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agents.py
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agents.py
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import json
import re
import logging
from dataclasses import dataclass
from pathlib import Path
from simple_parsing.helpers import field, FrozenSerializable, FlattenedAccess
from sweagent.agent.commands import Command, ParseCommand
from sweagent.agent.history_processors import HistoryProcessor
from sweagent.agent.models import (
APIStats,
ContextWindowExceededError,
CostLimitExceededError,
ModelArguments,
get_model,
)
from sweagent.agent.parsing import ParseFunction, FormatError
from sweagent.environment.utils import LOGGER_NAME
from sweagent.environment.swe_env import SWEEnv
from tenacity import RetryError
from typing import Optional, Tuple, Any
logger = logging.getLogger(LOGGER_NAME)
@dataclass(frozen=True)
class Subroutine(FrozenSerializable):
name: str
agent_file: str
return_type: str = None # one of "action", "observation", "response", "state", "thought"
init_observation: Optional[str] = None
end_name: Optional[str] = None
signature: Optional[str] = None
docstring: Optional[str] = None
model: Optional[ModelArguments] = None
agent_args: Optional[Any] = None
@dataclass(frozen=True)
class AgentConfig(FrozenSerializable):
system_template: str
instance_template: str
next_step_template: Optional[str] = None # defaults to instance_template
next_step_no_output_template: Optional[str] = None # defaults to next_step_template
strategy_template: Optional[str] = None
demonstration_template: Optional[str] = None
demonstrations: list[str] = field(default_factory=list)
put_demos_in_history: bool = False # if True, add demonstration to history instead of as a single message
format_error_template: str = None # defaults to format_error_template in ParseFunction
command_files: list[str] = field(default_factory=list)
env_variables: dict[str, str] = field(default_factory=dict)
util_functions: list[str] = field(default_factory=list)
submit_command: str = "submit"
parse_function: str = "ThoughtActionParser"
parse_command: str = "ParseCommandBash"
history_processor: str = "DefaultHistoryProcessor"
history_processor_args: dict[str, Any] = field(default_factory=dict)
command_docs: str = None
blocklist_error_template: str = "Interactive operation '{name}' is not supported by this environment"
blocklist: Tuple[str] = (
"vim",
"vi",
"emacs",
"nano",
"nohup",
"git",
)
blocklist_standalone: Tuple[str] = (
"python",
"python3",
"ipython",
"bash",
"sh",
"exit",
"/bin/bash",
"/bin/sh",
"nohup",
"vi",
"vim",
"emacs",
"nano",
)
# Should extract environment state in a json readable form
state_command: Command = Command(
name="state",
code="""state() {
echo '{"working_dir": "'$(realpath --relative-to=$ROOT/.. $PWD)'"}';
};""",
)
_commands: list[Command] = field(default_factory=list)
_subroutines: dict[str, Subroutine] = field(default_factory=dict)
subroutine_types: list[Subroutine] = field(default_factory=list)
def __post_init__(self):
if self.next_step_template is None:
object.__setattr__(self, "next_step_template", self.instance_template)
if self.next_step_no_output_template is None:
object.__setattr__(
self, "next_step_no_output_template", self.next_step_template
)
object.__setattr__(self, "parse_command", ParseCommand.get(self.parse_command))
for file in self.command_files:
commands = self.parse_command.parse_command_file(file)
util_functions = [
command for command in commands if command.name.startswith("_")
]
commands = [
command for command in commands if not command.name.startswith("_")
]
object.__setattr__(
self, "util_functions", self.util_functions + util_functions
)
object.__setattr__(self, "_commands", self._commands + commands)
for subroutine in self.subroutine_types:
if subroutine.name == 'submit':
raise ValueError("Cannot use 'submit' as a subroutine name")
agent_args = AgentArguments(
model=subroutine.model,
config_file=subroutine.agent_file,
)
object.__setattr__(subroutine, "agent_args", agent_args)
object.__setattr__(self, "_subroutines", {**self._subroutines, subroutine.name: subroutine})
multi_line_command_endings = {
command.name: command.end_name
for command in [*self._commands, *self._subroutines.values()]
if command.end_name is not None
}
object.__setattr__(self, "multi_line_command_endings", multi_line_command_endings)
object.__setattr__(
self,
"command_docs",
self.parse_command.generate_command_docs(
self._commands,
self.subroutine_types,
**self.env_variables,
),
)
object.__setattr__(self, "parse_function", ParseFunction.get(self.parse_function))
if self.format_error_template is None:
object.__setattr__(
self,
"format_error_template",
self.parse_function.format_error_template,
)
object.__setattr__(self, "format_error_template", self.format_error_template.format(**self.__dict__))
for command in self._commands:
if command.name == self.submit_command:
object.__setattr__(self, "submit_command_end_name", command.end_name)
break
object.__setattr__(
self, "history_processor",
HistoryProcessor.get(self.history_processor, **self.history_processor_args)
)
@dataclass(frozen=True)
class AgentArguments(FlattenedAccess, FrozenSerializable):
model: ModelArguments = None
# Policy can only be set via config yaml file from command line
config_file: Optional[Path] = None
config: Optional[AgentConfig] = field(default=None, cmd=False)
def __post_init__(self):
if self.config is None and self.config_file is not None:
# If unassigned, we load the config from the file to store its contents with the overall arguments
config = AgentConfig.load_yaml(self.config_file)
object.__setattr__(self, "config", config)
assert self.config is not None
for subroutine in getattr(self.config, "subroutines", {}).values():
model_args = getattr(subroutine, "model")
object.__setattr__(model_args, "per_instance_cost_limit", self.model.per_instance_cost_limit)
object.__setattr__(model_args, "total_cost_limit", self.model.total_cost_limit)
class Agent:
"""Agent handles the behaviour of the model and how it interacts with the environment."""
