From 6e4ff569340f1f09cfdea02b988bdd2ba16a8b6a Mon Sep 17 00:00:00 2001 From: Calvin Smith Date: Tue, 7 Jan 2025 13:36:30 -0700 Subject: [PATCH] feature: Condenser Interface and Defaults (#5306) Co-authored-by: openhands Co-authored-by: Calvin Smith Co-authored-by: Engel Nyst --- evaluation/benchmarks/swe_bench/run_infer.py | 4 +- evaluation/utils/shared.py | 27 + .../agenthub/codeact_agent/codeact_agent.py | 13 +- openhands/core/config/agent_config.py | 5 +- openhands/core/config/condenser_config.py | 90 + openhands/core/schema/observation.py | 3 + openhands/events/observation/__init__.py | 6 +- openhands/events/observation/agent.py | 11 + openhands/events/serialization/observation.py | 6 +- openhands/memory/__init__.py | 4 +- openhands/memory/condenser.py | 411 ++- poetry.lock | 3270 ++++++++--------- pyproject.toml | 2 +- tests/unit/test_codeact_agent.py | 87 +- tests/unit/test_condenser.py | 534 ++- tests/unit/test_config.py | 10 + tests/unit/test_prompt_caching.py | 5 +- 17 files changed, 2683 insertions(+), 1805 deletions(-) create mode 100644 openhands/core/config/condenser_config.py diff --git a/evaluation/benchmarks/swe_bench/run_infer.py b/evaluation/benchmarks/swe_bench/run_infer.py index 4f0dff6508f4..bf065ada9734 100644 --- a/evaluation/benchmarks/swe_bench/run_infer.py +++ b/evaluation/benchmarks/swe_bench/run_infer.py @@ -15,6 +15,7 @@ EvalOutput, assert_and_raise, codeact_user_response, + get_metrics, is_fatal_evaluation_error, make_metadata, prepare_dataset, @@ -148,6 +149,7 @@ def get_config( codeact_enable_jupyter=False, codeact_enable_browsing=RUN_WITH_BROWSING, codeact_enable_llm_editor=False, + condenser=metadata.condenser_config, ) config.set_agent_config(agent_config) return config @@ -448,7 +450,7 @@ def process_instance( # NOTE: this is NO LONGER the event stream, but an agent history that includes delegate agent's events histories = [event_to_dict(event) for event in state.history] - metrics = state.metrics.get() if state.metrics else None + metrics = get_metrics(state) # Save the output output = EvalOutput( diff --git a/evaluation/utils/shared.py b/evaluation/utils/shared.py index 514e90519724..23c5b319d3c2 100644 --- a/evaluation/utils/shared.py +++ b/evaluation/utils/shared.py @@ -17,6 +17,10 @@ from openhands.controller.state.state import State from openhands.core.config import LLMConfig +from openhands.core.config.condenser_config import ( + CondenserConfig, + NoOpCondenserConfig, +) from openhands.core.exceptions import ( AgentRuntimeBuildError, AgentRuntimeDisconnectedError, @@ -33,6 +37,7 @@ from openhands.events.event import Event from openhands.events.serialization.event import event_to_dict from openhands.events.utils import get_pairs_from_events +from openhands.memory.condenser import get_condensation_metadata class EvalMetadata(BaseModel): @@ -45,11 +50,17 @@ class EvalMetadata(BaseModel): dataset: str | None = None data_split: str | None = None details: dict[str, Any] | None = None + condenser_config: CondenserConfig | None = None def model_dump(self, *args, **kwargs): dumped_dict = super().model_dump(*args, **kwargs) # avoid leaking sensitive information dumped_dict['llm_config'] = self.llm_config.to_safe_dict() + if hasattr(self.condenser_config, 'llm_config'): + dumped_dict['condenser_config']['llm_config'] = ( + self.condenser_config.llm_config.to_safe_dict() + ) + return dumped_dict def model_dump_json(self, *args, **kwargs): @@ -57,6 +68,11 @@ def model_dump_json(self, *args, **kwargs): dumped_dict = json.loads(dumped) # avoid leaking sensitive information dumped_dict['llm_config'] = self.llm_config.to_safe_dict() + if hasattr(self.condenser_config, 'llm_config'): + dumped_dict['condenser_config']['llm_config'] = ( + self.condenser_config.llm_config.to_safe_dict() + ) + logger.debug(f'Dumped metadata: {dumped_dict}') return json.dumps(dumped_dict) @@ -192,6 +208,7 @@ def make_metadata( eval_output_dir: str, data_split: str | None = None, details: dict[str, Any] | None = None, + condenser_config: CondenserConfig | None = None, ) -> EvalMetadata: model_name = llm_config.model.split('/')[-1] model_path = model_name.replace(':', '_').replace('@', '-') @@ -222,6 +239,9 @@ def make_metadata( dataset=dataset_name, data_split=data_split, details=details, + condenser_config=condenser_config + if condenser_config + else NoOpCondenserConfig(), ) metadata_json = metadata.model_dump_json() logger.info(f'Metadata: {metadata_json}') @@ -551,3 +571,10 @@ def is_fatal_evaluation_error(error: str | None) -> bool: return True return False + + +def get_metrics(state: State) -> dict[str, Any]: + """Extract metrics from the state.""" + metrics = state.metrics.get() if state.metrics else {} + metrics['condenser'] = get_condensation_metadata(state) + return metrics diff --git a/openhands/agenthub/codeact_agent/codeact_agent.py b/openhands/agenthub/codeact_agent/codeact_agent.py index f811723dfbd5..d8b5702a235d 100644 --- a/openhands/agenthub/codeact_agent/codeact_agent.py +++ b/openhands/agenthub/codeact_agent/codeact_agent.py @@ -24,6 +24,7 @@ MessageAction, ) from openhands.events.observation import ( + AgentCondensationObservation, AgentDelegateObservation, BrowserOutputObservation, CmdOutputObservation, @@ -36,6 +37,7 @@ from openhands.events.observation.observation import Observation from openhands.events.serialization.event import truncate_content from openhands.llm.llm import LLM +from openhands.memory.condenser import Condenser from openhands.runtime.plugins import ( AgentSkillsRequirement, JupyterRequirement, @@ -115,6 +117,9 @@ def __init__( disabled_microagents=self.config.disabled_microagents, ) + self.condenser = Condenser.from_config(self.config.condenser) + logger.debug(f'Using condenser: {self.condenser}') + def get_action_message( self, action: Action, @@ -322,6 +327,9 @@ def get_observation_message( text = 'OBSERVATION:\n' + truncate_content(obs.content, max_message_chars) text += '\n[Last action has been rejected by the user]' message = Message(role='user', content=[TextContent(text=text)]) + elif isinstance(obs, AgentCondensationObservation): + text = truncate_content(obs.content, max_message_chars) + message = Message(role='user', content=[TextContent(text=text)]) else: # If an observation message is not returned, it will cause an error # when the LLM tries to return the next message @@ -442,7 +450,10 @@ def _get_messages(self, state: State) -> list[Message]: pending_tool_call_action_messages: dict[str, Message] = {} tool_call_id_to_message: dict[str, Message] = {} - events = list(state.history) + + # Condense the events from the state. + events = self.condenser.condensed_history(state) + for event in events: # create a regular message from an event if isinstance(event, Action): diff --git a/openhands/core/config/agent_config.py b/openhands/core/config/agent_config.py index 357f812809a0..77e9dbc1e32d 100644 --- a/openhands/core/config/agent_config.py +++ b/openhands/core/config/agent_config.py @@ -1,5 +1,6 @@ -from dataclasses import dataclass, fields +from dataclasses import dataclass, field, fields +from openhands.core.config.condenser_config import CondenserConfig, NoOpCondenserConfig from openhands.core.config.config_utils import get_field_info @@ -18,6 +19,7 @@ class AgentConfig: llm_config: The name of the llm config to use. If specified, this will override global llm config. use_microagents: Whether to use microagents at all. Default is True. disabled_microagents: A list of microagents to disable. Default is None. + condenser: Configuration for the memory condenser. Default is NoOpCondenserConfig. """ codeact_enable_browsing: bool = True @@ -29,6 +31,7 @@ class AgentConfig: llm_config: str | None = None use_microagents: bool = True disabled_microagents: list[str] | None = None + condenser: CondenserConfig = field(default_factory=NoOpCondenserConfig) # type: ignore def defaults_to_dict(self) -> dict: """Serialize fields to a dict for the frontend, including type hints, defaults, and whether it's optional.""" diff --git a/openhands/core/config/condenser_config.py b/openhands/core/config/condenser_config.py new file mode 100644 index 000000000000..07250aa06ad0 --- /dev/null +++ b/openhands/core/config/condenser_config.py @@ -0,0 +1,90 @@ +from typing import Literal + +from pydantic import BaseModel, Field + +from openhands.core.config.llm_config import LLMConfig + + +class NoOpCondenserConfig(BaseModel): + """Configuration for NoOpCondenser.""" + + type: Literal['noop'] = Field('noop') + + +class ObservationMaskingCondenserConfig(BaseModel): + """Configuration