fix(agent): Disable profile generator -> speed up agent setup

autogpt/autogpt/agent_factory/configurators.py

@@ -12,14 +12,15 @@
 def create_agent(
     agent_id: str,
     task: str,
-    ai_profile: AIProfile,
     app_config: Config,
     file_storage: FileStorage,
     llm_provider: MultiProvider,
+    ai_profile: Optional[AIProfile] = None,
     directives: Optional[AIDirectives] = None,
 ) -> Agent:
     if not task:
         raise ValueError("No task specified for new agent")
+    ai_profile = ai_profile or AIProfile()
     directives = directives or AIDirectives()
 
     agent = _configure_agent(

autogpt/autogpt/agent_factory/profile_generator.py

@@ -21,53 +21,48 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration):
     model_classification: LanguageModelClassification = UserConfigurable(
         default=LanguageModelClassification.SMART_MODEL
     )
-    _example_call: object = [
-        {
-            "type": "function",
-            "function": {
-                "name": "create_agent",
-                "arguments": {
-                    "name": "CMOGPT",
-                    "description": (
-                        "a professional digital marketer AI that assists Solopreneurs "
-                        "in growing their businesses by providing "
-                        "world-class expertise in solving marketing problems "
-                        "for SaaS, content products, agencies, and more."
+    _example_call: object = {
+        "name": "create_agent",
+        "arguments": {
+            "name": "CMOGPT",
+            "description": (
+                "a professional digital marketer AI that assists Solopreneurs "
+                "in growing their businesses by providing "
+                "world-class expertise in solving marketing problems "
+                "for SaaS, content products, agencies, and more."
+            ),
+            "directives": {
+                "best_practices": [
+                    (
+                        "Engage in effective problem-solving, prioritization, "
+                        "planning, and supporting execution to address your "
+                        "marketing needs as your virtual "
+                        "Chief Marketing Officer."
                     ),
-                    "directives": {
-                        "best_practices": [
-                            (
-                                "Engage in effective problem-solving, prioritization, "
-                                "planning, and supporting execution to address your "
-                                "marketing needs as your virtual "
-                                "Chief Marketing Officer."
-                            ),
-                            (
-                                "Provide specific, actionable, and concise advice to "
-                                "help you make informed decisions without the use of "
-                                "platitudes or overly wordy explanations."
-                            ),
-                            (
-                                "Identify and prioritize quick wins and cost-effective "
-                                "campaigns that maximize results with minimal time and "
-                                "budget investment."
-                            ),
-                            (
-                                "Proactively take the lead in guiding you and offering "
-                                "suggestions when faced with unclear information or "
-                                "uncertainty to ensure your marketing strategy remains "
-                                "on track."
-                            ),
-                        ],
-                        "constraints": [
-                            "Do not suggest illegal or unethical plans or strategies.",
-                            "Take reasonable budgetary limits into account.",
-                        ],
-                    },
-                },
+                    (
+                        "Provide specific, actionable, and concise advice to "
+                        "help you make informed decisions without the use of "
+                        "platitudes or overly wordy explanations."
+                    ),
+                    (
+                        "Identify and prioritize quick wins and cost-effective "
+                        "campaigns that maximize results with minimal time and "
+                        "budget investment."
+                    ),
+                    (
+                        "Proactively take the lead in guiding you and offering "
+                        "suggestions when faced with unclear information or "
+                        "uncertainty to ensure your marketing strategy remains "
+                        "on track."
+                    ),
+                ],
+                "constraints": [
+                    "Do not suggest illegal or unethical plans or strategies.",
+                    "Take reasonable budgetary limits into account.",
+                ],
             },
-        }
-    ]
+        },
+    }
     system_prompt: str = UserConfigurable(
         default=(
             "Your job is to respond to a user-defined task, given in triple quotes, by "
@@ -192,7 +187,6 @@ def parse_response_content(
 
         Returns:
             The parsed response.
-
         """
         try:
             if not response.tool_calls:

autogpt/autogpt/agents/agent.py

@@ -104,8 +104,6 @@ def __init__(
         super().__init__(settings)
 
         self.llm_provider = llm_provider
-        self.ai_profile = settings.ai_profile
-        self.directives = settings.directives
         prompt_config = OneShotAgentPromptStrategy.default_configuration.copy(deep=True)
         prompt_config.use_functions_api = (
             settings.config.use_functions_api
@@ -116,7 +114,7 @@ def __init__(
         self.commands: list[Command] = []
 