def __init__(self, name: str, args: AgentArguments):
self.name = name
self.model = get_model(args.model, args.config._commands + args.config.subroutine_types)
self.config = args.config
self.system_args = {
"command_docs": self.config.command_docs,
**self.config.env_variables,
}
self.instance_args = None
self._parse_command_patterns()
self.history = []
self.last_container_id = None
def setup(self, instance_args, init_model_stats=None) -> None:
"""Setup the agent for a new instance."""
self.model.reset_stats(init_model_stats)
self.instance_args = instance_args
system_msg = self.config.system_template.format(**self.system_args)
logger.info(f"SYSTEM ({self.name})\n{system_msg}")
self.history = [
{"role": "system", "content": system_msg, "agent": self.name},
]
if len(self.config.demonstrations) > 0 and "history_to_messages" in dir(
self.model
):
for demonstration_path in self.config.demonstrations:
if self.config.demonstration_template is None and not self.config.put_demos_in_history:
raise ValueError("Cannot use demonstrations without a demonstration template or put_demos_in_history=True")
# Load history
logger.info(f"DEMONSTRATION: {demonstration_path}")
demo_history = json.load(open(demonstration_path, "r"))["history"]
demo_history = [
entry for entry in demo_history
if ("agent" not in entry) or
("agent" in entry and entry["agent"] == self.name)
]
if self.config.put_demos_in_history:
if self.config.demonstration_template is not None:
logger.warning("Demonstration template is ignored for put_demos_in_history=True")
# Add demonstration to history directly as separate messages
for entry in demo_history:
if entry["role"] != "system":
entry["is_demo"] = True
self.history.append(entry)
else:
# Add demonstration as single message to history
demo_message = self.model.history_to_messages(
demo_history,
is_demonstration=True,
)
demonstration = self.config.demonstration_template.format(
**{"demonstration": demo_message}
)
self.history.append({
"agent": self.name,
"content": demonstration,
"is_demo": True,
"role": "user",
})
@property
def state_command(self) -> str:
"""Return the bash command that will be used to extract the environment state."""
return self.config.state_command.name
@property
def local_history(self) -> list[dict[str, str]]:
"""Return the history of the agent since the last reset."""
return self.config.history_processor([entry for entry in self.history if entry["agent"] == self.name])
def save_trajectory(self, trajectory, traj_dir, env, info):
log_path = traj_dir / (env.record['instance_id'] + ".traj")
log_dict = {
"environment": env.name,
"trajectory": trajectory,
"history": self.history,
"info": info,
}
with log_path.open("w") as f:
json.dump(log_dict, f, indent=2)
logger.info(f"Saved trajectory to {log_path}")
def _get_first_match(self, action: str, pattern_type: str) -> Optional[re.Match]:
"""Return the first match of a command pattern in the action string."""
if pattern_type == "subroutine":
patterns = {k: v for k, v in self.subroutine_patterns.items()}
elif pattern_type == "multi_line":
patterns = {k: v for k, v in self.command_patterns.items() if k in self.config.multi_line_command_endings or k == self.config.submit_command}
patterns += {k: v for k, v in self.subroutine_patterns.items() if k in self.config.multi_line_command_endings}
elif pattern_type == "multi_line_no_subroutines":
patterns = {k: v for k, v in self.command_patterns.items() if k in self.config.multi_line_command_endings}
else:
raise ValueError(f"Unknown pattern type: {pattern_type}")
matches = list()
for name, pat in patterns.items():
match = pat.search(action)
if match:
matches.append(match)
if len(matches) == 0:
return None
matches = sorted(matches, key=lambda x: x.start())
return matches[0]
def _guard_multiline_input(self, action: str) -> str:
"""Split action by multiline commands, then append the first line in each multiline command with "<< '{end_name}'".