for ObservationMaskingCondenser.""" + + type: Literal['observation_masking'] = Field('observation_masking') + attention_window: int = Field( + default=10, + description='The number of most-recent events where observations will not be masked.', + ge=1, + ) + + +class RecentEventsCondenserConfig(BaseModel): + """Configuration for RecentEventsCondenser.""" + + type: Literal['recent'] = Field('recent') + keep_first: int = Field( + default=0, + description='The number of initial events to condense.', + ge=0, + ) + max_events: int = Field( + default=10, description='Maximum number of events to keep.', ge=1 + ) + + +class LLMSummarizingCondenserConfig(BaseModel): + """Configuration for LLMCondenser.""" + + type: Literal['llm'] = Field('llm') + llm_config: LLMConfig = Field( + ..., description='Configuration for the LLM to use for condensing.' + ) + + +class AmortizedForgettingCondenserConfig(BaseModel): + """Configuration for AmortizedForgettingCondenser.""" + + type: Literal['amortized'] = Field('amortized') + max_size: int = Field( + default=100, + description='Maximum size of the condensed history before triggering forgetting.', + ge=2, + ) + keep_first: int = Field( + default=0, + description='Number of initial events to always keep in history.', + ge=0, + ) + + +class LLMAttentionCondenserConfig(BaseModel): + """Configuration for LLMAttentionCondenser.""" + + type: Literal['llm_attention'] = Field('llm_attention') + llm_config: LLMConfig = Field( + ..., description='Configuration for the LLM to use for attention.' + ) + max_size: int = Field( + default=100, + description='Maximum size of the condensed history before triggering forgetting.', + ge=2, + ) + keep_first: int = Field( + default=0, + description='Number of initial events to always keep in history.', + ge=0, + ) + + +CondenserConfig = ( + NoOpCondenserConfig + | ObservationMaskingCondenserConfig + | RecentEventsCondenserConfig + | LLMSummarizingCondenserConfig + | AmortizedForgettingCondenserConfig + | LLMAttentionCondenserConfig +) diff --git a/openhands/core/schema/observation.py b/openhands/core/schema/observation.py index 622f2680f785..b1414d075f3d 100644 --- a/openhands/core/schema/observation.py +++ b/openhands/core/schema/observation.py @@ -44,5 +44,8 @@ class ObservationTypeSchema(BaseModel): USER_REJECTED: str = Field(default='user_rejected') + CONDENSE: str = Field(default='condense') + """Result of a condensation operation.""" + ObservationType = ObservationTypeSchema() diff --git a/openhands/events/observation/__init__.py b/openhands/events/observation/__init__.py index 69a1853b268c..f113bcd134e5 100644 --- a/openhands/events/observation/__init__.py +++ b/openhands/events/observation/__init__.py @@ -1,4 +1,7 @@ -from openhands.events.observation.agent import AgentStateChangedObservation +from openhands.events.observation.agent import ( + AgentCondensationObservation, + AgentStateChangedObservation, +) from openhands.events.observation.browse import BrowserOutputObservation from openhands.events.observation.commands import ( CmdOutputMetadata, @@ -32,4 +35,5 @@ 'AgentDelegateObservation', 'SuccessObservation', 'UserRejectObservation', + 'AgentCondensationObservation', ] diff --git a/openhands/events/observation/agent.py b/openhands/events/observation/agent.py index 802c23c3786d..0dfbf0077464 100644 --- a/openhands/events/observation/agent.py +++ b/openhands/events/observation/agent.py @@ -14,3 +14,14 @@ class AgentStateChangedObservation(Observation): @property def message(self) -> str: return '' + + +@dataclass +class AgentCondensationObservation(Observation): + """The output of a condensation action.""" + + observation: str = ObservationType.CONDENSE + + @property + def message(self) -> str: + return self.content diff --git a/openhands/events/serialization/observation.py b/openhands/events/serialization/observation.py index 961c155e8916..f1ee333c019a 100644 --- a/openhands/events/serialization/observation.py +++ b/openhands/events/serialization/observation.py @@ -1,6 +1,9 @@ import copy -from openhands.events.observation.agent import AgentStateChangedObservation +from openhands.events.observation.agent import ( + AgentCondensationObservation, + AgentStateChangedObservation, +) from openhands.events.observation.browse import BrowserOutputObservation