mirror of
https://github.com/csunny/DB-GPT.git
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refactor(agent): Refactor resource of agents (#1518)
This commit is contained in:
Fangyin Cheng
GitHub
@@ -3,16 +3,17 @@
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import asyncio
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import json
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import logging
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from typing import Any, Dict, List, Optional, Tuple, Type, cast
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from concurrent.futures import Executor, ThreadPoolExecutor
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from typing import Any, Callable, Dict, List, Optional, Tuple, Type, cast
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from dbgpt._private.pydantic import ConfigDict, Field
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from dbgpt.core import LLMClient, ModelMessageRoleType
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from dbgpt.util.error_types import LLMChatError
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from dbgpt.util.executor_utils import blocking_func_to_async
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from dbgpt.util.tracer import SpanType, root_tracer
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from dbgpt.util.utils import colored
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from ..resource.resource_api import AgentResource, ResourceClient
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from ..resource.resource_loader import ResourceLoader
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from ..resource.base import Resource
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from ..util.llm.llm import LLMConfig, LLMStrategyType
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from ..util.llm.llm_client import AIWrapper
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from .action.base import Action, ActionOutput
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@@ -32,12 +33,15 @@ class ConversableAgent(Role, Agent):
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agent_context: Optional[AgentContext] = Field(None, description="Agent context")
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actions: List[Action] = Field(default_factory=list)
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resources: List[AgentResource] = Field(default_factory=list)
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resource: Optional[Resource] = Field(None, description="Resource")
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llm_config: Optional[LLMConfig] = None
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resource_loader: Optional[ResourceLoader] = None
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max_retry_count: int = 3
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consecutive_auto_reply_counter: int = 0
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llm_client: Optional[AIWrapper] = None
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executor: Executor = Field(
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default_factory=lambda: ThreadPoolExecutor(max_workers=1),
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description="Executor for running tasks",
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)
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def __init__(self, **kwargs):
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"""Create a new agent."""
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@@ -58,27 +62,12 @@ class ConversableAgent(Role, Agent):
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f"running!"
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)
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# resource check
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for resource in self.resources:
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if (
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self.resource_loader is None
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or self.resource_loader.get_resource_api(
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resource.type, check_instance=False
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)
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is None
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):
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raise ValueError(
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f"Resource {resource.type}:{resource.value} missing resource loader"
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f" implementation,unable to read resources!"
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)
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# action check
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if self.actions and len(self.actions) > 0:
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have_resource_types = [item.type for item in self.resources]
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for action in self.actions:
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if (
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action.resource_need
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and action.resource_need not in have_resource_types
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if action.resource_need and (
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not self.resource
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or not self.resource.get_resource_by_type(action.resource_need)
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):
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raise ValueError(
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f"{self.name}[{self.role}] Missing resources required for "
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@@ -112,13 +101,6 @@ class ConversableAgent(Role, Agent):
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raise ValueError("Agent context is not initialized！")
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return self.agent_context
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@property
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def not_null_resource_loader(self) -> ResourceLoader:
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"""Get the resource loader."""
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if not self.resource_loader:
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raise ValueError("Resource loader is not initialized！")
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return self.resource_loader
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@property
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def not_null_llm_config(self) -> LLMConfig:
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"""Get the LLM config."""
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@@ -134,23 +116,32 @@ class ConversableAgent(Role, Agent):
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raise ValueError("LLM client is not initialized！")
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return llm_client
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async def blocking_func_to_async(
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self, func: Callable[..., Any], *args, **kwargs
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) -> Any:
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"""Run a potentially blocking function within an executor."""
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if not asyncio.iscoroutinefunction(func):
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return await blocking_func_to_async(self.executor, func, *args, **kwargs)
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return await func(*args, **kwargs)
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async def preload_resource(self) -> None:
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"""Preload resources before agent initialization."""
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pass
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if self.resource:
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await self.blocking_func_to_async(self.resource.preload_resource)
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async def build(self) -> "ConversableAgent":
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"""Build the agent."""
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# Preload resources
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await self.preload_resource()
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# Check if agent is available
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self.check_available()
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_language = self.not_null_agent_context.language
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if _language:
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self.language = _language
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# Preload resources
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await self.preload_resource()
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# Initialize resource loader
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for action in self.actions:
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action.init_resource_loader(self.resource_loader)
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action.init_resource(self.resource)
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# Initialize LLM Server
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if not self.is_human:
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@@ -175,13 +166,8 @@ class ConversableAgent(Role, Agent):
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raise ValueError("GptsMemory is not supported!")
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elif isinstance(target, AgentContext):
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self.agent_context = target
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elif isinstance(target, ResourceLoader):
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self.resource_loader = target
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elif isinstance(target, list) and target and len(target) > 0:
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if _is_list_of_type(target, Action):
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self.actions.extend(target)
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elif _is_list_of_type(target, AgentResource):
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self.resources = target
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elif isinstance(target, Resource):
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self.resource = target
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elif isinstance(target, AgentMemory):
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self.memory = target
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return self
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@@ -480,12 +466,12 @@ class ConversableAgent(Role, Agent):
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last_out: Optional[ActionOutput] = None
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for i, action in enumerate(self.actions):
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# Select the resources required by acton
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need_resource = None
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if self.resources and len(self.resources) > 0:
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for item in self.resources:
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if item.type == action.resource_need:
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need_resource = item
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break
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if action.resource_need and self.resource:
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need_resources = self.resource.get_resource_by_type(
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action.resource_need
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)
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else:
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need_resources = []
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if not message:
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raise ValueError("The message content is empty!")
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@@ -497,7 +483,7 @@ class ConversableAgent(Role, Agent):
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"sender": sender.name if sender else None,
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"recipient": self.name,
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"reviewer": reviewer.name if reviewer else None,
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"need_resource": need_resource.to_dict() if need_resource else None,
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"need_resource": need_resources[0].name if need_resources else None,
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"rely_action_out": last_out.to_dict() if last_out else None,
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"conv_uid": self.not_null_agent_context.conv_id,
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"action_index": i,
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@@ -506,7 +492,7 @@ class ConversableAgent(Role, Agent):
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) as span:
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last_out = await action.run(
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ai_message=message,
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resource=need_resource,
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resource=None,
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rely_action_out=last_out,
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**kwargs,
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)
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@@ -703,23 +689,11 @@ class ConversableAgent(Role, Agent):
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self, question: Optional[str] = None
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) -> Dict[str, Any]:
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"""Generate the resource variables."""
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resource_prompt_list = []
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for item in self.resources:
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resource_client = self.not_null_resource_loader.get_resource_api(
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item.type, ResourceClient
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resource_prompt = None
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if self.resource:
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resource_prompt = await self.resource.get_prompt(
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lang=self.language, question=question
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)
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if not resource_client:
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raise ValueError(
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f"Resource {item.type}:{item.value} missing resource loader"
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f" implementation,unable to read resources!"
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)
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resource_prompt_list.append(
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await resource_client.get_resource_prompt(item, question)
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)
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resource_prompt = ""
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if len(resource_prompt_list) > 0:
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resource_prompt = "RESOURCES:" + "\n".join(resource_prompt_list)
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out_schema: Optional[str] = ""
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if self.actions and len(self.actions) > 0:
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