner)
manager.name_prefix = gpts_app.app_name
elif TeamMode.AWEL_LAYOUT == team_mode: elif TeamMode.AWEL_LAYOUT == team_mode:
if not awel_team_context: if not awel_team_context:
raise ValueError( raise ValueError(
@ -257,12 +261,7 @@ async def create_agent_of_gpts_app(
raise ValueError(f"Native APP chat not supported!") raise ValueError(f"Native APP chat not supported!")
else: else:
raise ValueError(f"Unknown Agent Team Mode!{team_mode}") raise ValueError(f"Unknown Agent Team Mode!{team_mode}")
manager = ( manager = await manager.bind(context).bind(memory).bind(llm_config).build()
await manager.bind(context)
.bind(memory)
.bind(llm_config)
.build()
)
manager.hire(employees) manager.hire(employees)
agent_of_app: ConversableAgent = manager agent_of_app: ConversableAgent = manager

5
dbgpt/serve/agent/agents/expand/__init__.py
View File

@ -1,6 +1,7 @@
from dbgpt.serve.agent.agents.expand.app_resource_start_assisant_agent import AppStarterAgent from dbgpt.serve.agent.agents.expand.app_resource_start_assisant_agent import (
AppStarterAgent,
)
__all__ = [ __all__ = [
"AppStarterAgent", "AppStarterAgent",
] ]

66
dbgpt/serve/agent/agents/expand/app_resource_start_assisant_agent.py
View File