from openhands.events.observation.commands import ( CmdOutputMetadata, @@ -32,6 +35,7 @@ ErrorObservation, AgentStateChangedObservation, UserRejectObservation, + AgentCondensationObservation, ) OBSERVATION_TYPE_TO_CLASS = { diff --git a/openhands/memory/__init__.py b/openhands/memory/__init__.py index 12c499c768be..89109ea270a1 100644 --- a/openhands/memory/__init__.py +++ b/openhands/memory/__init__.py @@ -1,4 +1,4 @@ -from openhands.memory.condenser import MemoryCondenser +from openhands.memory.condenser import Condenser from openhands.memory.memory import LongTermMemory -__all__ = ['LongTermMemory', 'MemoryCondenser'] +__all__ = ['LongTermMemory', 'Condenser'] diff --git a/openhands/memory/condenser.py b/openhands/memory/condenser.py index bd48d184305c..6318025171d0 100644 --- a/openhands/memory/condenser.py +++ b/openhands/memory/condenser.py @@ -1,24 +1,409 @@ +from __future__ import annotations + +from abc import ABC, abstractmethod +from contextlib import contextmanager +from typing import Any + +from litellm import supports_response_schema +from pydantic import BaseModel +from typing_extensions import override + +from openhands.controller.state.state import State +from openhands.core.config.condenser_config import ( + AmortizedForgettingCondenserConfig, + CondenserConfig, + LLMAttentionCondenserConfig, + LLMSummarizingCondenserConfig, + NoOpCondenserConfig, + ObservationMaskingCondenserConfig, + RecentEventsCondenserConfig, +) from openhands.core.logger import openhands_logger as logger +from openhands.events.event import Event +from openhands.events.observation import AgentCondensationObservation, Observation from openhands.llm.llm import LLM +CONDENSER_METADATA_KEY = 'condenser_meta' +"""Key identifying where metadata is stored in a `State` object's `extra_data` field.""" + + +def get_condensation_metadata(state: State) -> list[dict[str, Any]]: + """Utility function to retrieve a list of metadata batches from a `State`. + + Args: + state: The state to retrieve metadata from. + + Returns: + list[dict[str, Any]]: A list of metadata batches, each representing a condensation. + """ + if CONDENSER_METADATA_KEY in state.extra_data: + return state.extra_data[CONDENSER_METADATA_KEY] + return [] + + +class Condenser(ABC): + """Abstract condenser interface. + + Condensers take a list of `Event` objects and reduce them into a potentially smaller list. + + Agents can use condensers to reduce the amount of events they need to consider when deciding which action to take. To use a condenser, agents can call the `condensed_history` method on the current `State` being considered and use the results instead of the full history. + + Example usage:: + + condenser = Condenser.from_config(condenser_config) + events = condenser.condensed_history(state) + """ + + def __init__(self): + self._metadata_batch: dict[str, Any] = {} + + def add_metadata(self, key: str, value: Any) -> None: + """Add information to the current metadata batch. + + Any key/value pairs added to the metadata batch will be recorded in the `State` at the end of the current condensation. + + Args: + key: The key to store the metadata under. + + value: The metadata to store. + """ + self._metadata_batch[key] = value + + def write_metadata(self, state: State) -> None: + """Write the current batch of metadata to the `State`. + + Resets the current metadata batch: any metadata added after this call will be stored in a new batch and written to the `State` at the end of the next condensation. + """ + if CONDENSER_METADATA_KEY not in state.extra_data: + state.extra_data[CONDENSER_METADATA_KEY] = [] + if self._metadata_batch: + state.extra_data[CONDENSER_METADATA_KEY].append(self._metadata_batch) + + # Since the batch has been written, clear it for the next condensation + self._metadata_batch = {} + + @contextmanager + def metadata_batch(self, state: State): + """Context manager to ensure batched metadata is always written to the `State`.""" + try: + yield + finally: + self.write_metadata(state) + + @abstractmethod + def condense(self, events: list[Event]) -> list[Event]: + """Condense a sequence of events into a potentially smaller list. + + New condenser strategies should override this method to implement their own condensation logic. Call `self.add_metadata` in the implementation to record any relevant per-condensation diagnostic information. + + Args: + events: A list of events representing the entire history of the agent. + + Returns: + list[Event]: An event sequence representing a condensed history of the agent. + """ + + def condensed_history(self, state: State) -> list[Event]: + """Condense the state's history.""" + with self.metadata_batch(state): + return self.condense(state.history) + + @classmethod + def from_config(cls, config: CondenserConfig) -> Condenser: + """Create a condenser from a configuration object. + + Args: + config: Configuration for the condenser. + + Returns: + Condenser: A condenser instance. + + Raises: + ValueError: If the condenser type is not recognized. + """ + match config: + case NoOpCondenserConfig(): + return NoOpCondenser() + + case ObservationMaskingCondenserConfig(): + return ObservationMaskingCondenser( + **config.model_dump(exclude=['type']) + ) + + case RecentEventsCondenserConfig(): + return RecentEventsCondenser(**config.model_dump(exclude=['type'])) + + case LLMSummarizingCondenserConfig(llm_config=llm_config): + return LLMSummarizingCondenser(llm=LLM(config=llm_config)) + + case AmortizedForgettingCondenserConfig(): + return AmortizedForgettingCondenser( + **config.model_dump(exclude=['type']) + ) + + case LLMAttentionCondenserConfig(llm_config=llm_config): + return LLMAttentionCondenser( + llm=LLM(config=llm_config), + **config.model_dump(exclude=['type', 'llm_config']), + ) + + case _: + raise ValueError(f'Unknown condenser config: {config}') + + +class RollingCondenser(Condenser, ABC): + """Base class for a specialized condenser strategy that applies condensation to a rolling history. + + The rolling history is computed by appending new events to the most recent condensation. For example, the sequence of calls:: + + assert state.history == [event1, event2, event3] + condensation = condenser.condensed_history(state) + + # ...new events are added to the state... + + assert state.history == [event1, event2, event3, event4, event5] + condenser.condensed_history(state) + + will result in second call to `condensed_history` passing `condensation + [event4, event5]` to the `condense` method. + """ + + def __init__(self) -> None: + self._condensation: list[Event] = [] + self._last_history_length: int = 0 + + super().__init__() + + @override + def condensed_history(self, state: State) -> list[Event]: + new_events = state.history[self._last_history_length :] + + with self.metadata_batch(state): + results = self.condense(self._condensation + new_events) + + self._condensation = results + self._last_history_length = len(state.history) -class MemoryCondenser: - def condense(self, summarize_prompt: str, llm: LLM): - """Attempts to condense the memory by using the llm + return results - Parameters: - - llm (LLM): llm to be used for summarization + +class NoOpCondenser(Condenser): + """A condenser that does nothing to the event sequence.""" + + def condense(self, events: list[Event]) -> list[Event]: + """Returns the list of events unchanged.""" + return events + + +class ObservationMaskingCondenser(Condenser): + """A condenser that masks the values of observations outside of a recent attention window.""" + + def __init__(self, attention_window: int = 5): + self.attention_window = attention_window + + super().__init__() + + def condense(self, events: list[Event]) -> list[Event]: + """Replace the content of observations outside of the attention window with a placeholder.""" + results: list[Event] = [] + for i, event in enumerate(events): + if ( + isinstance(event, Observation) + and i < len(events) - self.attention_window + ): + results.append(AgentCondensationObservation('')) + else: + results.append(event) + + return results + + +class RecentEventsCondenser(Condenser): + """A condenser that only keeps a certain number of the most recent events.""" + + def __init__(self, keep_first: int = 0, max_events: int = 10): + self.keep_first = keep_first + self.max_events = max_events + + super().