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Integrate ActionHistory into Agent + BaseAgent

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This commit is contained in:
Reinier van der Leer
2023-08-25 02:09:38 +02:00
parent 2c07e8a4d9
commit 69f43edfee
7 changed files with 81 additions and 45 deletions
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34
autogpt/agents/agent.py
View File

@@ -24,6 +24,7 @@ from autogpt.logs.log_cycle import (
LogCycleHandler,
)
from autogpt.models.agent_actions import (
Action,
ActionErrorResult,
ActionInterruptedByHuman,
ActionResult,
@@ -111,8 +112,8 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
kwargs["append_messages"] = []
kwargs["append_messages"].append(budget_msg)
# Include message history in base prompt
kwargs["with_message_history"] = True
# # Include message history in base prompt
# kwargs["with_message_history"] = True
return super().construct_base_prompt(*args, **kwargs)
@@ -124,7 +125,7 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
self.ai_config.ai_name,
self.created_at,
self.cycle_count,
self.history.raw(),
self.message_history.raw(),
FULL_MESSAGE_HISTORY_FILE_NAME,
)
self.log_cycle_handler.log_cycle(
@@ -146,7 +147,7 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
if command_name == "human_feedback":
result = ActionInterruptedByHuman(user_input)
self.history.add(
self.message_history.add(
"user",
"I interrupted the execution of the command you proposed "
f"to give you some feedback: {user_input}",
@@ -190,10 +191,13 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
logger.debug(f"Command result: {result}")
result_tlength = count_string_tokens(str(result), self.llm.name)
memory_tlength = count_string_tokens(
str(self.history.summary_message()), self.llm.name
# history_tlength = count_string_tokens(
# str(self.message_history.summary_message()), self.llm.name
# )
history_tlength = count_string_tokens(
self.event_history.generate_list(), self.llm.name
)
if result_tlength + memory_tlength > self.send_token_limit:
if result_tlength + history_tlength > self.send_token_limit:
result = ActionErrorResult(
reason=f"Command {command_name} returned too much output. "
"Do not execute this command again with the same arguments."
@@ -209,7 +213,7 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
# Check if there's a result from the command append it to the message
if result.status == "success":
self.history.add(
self.message_history.add(
"system",
f"Command {command_name} returned: {result.results}",
"action_result",
@@ -225,7 +229,10 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
):
message = message.rstrip(".") + f". {result.error.hint}"
self.history.add("system", message, "action_result")
self.message_history.add("system", message, "action_result")
# Update action history
self.event_history.register_result(result)
return result
@@ -264,6 +271,15 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
assistant_reply_dict,
NEXT_ACTION_FILE_NAME,
)
self.event_history.register_action(
Action(
name=command_name,
args=arguments,
reasoning=assistant_reply_dict["thoughts"]["reasoning"],
)
)
return response

28
autogpt/agents/base.py
View File

@@ -15,7 +15,7 @@ from autogpt.llm.base import ChatModelResponse, ChatSequence, Message
from autogpt.llm.providers.openai import OPEN_AI_CHAT_MODELS, get_openai_command_specs
from autogpt.llm.utils import count_message_tokens, create_chat_completion
from autogpt.memory.message_history import MessageHistory
from autogpt.models.agent_actions import ActionResult
from autogpt.models.agent_actions import ActionHistory, ActionResult
from autogpt.prompts.generator import PromptGenerator
from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT
@@ -93,7 +93,9 @@ class BaseAgent(metaclass=ABCMeta):
defaults to 75% of `llm.max_tokens`.
"""
self.history = MessageHistory(
self.event_history = ActionHistory()
self.message_history = MessageHistory(
self.llm,
max_summary_tlength=summary_max_tlength or self.send_token_limit // 6,
)
@@ -177,6 +179,16 @@ class BaseAgent(metaclass=ABCMeta):
reserve_tokens: Number of tokens to reserve for content that is added later
"""
if self.event_history:
prepend_messages.append(
Message(
"system",
"# Progress\n"
"So far, the following things have happened:\n"
f"{self.event_history.generate_list()}",
)
)
prompt = ChatSequence.for_model(
self.llm.name,
[Message("system", self.system_prompt)] + prepend_messages,
@@ -184,7 +196,7 @@ class BaseAgent(metaclass=ABCMeta):
if with_message_history:
# Reserve tokens for messages to be appended later, if any
reserve_tokens += self.history.max_summary_tlength
reserve_tokens += self.message_history.max_summary_tlength
if append_messages:
reserve_tokens += count_message_tokens(append_messages, self.llm.name)
@@ -192,10 +204,10 @@ class BaseAgent(metaclass=ABCMeta):
# Trim remaining historical messages and add them to the running summary.
history_start_index = len(prompt)
trimmed_history = add_history_upto_token_limit(
prompt, self.history, self.send_token_limit - reserve_tokens
prompt, self.message_history, self.send_token_limit - reserve_tokens
)
if trimmed_history:
new_summary_msg, _ = self.history.trim_messages(
new_summary_msg, _ = self.message_history.trim_messages(
list(prompt), self.config
)
prompt.insert(history_start_index, new_summary_msg)
@@ -359,8 +371,8 @@ class BaseAgent(metaclass=ABCMeta):
"""
# Save assistant reply to message history
self.history.append(prompt[-1])
self.history.add(
self.message_history.append(prompt[-1])
self.message_history.add(
"assistant", llm_response.content, "ai_response"
) # FIXME: support function calls
@@ -370,7 +382,7 @@ class BaseAgent(metaclass=ABCMeta):
)
except InvalidAgentResponseError as e:
# TODO: tune this message
self.history.add(
self.message_history.add(
"system",
f"Your response could not be parsed: {e}"
"\n\nRemember to only respond using the specified format above!",