Multiline commands (which are specified by an end_name) are commands that span multiple lines and are terminated by a specific end_name.
Their multi-line argument is sent using a heredoc, which is a way to send a multi-line string to a command in bash.
"""
parsed_action = list()
rem_action = action
while rem_action.strip():
first_match = self._get_first_match(rem_action, "multi_line_no_subroutines")
if first_match:
pre_action = rem_action[:first_match.start()]
match_action = rem_action[first_match.start():first_match.end()]
rem_action = rem_action[first_match.end():]
if pre_action.strip():
parsed_action.append(pre_action)
if match_action.strip():
eof = first_match.group(3).strip()
if not match_action.split('\n')[0].strip().endswith(f"<< '{eof}'"):
guarded_command = match_action[first_match.start():]
first_line = guarded_command.split('\n')[0]
guarded_command = guarded_command.replace(
first_line,
first_line + f" << '{eof}'",
1
)
parsed_action.append(guarded_command)
else:
parsed_action.append(match_action)
else:
parsed_action.append(rem_action)
rem_action = ""
return '\n'.join(parsed_action)
def split_actions(self, action: str, pattern_type="subroutine") -> list[str]:
"""Split an action into a list of actions in a greedy manner, each of which is a subroutine call or a single command."""
parsed_action = list()
rem_action = action
while rem_action.strip():
first_match = self._get_first_match(rem_action, pattern_type)
if first_match:
pre_action = rem_action[:first_match.start()]
match_action = rem_action[first_match.start():first_match.end()]
rem_action = rem_action[first_match.end():]
if pre_action.strip():
parsed_action.append({'agent': self.name, 'action': pre_action, 'cmd_name': None})
if match_action.strip():
if match_action.split()[0] == self.config.submit_command:
parsed_action.append({'agent': self.name, 'action': match_action, 'cmd_name': first_match.group(1)}) # submit command is not a subroutine
else:
parsed_action.append({'agent': first_match.group(1), 'args': first_match.group(2), 'action': match_action, 'cmd_name': first_match.group(1)})
else:
parsed_action.append({'agent': self.name, 'action': rem_action, 'cmd_name': None})
rem_action = ""
return parsed_action
def _parse_command_patterns(self):
self.command_patterns = dict()
for command in self.config._commands:
if command.end_name is not None:
pat = re.compile(fr'^\s*({command.name})\s*(.*?)^({command.end_name})\s*$', re.DOTALL | re.MULTILINE)
self.command_patterns[command.name] = pat
else:
pat = re.compile(fr'^\s*({command.name})\s*(.*?)$', re.MULTILINE)
self.command_patterns[command.name] = pat
self.subroutine_patterns = dict()
for _, subroutine in self.config._subroutines.items():
if subroutine.end_name is None:
pat = re.compile(fr'^\s*({subroutine.name})\s*(.*?)$', re.MULTILINE)
self.subroutine_patterns[subroutine.name,] = pat
else:
pat = re.compile(fr'^\s*({subroutine.name})\s*(.*?)^({subroutine.end_name})\s*$', re.DOTALL | re.MULTILINE)
self.subroutine_patterns[subroutine.name] = pat
if hasattr(self.config, 'submit_command_end_name'):
submit_pat = re.compile(rf'^\s*({self.config.submit_command})\s*(.*?)^({self.config.submit_command_end_name})\s*$', re.DOTALL | re.MULTILINE)
else:
submit_pat = re.compile(rf'^\s*({self.config.submit_command})(\s*)$', re.MULTILINE) # group 2 is nothing
self.subroutine_patterns[self.config.submit_command] = submit_pat
self.command_patterns[self.config.submit_command] = submit_pat
def forward(self, observation: str, available_actions: list[str], state: str) -> Tuple[str, str, str]:
thought, action, output = self.forward_with_error_check(observation, state)
self.history.append(
{"role": "assistant",
"content": output,
"thought": thought,
"action": action,
"agent": self.name,
}
)
logger.info(f"💭 THOUGHT ({self.name})\n{thought}")
logger.info(f"🎬 ACTION ({self.name})\n{action}")
return thought, action, output
def forward_model(self, observation: str, state: str) -> str:
"""Query the model with the current state and observation with the appropriate template.