__init__() + + def condense(self, events: list[Event]) -> list[Event]: + """Keep only the most recent events (up to `max_events`).""" + head = events[: self.keep_first] + tail_length = max(0, self.max_events - len(head)) + tail = events[-tail_length:] + return head + tail + + +class LLMSummarizingCondenser(Condenser): + """A condenser that relies on a language model to summarize the event sequence as a single event.""" + + def __init__(self, llm: LLM): + self.llm = llm + + super().__init__() + + def condense(self, events: list[Event]) -> list[Event]: + """Applies an LLM to summarize the list of events. Raises: - - Exception: the same exception as it got from the llm or processing the response + Exception: If the LLM is unable to summarize the event sequence. """ try: - messages = [{'content': summarize_prompt, 'role': 'user'}] - resp = llm.completion(messages=messages) - summary_response = resp['choices'][0]['message']['content'] - return summary_response + # Convert events to a format suitable for summarization + events_text = '\n'.join(f'{e.timestamp}: {e.message}' for e in events) + summarize_prompt = f'Please summarize these events:\n{events_text}' + + resp = self.llm.completion( + messages=[{'content': summarize_prompt, 'role': 'user'}] + ) + summary_response = resp.choices[0].message.content + + # Create a new summary event with the condensed content + summary_event = AgentCondensationObservation(summary_response) + + # Add metrics to state + self.add_metadata('response', resp.model_dump()) + self.add_metadata('metrics', self.llm.metrics.get()) + + return [summary_event] + except Exception as e: - logger.error('Error condensing thoughts: %s', str(e), exc_info=False) + logger.error('Error condensing events: %s', str(e), exc_info=False) + raise e + + +class AmortizedForgettingCondenser(RollingCondenser): + """A condenser that maintains a condensed history and forgets old events when it grows too large.""" + + def __init__(self, max_size: int = 100, keep_first: int = 0): + """Initialize the condenser. + + Args: + max_size: Maximum size of history before forgetting. + keep_first: Number of initial events to always keep. + + Raises: + ValueError: If keep_first is greater than max_size, keep_first is negative, or max_size is non-positive. + """ + if keep_first >= max_size // 2: + raise ValueError( + f'keep_first ({keep_first}) must be less than half of max_size ({max_size})' + ) + if keep_first < 0: + raise ValueError(f'keep_first ({keep_first}) cannot be negative') + if max_size < 1: + raise ValueError(f'max_size ({keep_first}) cannot be non-positive') + + self.max_size = max_size + self.keep_first = keep_first + + super().__init__() + + def condense(self, events: list[Event]) -> list[Event]: + """Apply the amortized forgetting strategy to the given list of events.""" + if len(events) <= self.max_size: + return events + + target_size = self.max_size // 2 + head = events[: self.keep_first] + + events_from_tail = target_size - len(head) + tail = events[-events_from_tail:] + + return head + tail + + +class ImportantEventSelection(BaseModel): + """Utility class for the `LLMAttentionCondenser` that forces the LLM to return a list of integers.""" + + ids: list[int] + + +class LLMAttentionCondenser(RollingCondenser): + """Rolling condenser strategy that uses an LLM to select the most important events when condensing the history.""" + + def __init__(self, llm: LLM, max_size: int = 100, keep_first: int = 0): + if keep_first >= max_size // 2: + raise ValueError( + f'keep_first ({keep_first}) must be less than half of max_size ({max_size})' + ) + if keep_first < 0: + raise ValueError(f'keep_first ({keep_first}) cannot be negative') + if max_size < 1: + raise ValueError(f'max_size ({keep_first}) cannot be non-positive') + + self.max_size = max_size + self.keep_first = keep_first + self.llm = llm + + # This condenser relies on the `response_schema` feature, which is not supported by all LLMs + if not supports_response_schema( + model=self.llm.config.model, + custom_llm_provider=self.llm.config.custom_llm_provider, + ): + raise ValueError( + "The LLM model must support the 'response_schema' parameter to use the LLMAttentionCondenser." + ) + + super().