6
autogpt/agents/planning_agent.py
View File

@@ -285,7 +285,7 @@ class PlanningAgent(ContextMixin, WorkspaceMixin, BaseAgent):
result_tlength = count_string_tokens(str(result), self.llm.name)
memory_tlength = count_string_tokens(
str(self.history.summary_message()), self.llm.name
str(self.message_history.summary_message()), self.llm.name
)
if result_tlength + memory_tlength > self.send_token_limit:
result = ActionErrorResult(
@@ -303,7 +303,7 @@ class PlanningAgent(ContextMixin, WorkspaceMixin, BaseAgent):
# Check if there's a result from the command append it to the message
if result.status == "success":
self.history.add(
self.message_history.add(
"system",
f"Command {command_name} returned: {result.results}",
"action_result",
@@ -316,7 +316,7 @@ class PlanningAgent(ContextMixin, WorkspaceMixin, BaseAgent):
and result.error.hint
):
message = message.rstrip(".") + f". {result.error.hint}"
self.history.add("system", message, "action_result")
self.message_history.add("system", message, "action_result")
return result

26
autogpt/models/agent_actions.py
View File

@@ -3,6 +3,8 @@ from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Iterator, Literal, Optional
from autogpt.prompts.utils import format_numbered_list
@dataclass
class Action:
@@ -20,7 +22,12 @@ class ActionSuccessResult:
status: Literal["success"] = "success"
def __str__(self) -> str:
return f"Action succeeded and returned: `{self.results}`"
results = (
f'"""{self.results}"""'
if type(self.results) == str and any(s in self.results for s in ("\n", '"'))
else f'"{self.results}"'
)
return f"Action succeeded, and returned: {results}"
@dataclass
@@ -30,7 +37,7 @@ class ActionErrorResult:
status: Literal["error"] = "error"
def __str__(self) -> str:
return f"Action failed: `{self.reason}`"
return f"Action failed: '{self.reason}'"
@dataclass
@@ -50,9 +57,14 @@ class ActionHistory:
@dataclass
class CycleRecord:
action: Action | None
action: Action
result: ActionResult | None
def __str__(self):
executed_action = f"You executed `{self.action.format_call()}`."
action_result = f" Result: {self.result}" if self.result else ""
return executed_action + action_result
cursor: int
cycles: list[CycleRecord]
@@ -80,13 +92,11 @@ class ActionHistory:
def register_action(self, action: Action) -> None:
if not self.current_record:
self.cycles.append(self.CycleRecord(None, None))
self.cycles.append(self.CycleRecord(action, None))
assert self.current_record
elif self.current_record.action:
raise ValueError("Action for current cycle already set")
self.current_record.action = action
def register_result(self, result: ActionResult) -> None:
if not self.current_record:
raise RuntimeError("Cannot register result for cycle without action")
@@ -94,3 +104,7 @@ class ActionHistory:
raise ValueError("Result for current cycle already set")
self.current_record.result = result
self.cursor = len(self.cycles)
def generate_list(self) -> str:
return format_numbered_list(self.cycles)

25
autogpt/prompts/generator.py
View File

@@ -13,6 +13,8 @@ if TYPE_CHECKING:
from autogpt.config import AIConfig, AIDirectives, Config
from autogpt.models.command_registry import CommandRegistry
from .utils import format_numbered_list
logger = logging.getLogger(__name__)
@@ -124,19 +126,6 @@ class PromptGenerator:
if best_practice not in self.best_practices:
self.best_practices.append(best_practice)
def _generate_numbered_list(self, items: list[str], start_at: int = 1) -> str:
"""
Generate a numbered list containing the given items.
Params:
items (list): A list of items to be numbered.
start_at (int, optional): The number to start the sequence with; defaults to 1.
Returns:
str: The formatted numbered list.
"""
return "\n".join(f"{i}. {item}" for i, item in enumerate(items, start_at))
def construct_system_prompt(self, agent: BaseAgent) -> str:
"""Constructs a system prompt containing the most important information for the AI.
@@ -257,15 +246,15 @@ class PromptGenerator:
return [
"## Constraints\n"
"You operate within the following constraints:\n"
f"{self._generate_numbered_list(self.constraints + additional_constraints)}",
f"{format_numbered_list(self.constraints + additional_constraints)}",
"## Resources\n"
"You can leverage access to the following resources:\n"
f"{self._generate_numbered_list(self.resources + additional_resources)}",
f"{format_numbered_list(self.resources + additional_resources)}",
"## Commands\n"
"You have access to the following commands:\n"
f"{self.list_commands(agent)}",
"## Best practices\n"
f"{self._generate_numbered_list(self.best_practices + additional_best_practices)}",
f"{format_numbered_list(self.best_practices + additional_best_practices)}",
]
def list_commands(self, agent: BaseAgent) -> str:
@@ -284,6 +273,6 @@ class PromptGenerator:
]
# Add commands from plugins etc.
command_strings += [str(cmd) for cmd in self.commands]
command_strings += [str(cmd) for cmd in self.commands.values()]
return self._generate_numbered_list(command_strings)
return format_numbered_list(command_strings)

5
autogpt/prompts/utils.py Normal file
View File

@@ -0,0 +1,5 @@
from typing import Any
def format_numbered_list(items: list[Any], start_at: int = 1) -> str:
return "\n".join(f"{i}. {str(item)}" for i, item in enumerate(items, start_at))

2
tests/unit/test_agent.py
View File

@@ -3,7 +3,7 @@ from autogpt.agents.agent import Agent, execute_command
def test_agent_initialization(agent: Agent):
assert agent.ai_config.ai_name == "Base"
assert agent.history.messages == []
assert agent.message_history.messages == []
assert agent.cycle_budget is None
assert "You are Base" in agent.system_prompt