Returns the model output."""
state_vars = json.loads(state)
templates = []
# Determine observation template based on what prior observation was
if self.history[-1]["role"] == "system" or self.history[-1].get("is_demo", False):
# Show instance template if prev. obs. was initial system message
templates = [self.config.instance_template]
if self.config.strategy_template is not None:
templates.append(self.config.strategy_template)
elif observation is None or observation.strip() == "":
# Show no output template if observation content was empty
templates = [self.config.next_step_no_output_template]
else:
# Show standard output template if there is observation content
templates = [self.config.next_step_template]
# Populate selected template(s) with information (e.g., issue, arguments, state)
messages = []
for template in templates:
messages.append(
template.format(
**self.instance_args,
**self.system_args,
**state_vars,
observation=(observation if observation is not None else ""),
)
)
message = "\n".join(messages)
logger.info(f"🤖 MODEL INPUT\n{message}")
self.history.append({"role": "user", "content": message, "agent": self.name})
return self.model.query(self.local_history)
def retry_after_format_fail(self, output):
"""Ask the model to correct (without committing to persistent history) after a malformatted model output"""
format_error_template = self.config.format_error_template
logger.warning(f"MALFORMED OUTPUT\n{output}")
logger.warning(f"FORMAT ERROR\n{format_error_template}")
temp_history = self.local_history + [
{"role": "assistant", "content": output, "agent": self.name},
{"role": "user", "content": format_error_template, "agent": self.name},
]
return self.model.query(temp_history)
def retry_after_blocklist_fail(self, output, action):
"""Ask the model to correct (without committing to persistent history) after a disallowed command"""
name = action.strip().split()[0]
blocklist_error_message = self.config.blocklist_error_template.format(name=name)
logger.warning(f"BLOCKLISTED OUTPUT\n{output}")
logger.warning(f"BLOCKLIST ERROR\n{blocklist_error_message}")
temp_history = self.local_history + [
{"role": "assistant", "content": output, "agent": self.name},
{"role": "user", "content": blocklist_error_message, "agent": self.name},
]
return self.model.query(temp_history)
def should_block_action(self, action):
"""Check if the command should be blocked."""
names = action.strip().split()
if len(names) == 0:
return False
name = names[0]
if name in self.config.blocklist:
return True
if name in self.config.blocklist_standalone and name == action.strip():
return True
return False
def check_format_and_requery(
self, output: str,
) -> Tuple[str, str, str]:
"""Query the model with the current state and observation with the appropriate template.
Try to parse the output into a thought and action. Retry if the output is malformatted or the action is blocked.
Returns the thought, action, and raw model output.
"""
# Condition for handling outputs with no thought (just action)
if self.model.args.model_name == "human":
return "", output, output
elif self.model.args.model_name == "human_thought":
thought, action = ParseFunction.get("ThoughtActionParser")(
output,
self.config._commands + self.config.subroutine_types,
strict=False,
)
return thought, action, output
format_fails = blocklist_fails = 0
while format_fails + blocklist_fails <= 2:
try:
thought, action = self.config.parse_function(
output,
self.config._commands + self.config.subroutine_types,
strict=False,
)
except KeyboardInterrupt:
raise
except FormatError as e:
format_fails += 1
output = self.retry_after_format_fail(output)
continue
if self.should_block_action(action):
blocklist_fails += 1
output = self.retry_after_blocklist_fail(output, action)
else:
return thought, action, output
logger.warning(f"Malformat limit reached: \n{output}")
return "Exit due to format error", "exit_format", output
def forward_with_error_check(self, observation: str, state: str) -> Tuple[str, str, str]:
try:
output = self.forward_model(observation, state)
except KeyboardInterrupt:
raise
except RuntimeError as e:
logger.warning(f"Runtime error: {e}")
return (
f"Exit due to runtime error: {e}",
"exit_error",
f"exit due to runtime error: {e}",
)
except ContextWindowExceededError as e:
logger.warning(f"Context window exceeded")
return "Exit due to context window", "exit_context", "Exit due to context window"
except CostLimitExceededError as e:
logger.warning(f"Cost limit exceeded")
return "Exit due to cost limit", "exit_cost", "Exit due to cost limit"
except RetryError as e:
logger.warning(f"Retry error: {e}")
return (
f"Exit due to retry error: {e}",
"exit_api",