__init__() + + def condense(self, events: list[Event]) -> list[Event]: + """If the history is too long, use an LLM to select the most important events.""" + if len(events) <= self.max_size: + return events + + target_size = self.max_size // 2 + head = events[: self.keep_first] + + events_from_tail = target_size - len(head) + + message: str = """You will be given a list of actions, observations, and thoughts from a coding agent. + Each item in the list has an identifier. Please sort the identifiers in order of how important the + contents of the item are for the next step of the coding agent's task, from most important to least + important.""" + + response = self.llm.completion( + messages=[ + {'content': message, 'role': 'user'}, + *[ + { + 'content': f'{e.id}\n{e.message}', + 'role': 'user', + } + for e in events + ], + ], + response_format={ + 'type': 'json_schema', + 'json_schema': { + 'name': 'ImportantEventSelection', + 'schema': ImportantEventSelection.model_json_schema(), + }, + }, + ) + + response_ids = ImportantEventSelection.model_validate_json( + response.choices[0].message.content + ).ids + + self.add_metadata('all_event_ids', [event.id for event in events]) + self.add_metadata('response_ids', response_ids) + self.add_metadata('metrics', self.llm.metrics.get()) + + # Filter out any IDs from the head and trim the results down + head_ids = [event.id for event in head] + response_ids = [ + response_id for response_id in response_ids if response_id not in head_ids + ][:events_from_tail] + + # If the response IDs aren't _long_ enough, iterate backwards through the events and add any unfound IDs to the list. + for event in reversed(events): + if len(response_ids) >= events_from_tail: + break + if event.id not in response_ids: + response_ids.append(event.id) + + # Grab the events associated with the response IDs + tail = [event for event in events if event.id in response_ids] - # TODO If the llm fails with ContextWindowExceededError, we can try to condense the memory chunk by chunk - raise + return head + tail diff --git a/poetry.lock b/poetry.lock index e7cd99236ee3..26b48eba7de8 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,99 +1,99 @@ -# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. 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b/tests/unit/test_codeact_agent.py @@ -1,6 +1,7 @@ from unittest.mock import Mock import pytest +from litellm import ChatCompletionMessageToolCall from openhands.agenthub.codeact_agent.codeact_agent import CodeActAgent from openhands.agenthub.codeact_agent.function_calling import ( @@ -15,6 +16,7 @@ get_tools, response_to_actions, ) +from openhands.controller.state.state import State from openhands.core.config import AgentConfig, LLMConfig from openhands.core.exceptions import FunctionCallNotExistsError from openhands.core.message import ImageContent, TextContent @@ -48,6 +50,15 @@ def agent() -> CodeActAgent: return agent +@pytest.fixture +def mock_state() -> State: + state = Mock(spec=State) + state.history = [] + state.extra_data = {} + + return state + + def test_cmd_output_observation_message(agent: CodeActAgent): agent.config.function_calling = False obs = CmdOutputObservation( @@ -481,7 +492,7 @@ def test_response_to_actions_invalid_tool(): response_to_actions(mock_response) -def test_step_with_no_pending_actions(): +def test_step_with_no_pending_actions(mock_state: State): # Mock the LLM response mock_response = Mock() mock_response.id = 'mock_id' @@ -502,16 +513,68 @@ def test_step_with_no_pending_actions(): agent = CodeActAgent(llm=llm, config=config) # Test step with no pending actions - state = Mock() - state.history = [] - state.latest_user_message = None - state.latest_user_message_id = None - state.latest_user_message_timestamp = None - state.latest_user_message_cause = None - state.latest_user_message_timeout = None - state.latest_user_message_llm_metrics = None - state.latest_user_message_tool_call_metadata = None - - action = agent.step(state) + mock_state.latest_user_message = None + mock_state.latest_user_message_id = None + mock_state.latest_user_message_timestamp = None + mock_state.latest_user_message_cause = None + mock_state.latest_user_message_timeout = None + mock_state.latest_user_message_llm_metrics = None + mock_state.latest_user_message_tool_call_metadata = None + + action = agent.step(mock_state) assert isinstance(action, MessageAction) assert action.content == 'Task completed' + + +def test_mismatched_tool_call_events(mock_state: State): + """Tests that the agent can convert mismatched tool call events (i.e., an observation