         # Components
-        self.system = SystemComponent(legacy_config, settings.ai_profile)
+        self.system = SystemComponent()
         self.history = ActionHistoryComponent(
             settings.history,
             self.send_token_limit,

autogpt/autogpt/agents/prompt_strategies/one_shot.py

@@ -160,10 +160,7 @@ def build_system_prompt(
             + (self._generate_os_info() if include_os_info else [])
             + [
                 self.config.body_template.format(
-                    constraints=format_numbered_list(
-                        ai_directives.constraints
-                        + self._generate_budget_constraint(ai_profile.api_budget)
-                    ),
+                    constraints=format_numbered_list(ai_directives.constraints),
                     resources=format_numbered_list(ai_directives.resources),
                     commands=self._generate_commands_list(commands),
                     best_practices=format_numbered_list(ai_directives.best_practices),
@@ -237,19 +234,6 @@ def _generate_os_info(self) -> list[str]:
         )
         return [f"The OS you are running on is: {os_info}"]
 
-    def _generate_budget_constraint(self, api_budget: float) -> list[str]:
-        """Generates the budget information part of the prompt.
-
-        Returns:
-            list[str]: The budget information part of the prompt, or an empty list.
-        """
-        if api_budget > 0.0:
-            return [
-                f"It takes money to let you run. "
-                f"Your API budget is ${api_budget:.3f}"
-            ]
-        return []
-
     def _generate_commands_list(self, commands: list[CompletionModelFunction]) -> str:
         """Lists the commands available to the agent.
 

autogpt/autogpt/app/agent_protocol_server.py

@@ -33,8 +33,7 @@
 from hypercorn.config import Config as HypercornConfig
 from sentry_sdk import set_user
 
-from autogpt.agent_factory.configurators import configure_agent_with_state
-from autogpt.agent_factory.generators import generate_agent_for_task
+from autogpt.agent_factory.configurators import configure_agent_with_state, create_agent
 from autogpt.agents.agent_manager import AgentManager
 from autogpt.app.utils import is_port_free
 
@@ -134,8 +133,10 @@
             input=task_request.input,
             additional_input=task_request.additional_input,
         )
-        logger.debug(f"Creating agent for task: '{task.input}'")
-        task_agent = await generate_agent_for_task(
+        # TODO: re-evaluate performance benefit of task-oriented profiles
+        # logger.debug(f"Creating agent for task: '{task.input}'")
+        # task_agent = await generate_agent_for_task(
+        task_agent = create_agent(
             agent_id=task_agent_id(task.task_id),
             task=task.input,
             app_config=self.app_config,

autogpt/autogpt/app/main.py

@@ -19,6 +19,7 @@
     is_docker_available,
     we_are_running_in_a_docker_container,
 )
+from forge.config.ai_directives import AIDirectives
 from forge.config.ai_profile import AIProfile
 from forge.config.config import Config, ConfigBuilder, assert_config_has_openai_api_key
 from forge.file_storage import FileStorageBackendName, get_storage
@@ -31,7 +32,6 @@
 from forge.utils.exceptions import AgentTerminated, InvalidAgentResponseError
 
 from autogpt.agent_factory.configurators import configure_agent_with_state, create_agent
-from autogpt.agent_factory.profile_generator import generate_agent_profile_for_task
 from autogpt.agents.agent_manager import AgentManager
 from autogpt.agents.prompt_strategies.one_shot import AssistantThoughts
 
@@ -260,15 +260,11 @@
                 " with as much detail as possible:",
             )
 