@ -1,13 +1,17 @@
import json import json
import logging import logging
from typing import Any, Dict, List from typing import Any, Dict, List, Optional
from typing import Optional
from dbgpt._private.pydantic import BaseModel, Field from dbgpt._private.pydantic import BaseModel, Field
from dbgpt.agent import Action, ActionOutput, AgentResource, AgentMessage, ResourceType
from dbgpt.agent import ( from dbgpt.agent import (
Action,
ActionOutput,
Agent, Agent,
AgentMessage,
AgentResource,
ConversableAgent, ConversableAgent,
Resource,
ResourceType,
get_agent_manager, get_agent_manager,
) )
from dbgpt.agent.core.profile import DynConfig, ProfileConfig from dbgpt.agent.core.profile import DynConfig, ProfileConfig
@ -23,7 +27,7 @@ class AppResourceInput(BaseModel):
app_name: str = Field( app_name: str = Field(
..., ...,
description="The name of a application that can be used to answer the current question" description="The name of a application that can be used to answer the current question"
" or solve the current task.", " or solve the current task.",
) )
app_query: str = Field( app_query: str = Field(
@ -60,7 +64,7 @@ class AppResourceAction(Action[AppResourceInput]):
"""Return the AI output schema.""" """Return the AI output schema."""
out_put_schema = { out_put_schema = {
"app_name": "the agent name you selected", "app_name": "the agent name you selected",
"app_query": "the query to the selected agent, must input a str, base on the natural language " "app_query": "the query to the selected agent, must input a str, base on the natural language ",
} }
return f"""Please response in the following json format: return f"""Please response in the following json format:
@ -69,12 +73,12 @@ class AppResourceAction(Action[AppResourceInput]):
""" """
async def run( async def run(
self, self,
ai_message: str, ai_message: str,
resource: Optional[AgentResource] = None, resource: Optional[AgentResource] = None,
rely_action_out: Optional[ActionOutput] = None, rely_action_out: Optional[ActionOutput] = None,
need_vis_render: bool = True, need_vis_render: bool = True,
**kwargs, **kwargs,
) -> ActionOutput: ) -> ActionOutput:
"""Perform the plugin action. """Perform the plugin action.
@ -92,7 +96,9 @@ class AppResourceAction(Action[AppResourceInput]):
err_msg = None err_msg = None
app_result = None app_result = None
try: try:
param: AppResourceInput = self._input_convert(ai_message, AppResourceInput) param: AppResourceInput = self._input_convert(
ai_message, AppResourceInput
)
except Exception as e: except Exception as e:
logger.exception((str(e))) logger.exception((str(e)))
return ActionOutput( return ActionOutput(
@ -126,7 +132,9 @@ class AppResourceAction(Action[AppResourceInput]):
is_exe_success=False, content=f"App action run failed!{str(e)}" is_exe_success=False, content=f"App action run failed!{str(e)}"
) )
async def __get_plugin_view(self, param: AppResourceInput, app_result: Any, err_msg: str): async def __get_plugin_view(
self, param: AppResourceInput, app_result: Any, err_msg: str
):
if not self.render_protocol: if not self.render_protocol:
return None return None
# raise NotImplementedError("The render_protocol should be implemented.") # raise NotImplementedError("The render_protocol should be implemented.")
@ -181,11 +189,8 @@ class AppStarterAgent(ConversableAgent):
constraints=DynConfig( constraints=DynConfig(
[ [
"请一步一步思考参为用户问题选择一个最匹配的应用来进行用户问题回答，可参考给出示例的应用选择逻辑.", "请一步一步思考参为用户问题选择一个最匹配的应用来进行用户问题回答，可参考给出示例的应用选择逻辑.",
"请阅读用户问题，确定问题所属领域和问题意图，按领域和意图匹配应用,如果用户问题意图缺少操作类应用需要的参数，优先使用咨询类型应用，有明确操作目标才使用操作类应用.",
"必须从已知的应用中选出一个可用的应用来进行回答，不要瞎编应用的名称", "必须从已知的应用中选出一个可用的应用来进行回答，不要瞎编应用的名称",
"仅选择可回答问题的应用即可，不要直接回答用户问题.", "如果选择出了合适的应用，传递给应用的请求和用户输入的请求中的信息必须完全对等，不能丢失或增加任何信息",
"如果用户的问题和提供的所有应用全都不相关，则应用code和name都输出为空",
"注意应用意图定义中如果有槽位信息，再次阅读理解用户输入信息，将对应的内容填入对应槽位参数定义中.",
], ],
category="agent", category="agent",
key="dbgpt_ant_agent_agents_app_resource_starter_assistant_agent_profile_constraints", key="dbgpt_ant_agent_agents_app_resource_starter_assistant_agent_profile_constraints",
@ -203,11 +208,11 @@ class AppStarterAgent(ConversableAgent):
self._init_actions([AppResourceAction]) self._init_actions([AppResourceAction])
def prepare_act_param( def prepare_act_param(
self, self,
received_message: Optional[AgentMessage], received_message: Optional[AgentMessage],
sender: Agent, sender: Agent,
rely_messages: Optional[List[AgentMessage]] = None, rely_messages: Optional[List[AgentMessage]] = None,
**kwargs, **kwargs,
) -> Dict[str, Any]: ) -> Dict[str, Any]:
return { return {
"user_input": received_message.content, "user_input": received_message.content,
@ -215,6 +220,23 @@ class AppStarterAgent(ConversableAgent):
"parent_agent": self, "parent_agent": self,
} }
@property
def desc(self) -> Optional[str]:
resources: List[AppResource] = get_app_resource_list(self.resource)
return f"根据用户问题匹配合适的应用来进行回答. AppStart下的应用中可以解决下列问题：{[f' {res.app_desc}' for res in resources]}"
def get_app_resource_list(resource: Resource) -> List[AppResource]:
app_resource_list: List[AppResource] = []
if resource.type() == ResourceType.Pack:
for sub_resource in resource.sub_resources:
if sub_resource.type() == ResourceType.App:
app_resource_list.extend(AppResource.from_resource(sub_resource))
if resource.type() == ResourceType.App:
app_resource_list.extend(AppResource.from_resource(resource))
return app_resource_list
agent_manage = get_agent_manager() agent_manage = get_agent_manager()
agent_manage.register_agent(AppStarterAgent) agent_manage.register_agent(AppStarterAgent)