github/DB-GPT
1
0
Fork 0
mirror of https://github.com/csunny/DB-GPT.git synced 2025-09-10 05:19:44 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat:deepsearch v1

Browse Source
This commit is contained in:
aries_ckt
2025-07-17 20:00:40 +08:00
parent 74850cbe09
commit e218aa952e
2 changed files with 55 additions and 41 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
packages/dbgpt-core/src/dbgpt/agent/expand/actions/deep_search_action.py
View File

@@ -55,8 +55,8 @@ class ReflectionModel(BaseModel):
default_factory=list, default_factory=list,
description="List of tools to be used in the action.", description="List of tools to be used in the action.",
) )
thought: str = Field( thought: Optional[str] = Field(
..., None,
description="The thought of the current action, describing what you want to achieve.", description="The thought of the current action, describing what you want to achieve.",
) )
@@ -102,7 +102,12 @@ class DeepSearchAction(ToolAction):
) -> ActionOutput: ) -> ActionOutput:
"""Perform the action.""" """Perform the action."""
try: try:
# state = "split_query" if self.state == "summarize":
return ActionOutput(
is_exe_success=True,
content=ai_message,
view=ai_message,
)
action_param: ReflectionModel = self._input_convert( action_param: ReflectionModel = self._input_convert(
ai_message, ReflectionModel ai_message, ReflectionModel
) )
@@ -115,6 +120,7 @@ class DeepSearchAction(ToolAction):
sub_queries = action_param.sub_queries sub_queries = action_param.sub_queries
if action_param.status == "summarize": if action_param.status == "summarize":
self.state = "summarize"
return ActionOutput( return ActionOutput(
is_exe_success=True, is_exe_success=True,
content=action_param.thought, content=action_param.thought,

84
packages/dbgpt-core/src/dbgpt/agent/expand/deep_search.py
View File

@@ -13,7 +13,7 @@ from dbgpt.agent import (
ProfileConfig, ProfileConfig,
Resource, Resource,
ResourceType, ResourceType,
StructuredAgentMemoryFragment, StructuredAgentMemoryFragment, BlankAction,
) )
from dbgpt.agent.core.role import AgentRunMode from dbgpt.agent.core.role import AgentRunMode
from dbgpt.agent.resource import BaseTool, ResourcePack, ToolPack from dbgpt.agent.resource import BaseTool, ResourcePack, ToolPack
@@ -214,7 +214,7 @@ class DeepSearchAgent(ConversableAgent):
"""Init indicator AssistantAgent.""" """Init indicator AssistantAgent."""
super().__init__(**kwargs) super().__init__(**kwargs)
self._init_actions([DeepSearchAction]) self._init_actions([DeepSearchAction, BlankAction])
async def preload_resource(self) -> None: async def preload_resource(self) -> None:
await super().preload_resource() await super().preload_resource()
@@ -294,41 +294,41 @@ class DeepSearchAgent(ConversableAgent):
return json.dumps(abilities, ensure_ascii=False), [] return json.dumps(abilities, ensure_ascii=False), []
async def build_system_prompt( # async def build_system_prompt(
self, # self,
question: Optional[str] = None, # question: Optional[str] = None,
most_recent_memories: Optional[str] = None, # most_recent_memories: Optional[str] = None,
resource_vars: Optional[Dict] = None, # resource_vars: Optional[Dict] = None,
context: Optional[Dict[str, Any]] = None, # context: Optional[Dict[str, Any]] = None,
is_retry_chat: bool = False, # is_retry_chat: bool = False,
): # ):
"""Build system prompt.""" # """Build system prompt."""
system_prompt = None # system_prompt = None
if self.bind_prompt: # if self.bind_prompt:
prompt_param = {} # prompt_param = {}
if resource_vars: # if resource_vars:
prompt_param.update(resource_vars) # prompt_param.update(resource_vars)
if context: # if context:
prompt_param.update(context) # prompt_param.update(context)
if self.bind_prompt.template_format == "f-string": # if self.bind_prompt.template_format == "f-string":
system_prompt = self.bind_prompt.template.format( # system_prompt = self.bind_prompt.template.format(
**prompt_param, # **prompt_param,
) # )
elif self.bind_prompt.template_format == "jinja2": # elif self.bind_prompt.template_format == "jinja2":
system_prompt = Template(self.bind_prompt.template).render(prompt_param) # system_prompt = Template(self.bind_prompt.template).render(prompt_param)
else: # else:
logger.warning("Bind prompt template not exsit or format not support!") # logger.warning("Bind prompt template not exsit or format not support!")
if not system_prompt: # if not system_prompt:
param: Dict = context if context else {} # param: Dict = context if context else {}
system_prompt = await self.build_prompt( # system_prompt = await self.build_prompt(
question=question, # question=question,
is_system=True, # is_system=True,
most_recent_memories=most_recent_memories, # most_recent_memories=most_recent_memories,
resource_vars=resource_vars, # resource_vars=resource_vars,
is_retry_chat=is_retry_chat, # is_retry_chat=is_retry_chat,
**param, # **param,
) # )
return system_prompt # return system_prompt
def prepare_act_param( def prepare_act_param(
self, self,
@@ -376,6 +376,12 @@ class DeepSearchAgent(ConversableAgent):
# ) # )
# if real_action is None: # if real_action is None:
# continue # continue
final_summarize = False
if self.profile.system_prompt_template == _DEEPSEARCH_FINIAL_SUMMARY_TEMPLATE:
if isinstance(action, DeepSearchAction):
continue
else:
final_summarize = True
last_out = await action.run( last_out = await action.run(
ai_message=message.content if message.content else "", ai_message=message.content if message.content else "",
@@ -383,6 +389,7 @@ class DeepSearchAgent(ConversableAgent):
rely_action_out=last_out, rely_action_out=last_out,
**kwargs, **kwargs,
) )
last_out.terminate = final_summarize
if not last_out.terminate: if not last_out.terminate:
self.profile.system_prompt_template = _DEEPSEARCH_FINIAL_SUMMARY_TEMPLATE self.profile.system_prompt_template = _DEEPSEARCH_FINIAL_SUMMARY_TEMPLATE
span.metadata["action_out"] = last_out.to_dict() if last_out else None span.metadata["action_out"] = last_out.to_dict() if last_out else None
@@ -459,5 +466,6 @@ class DeepSearchAgent(ConversableAgent):
# ) # )
# ) # )
return "\n".join([ return "\n".join([
mem_dict.get("observation") for mem_dict in structured_memories mem_dict.get("observation") for mem_dict in structured_memories if mem_dict.get("observation")
]) ])