-        ai_profile, task_oriented_ai_directives = await generate_agent_profile_for_task(
-            task,
-            app_config=config,
-            llm_provider=llm_provider,
-        )
-        ai_directives = task_oriented_ai_directives
+        ai_profile = AIProfile()
+        additional_ai_directives = AIDirectives()
         apply_overrides_to_ai_settings(
             ai_profile=ai_profile,
-            directives=ai_directives,
+            directives=additional_ai_directives,
             override_name=override_ai_name,
             override_role=override_ai_role,
             resources=resources,
@@ -288,9 +284,12 @@
                 best_practices,
             ]
         ):
-            ai_profile, ai_directives = await interactively_revise_ai_settings(
+            (
+                ai_profile,
+                additional_ai_directives,
+            ) = await interactively_revise_ai_settings(
                 ai_profile=ai_profile,
-                directives=ai_directives,
+                directives=additional_ai_directives,
                 app_config=config,
             )
         else:
@@ -300,7 +299,7 @@
             agent_id=agent_manager.generate_id(ai_profile.ai_name),
             task=task,
             ai_profile=ai_profile,
-            directives=ai_directives,
+            directives=additional_ai_directives,
             app_config=config,
             file_storage=file_storage,
             llm_provider=llm_provider,
@@ -316,6 +315,22 @@
                 extra={"preserve_color": True},
             )
 
+        # TODO: re-evaluate performance benefit of task-oriented profiles
+        # # Concurrently generate a custom profile for the agent and apply it once done
+        # def update_agent_directives(
+        #     task: asyncio.Task[tuple[AIProfile, AIDirectives]]
+        # ):
+        #     logger.debug(f"Updating AIProfile: {task.result()[0]}")
+        #     logger.debug(f"Adding AIDirectives: {task.result()[1]}")
+        #     agent.state.ai_profile = task.result()[0]
+        #     agent.state.directives = agent.state.directives + task.result()[1]
+
+        # asyncio.create_task(
+        #     generate_agent_profile_for_task(
+        #         task, app_config=config, llm_provider=llm_provider
+        #     )
+        # ).add_done_callback(update_agent_directives)
+
     #################
     # Run the Agent #
     #################
@@ -445,7 +460,7 @@
     """
     # These contain both application config and agent config, so grab them here.
     legacy_config = agent.legacy_config
-    ai_profile = agent.ai_profile
+    ai_profile = agent.state.ai_profile
     logger = logging.getLogger(__name__)
 
     cycle_budget = cycles_remaining = _get_cycle_budget(

forge/forge/components/system/system.py

@@ -4,8 +4,6 @@
 
 from forge.agent.protocols import CommandProvider, DirectiveProvider, MessageProvider
 from forge.command import Command, command
-from forge.config.ai_profile import AIProfile
-from forge.config.config import Config
 from forge.llm.providers import ChatMessage
 from forge.models.json_schema import JSONSchema
 from forge.utils.const import FINISH_COMMAND
@@ -17,16 +15,7 @@
 class SystemComponent(DirectiveProvider, MessageProvider, CommandProvider):
     """Component for system messages and commands."""
 
-    def __init__(self, config: Config, profile: AIProfile):
-        self.legacy_config = config
-        self.profile = profile
-
     def get_constraints(self) -> Iterator[str]:
-        if self.profile.api_budget > 0.0:
-            yield (
-                f"It takes money to let you run. "
-                f"Your API budget is ${self.profile.api_budget:.3f}"
-            )
         yield "Exclusively use the commands listed below."
         yield (
             "You can only act proactively, and are unable to start background jobs or "

forge/forge/config/ai_profile.py

@@ -1,5 +1,14 @@
 from pydantic import BaseModel, Field
 
+DEFAULT_AI_NAME = "AutoGPT"
+DEFAULT_AI_ROLE = (
+    "a seasoned digital assistant: "
+    "capable, intelligent, considerate and assertive. "
+    "You have extensive research and development skills, and you don't shy "
+    "away from writing some code to solve a problem. "
+    "You are pragmatic and make the most out of the tools available to you."
+)
+
 
 class AIProfile(BaseModel):
     """
@@ -12,7 +21,7 @@ class AIProfile(BaseModel):
         api_budget (float): The maximum dollar value for API calls (0.0 means infinite)
     """
 
-    ai_name: str = ""
-    ai_role: str = ""
+    ai_name: str = DEFAULT_AI_NAME
+    ai_role: str = DEFAULT_AI_ROLE
+    """`ai_role` should fit in the following format: `You are {ai_name}, {ai_role}`"""
     ai_goals: list[str] = Field(default_factory=list[str])
-    api_budget: float = 0.0