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from typing import Optional
from autogpt.agents.agent import Agent, AgentConfiguration, AgentSettings
from autogpt.config import AIDirectives, AIProfile, Config
from autogpt.core.resource.model_providers import ChatModelProvider
from autogpt.file_storage.base import FileStorage
from autogpt.logs.config import configure_chat_plugins
from autogpt.plugins import scan_plugins
def create_agent(
agent_id: str,
task: str,
ai_profile: AIProfile,
app_config: Config,
file_storage: FileStorage,
llm_provider: ChatModelProvider,
directives: Optional[AIDirectives] = None,
) -> Agent:
if not task:
raise ValueError("No task specified for new agent")
if not directives:
directives = AIDirectives.from_file(app_config.prompt_settings_file)
agent = _configure_agent(
agent_id=agent_id,
task=task,
ai_profile=ai_profile,
directives=directives,
app_config=app_config,
file_storage=file_storage,
llm_provider=llm_provider,
)
return agent
def configure_agent_with_state(
state: AgentSettings,
app_config: Config,
file_storage: FileStorage,
llm_provider: ChatModelProvider,
) -> Agent:
return _configure_agent(
state=state,
app_config=app_config,
file_storage=file_storage,
llm_provider=llm_provider,
)
def _configure_agent(
app_config: Config,
llm_provider: ChatModelProvider,
file_storage: FileStorage,
agent_id: str = "",
task: str = "",
ai_profile: Optional[AIProfile] = None,
directives: Optional[AIDirectives] = None,
state: Optional[AgentSettings] = None,
) -> Agent:
if not (state or agent_id and task and ai_profile and directives):
raise TypeError(
"Either (state) or (agent_id, task, ai_profile, directives)"
" must be specified"
)
app_config.plugins = scan_plugins(app_config)
configure_chat_plugins(app_config)
agent_state = state or create_agent_state(
agent_id=agent_id,
task=task,
ai_profile=ai_profile,
directives=directives,
app_config=app_config,
)
# TODO: configure memory
return Agent(
settings=agent_state,
llm_provider=llm_provider,
file_storage=file_storage,
legacy_config=app_config,
)
def create_agent_state(
agent_id: str,
task: str,
ai_profile: AIProfile,
directives: AIDirectives,
app_config: Config,
) -> AgentSettings:
return AgentSettings(
agent_id=agent_id,
name=Agent.default_settings.name,
description=Agent.default_settings.description,
task=task,
ai_profile=ai_profile,
directives=directives,
config=AgentConfiguration(
fast_llm=app_config.fast_llm,
smart_llm=app_config.smart_llm,
allow_fs_access=not app_config.restrict_to_workspace,
use_functions_api=app_config.openai_functions,
plugins=app_config.plugins,
),
history=Agent.default_settings.history.copy(deep=True),
)
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