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Merge branch 'action-history'

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This commit is contained in:
Reinier van der Leer
2023-08-28 19:46:25 +02:00
parent 78a620c1ec 82a81e5865
commit a929716456
8 changed files with 115 additions and 59 deletions
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37
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}",
@@ -187,13 +188,11 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
except AgentException as e:
result = ActionErrorResult(e.message, e)
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(
self.event_history.fmt_paragraph(), 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."
@@ -203,15 +202,15 @@ class Agent(ContextMixin, WorkspaceMixin, BaseAgent):
if not plugin.can_handle_post_command():
continue
if result.status == "success":
result.results = plugin.post_command(command_name, result.results)
result.outputs = plugin.post_command(command_name, result.outputs)
elif result.status == "error":
result.reason = plugin.post_command(command_name, result.reason)
# 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}",
f"Command {command_name} returned: {result.outputs}",
"action_result",
)
elif result.status == "error":
@@ -225,7 +224,10 @@ 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 +266,15 @@ 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

27
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 +179,15 @@ class BaseAgent(metaclass=ABCMeta):
reserve_tokens: Number of tokens to reserve for content that is added later
"""
if self.event_history:
prepend_messages.insert(
0,
Message(
"system",
"## Progress\n\n" f"{self.event_history.fmt_paragraph()}",
),
)
prompt = ChatSequence.for_model(
self.llm.name,
[Message("system", self.system_prompt)] + prepend_messages,
@@ -184,7 +195,7 @@ 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 +203,10 @@ 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 +370,8 @@ 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 +381,7 @@ 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!",

10
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(
@@ -297,15 +297,15 @@ class PlanningAgent(ContextMixin, WorkspaceMixin, BaseAgent):
if not plugin.can_handle_post_command():
continue
if result.status == "success":
result.results = plugin.post_command(command_name, result.results)
result.outputs = plugin.post_command(command_name, result.outputs)
elif result.status == "error":
result.reason = plugin.post_command(command_name, result.reason)
# 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}",
f"Command {command_name} returned: {result.outputs}",
"action_result",
)
elif result.status == "error":
@@ -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

14
autogpt/commands/file_operations.py
View File

@@ -11,7 +11,7 @@ import logging
import os
import os.path
from pathlib import Path
from typing import Generator, Literal
from typing import Iterator, Literal
from autogpt.agents.agent import Agent
from autogpt.agents.utils.exceptions import DuplicateOperationError
@@ -34,7 +34,9 @@ def text_checksum(text: str) -> str:
def operations_from_log(
log_path: str | Path,
) -> Generator[tuple[Operation, str, str | None], None, None]:
) -> Iterator[
tuple[Literal["write", "append"], str, str] | tuple[Literal["delete"], str, None]
]:
"""Parse the file operations log and return a tuple containing the log entries"""
try:
log = open(log_path, "r", encoding="utf-8")
@@ -48,11 +50,7 @@ def operations_from_log(
operation, tail = line.split(": ", maxsplit=1)
operation = operation.strip()
if operation in ("write", "append"):
try:
path, checksum = (x.strip() for x in tail.rsplit(" #", maxsplit=1))
except ValueError:
logger.warn(f"File log entry lacks checksum: '{line}'")
path, checksum = tail.strip(), None
path, checksum = (x.strip() for x in tail.rsplit(" #", maxsplit=1))
yield (operation, path, checksum)
elif operation == "delete":
yield (operation, tail.strip(), None)
@@ -228,7 +226,7 @@ def write_to_file(filename: Path, text: str, agent: Agent) -> str:
with open(filename, "w", encoding="utf-8") as f:
f.write(text)
log_operation("write", filename, agent, checksum)
return "File written to successfully."
return f"File {filename.name} has been written successfully."
@sanitize_path_arg("filename")

50
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, indent
@dataclass
class Action:
@@ -16,11 +18,13 @@ class Action:
@dataclass
class ActionSuccessResult:
results: Any
outputs: Any
status: Literal["success"] = "success"
def __str__(self) -> str:
return f"Action succeeded and returned: `{self.results}`"
outputs = str(self.outputs).replace("```", r"\```")
multiline = "\n" in outputs
return f"```\n{self.outputs}\n```" if multiline else str(self.outputs)
@dataclass
@@ -30,7 +34,7 @@ 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 +54,14 @@ class ActionHistory:
@dataclass
class CycleRecord:
action: Action | None
action: Action
result: ActionResult | None
def __str__(self) -> str:
executed_action = f"Executed `{self.action.format_call()}`"
action_result = f": {self.result}" if self.result else "."
return executed_action + action_result
cursor: int
cycles: list[CycleRecord]
@@ -80,13 +89,11 @@ 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 +101,32 @@ class ActionHistory:
raise ValueError("Result for current cycle already set")
self.current_record.result = result
self.cursor = len(self.cycles)
def fmt_list(self) -> str:
return format_numbered_list(self.cycles)
def fmt_paragraph(self) -> str:
steps: list[str] = []
for i, c in enumerate(self.cycles, 1):
step = f"### Step {i}: Executed `{c.action.format_call()}`\n"
step += f'- **Reasoning:** "{c.action.reasoning}"\n'
step += (
f"- **Status:** `{c.result.status if c.result else 'did_not_finish'}`\n"
)
if c.result:
if c.result.status == "success":
result = str(c.result)
result = "\n" + indent(result) if "\n" in result else result
step += f"- **Output:** {result}"
elif c.result.status == "error":
step += f"- **Reason:** {c.result.reason}\n"
if c.result.error:
step += f"- **Error:** {c.result.error}\n"
elif c.result.status == "interrupted_by_human":
step += f"- **Feedback:** {c.result.feedback}\n"
steps.append(step)
return "\n\n".join(steps)

23
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:
@@ -286,4 +275,4 @@ class PromptGenerator:
# Add commands from plugins etc.
command_strings += [str(cmd) for cmd in self.commands.values()]
return self._generate_numbered_list(command_strings)
return format_numbered_list(command_strings)

11
autogpt/prompts/utils.py Normal file
View File

@@ -0,0 +1,11 @@
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))
def indent(content: str, indentation: int | str = 4) -> str:
if type(indentation) == int:
indentation = " " * indentation
return indentation + content.replace("\n", f"\n{indentation}") # type: ignore

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