f"exit due to retry error: {e}",
)
return self.check_format_and_requery(output)
def init_environment_vars(self, env):
self.set_environment_vars(env, self.config.env_variables)
def set_environment_vars(self, env, env_variables):
commands_to_execute = (
[self.config.state_command.code] +
# [code for code in self.config.util_functions] +
# [command.code for command in self.config._commands] +
[f"{k}={v}" for k,v in env_variables.items()]
)
commands = "\n".join(commands_to_execute)
try:
output = env.communicate(commands)
if env.returncode != 0:
raise RuntimeError(f"Nonzero return code: {env.returncode}\nOutput: {output}")
except KeyboardInterrupt:
raise
except Exception as e:
logger.warning("Failed to set environment variables")
raise e
command_files = list()
for file in self.config.command_files:
datum = dict()
contents = open(file, 'r').read()
datum['contents'] = contents
filename = Path(file).name
if not contents.strip().startswith('#!'):
if filename.endswith('.sh'):
# files are sourced, so they are not executable
datum['name'] = Path(file).name
datum['type'] = 'source_file'
elif filename.startswith('_'):
# files are sourced, so they are not executable
datum['name'] = Path(file).name
datum['type'] = 'utility'
else:
raise ValueError((
f"Non-shell script file {file} does not start with shebang.\n"
"Either add a shebang (#!) or change the file extension to .sh if you want to source it.\n"
"You can override this behavior by adding an underscore to the file name (e.g. _utils.py)."
))
else:
# scripts are made executable
datum['name'] = Path(file).name.rsplit('.', 1)[0]
datum['type'] = 'script'
command_files.append(datum)
env.add_commands(command_files)
def get_environment_vars(self, env):
env_vars = dict()
for var in self.config.env_variables:
env_vars[var] = env.communicate(f"echo ${var}").strip()
return env_vars
def call_subroutine(self, agent_name, sub_action, env):
env_vars = self.get_environment_vars(env)
cwd = env.communicate("pwd -P").strip()
init_observation = self.config._subroutines[agent_name].init_observation
if init_observation is not None:
obs, _, _, _ = env.step(init_observation.format(args=sub_action['args']))
else:
obs = None
if env.returncode != 0:
self.history.append({"role": "user", "content": obs, "agent": agent_name})
raise RuntimeError(f"Nonzero return code: {env.returncode} for init_observation in {agent_name}.\n{obs}")
return_type = self.config._subroutines[agent_name].return_type
sub_agent = Agent(agent_name, self.config._subroutines[agent_name].agent_args)
sub_agent_output = sub_agent.run(
{"issue": sub_action['args']},
env,
observation=obs,
return_type=return_type,
init_model_stats=self.model.stats,
)
self.history += sub_agent.history
self.set_environment_vars(env, env_vars)
env.communicate(f"cd {cwd}")
self.model.stats.replace(sub_agent.model.stats)
return sub_agent_output
def run(
self,
setup_args,
env: SWEEnv,
observation: str = None,
traj_dir: Optional[Path] = None,
return_type: Optional[str] = "info",
init_model_stats: Optional[APIStats] = None,
):
"""
Run the agent on an environment.
Return the final value of the specified return type.
"""
done = False
if env.container_obj.id != self.last_container_id:
logger.info(f"Initializing agent settings for container {env.container_obj.id}")
self.init_environment_vars(env)
self.last_container_id = env.container_obj.id
# Re-initialize primary
self.setup(setup_args, init_model_stats)
# Run action/observation loop
trajectory = []
info = {}
while not done:
state = env.communicate(self.state_command) if self.state_command else None
thought, action, output = self.forward(
observation,
env.get_available_actions(),
state)
observations = list()
run_action = self._guard_multiline_input(action)
for sub_action in self.split_actions(run_action):
if sub_action['agent'] == self.name or sub_action['cmd_name'] == self.config.submit_command:
obs, _, done, info = env.step(sub_action['action'])
observations.append(obs)
if sub_action['cmd_name'] == self.config.submit_command:
done = True
if done:
break
else:
agent_name = sub_action['agent']
sub_agent_output = self.call_subroutine(agent_name, sub_action, env)
observations.append(sub_agent_output)
observation = '\n'.join([obs for obs in observations if obs is not None])
trajectory.append(
{
"action": action,
"observation": observation,
"response": output,
"state": state,
"thought": thought,
}
)
info['model_stats'] = self.model.stats.to_dict()
if traj_dir:
self.save_trajectory(trajectory, traj_dir, env, info)
if return_type == "info":
return info
if return_type == "info_trajectory":
return info, trajectory
if return_type != "info":
return trajectory[-1][return_type]