with no corresponding action) into messages.""" + agent = CodeActAgent(llm=LLM(LLMConfig()), config=AgentConfig()) + + tool_call_metadata = Mock( + spec=ToolCallMetadata, + model_response=Mock( + id='model_response_0', + choices=[ + Mock( + message=Mock( + role='assistant', + content='', + tool_calls=[ + Mock(spec=ChatCompletionMessageToolCall, id='tool_call_0') + ], + ) + ) + ], + ), + tool_call_id='tool_call_0', + function_name='foo', + ) + + action = CmdRunAction('foo') + action._source = 'agent' + action.tool_call_metadata = tool_call_metadata + + observation = CmdOutputObservation(content='', command_id=0, command='foo') + observation.tool_call_metadata = tool_call_metadata + + # When both events are provided, the agent should get three messages: + # 1. The system message, + # 2. The action message, and + # 3. The observation message + mock_state.history = [action, observation] + messages = agent._get_messages(mock_state) + assert len(messages) == 3 + + # The same should hold if the events are presented out-of-order + mock_state.history = [observation, action] + messages = agent._get_messages(mock_state) + assert len(messages) == 3 + + # If only one of the two events is present, then we should just get the system message + mock_state.history = [action] + messages = agent._get_messages(mock_state) + assert len(messages) == 1 + + mock_state.history = [observation] + messages = agent._get_messages(mock_state) + assert len(messages) == 1 diff --git a/tests/unit/test_condenser.py b/tests/unit/test_condenser.py index 5a8ab72978a5..4aa5afcf7543 100644 --- a/tests/unit/test_condenser.py +++ b/tests/unit/test_condenser.py @@ -1,44 +1,520 @@ -from unittest.mock import Mock, patch +from datetime import datetime +from typing import Any +from unittest.mock import MagicMock import pytest -from openhands.core.exceptions import LLMResponseError -from openhands.llm.llm import LLM -from openhands.memory.condenser import MemoryCondenser +from openhands.controller.state.state import State +from openhands.core.config.condenser_config import ( + AmortizedForgettingCondenserConfig, + LLMAttentionCondenserConfig, + LLMSummarizingCondenserConfig, + NoOpCondenserConfig, + ObservationMaskingCondenserConfig, + RecentEventsCondenserConfig, +) +from openhands.core.config.llm_config import LLMConfig +from openhands.events.event import Event, EventSource +from openhands.events.observation.observation import Observation +from openhands.llm import LLM +from openhands.memory.condenser import ( + AmortizedForgettingCondenser, + Condenser, + ImportantEventSelection, + LLMAttentionCondenser, + LLMSummarizingCondenser, + NoOpCondenser, + ObservationMaskingCondenser, + RecentEventsCondenser, +) + + +def create_test_event( + message: str, timestamp: datetime | None = None, id: int | None = None +) -> Event: + """Create a simple test event.""" + event = Event() + event._message = message + event.timestamp = timestamp if timestamp else datetime.now() + if id: + event._id = id + event._source = EventSource.USER + return event @pytest.fixture -def memory_condenser(): - return MemoryCondenser() +def mock_llm() -> LLM: + """Mocks an LLM object with a utility function for setting and resetting response contents in unit tests.""" + # Create a MagicMock for the LLM object + mock_llm = MagicMock( + spec=LLM, + config=MagicMock( + spec=LLMConfig, model='gpt-4o', api_key='test_key', custom_llm_provider=None + ), + metrics=MagicMock(), + ) + _mock_content = None + + # Set a mock message with the mocked content + mock_message = MagicMock() + mock_message.content = _mock_content + + def set_mock_response_content(content: Any): + """Set the mock response for the LLM.""" + nonlocal mock_message + mock_message.content = content + + mock_choice = MagicMock() + mock_choice.message = mock_message + + mock_response = MagicMock() + mock_response.choices = [mock_choice] + + mock_llm.completion.return_value = mock_response + + # Attach helper methods to the mock object + mock_llm.set_mock_response_content = set_mock_response_content + + return mock_llm @pytest.fixture -def mock_llm(): - return Mock(spec=LLM) - - -def test_condense_success(memory_condenser, mock_llm): - mock_llm.completion.return_value = { - 'choices': [{'message': {'content': 'Condensed memory'}}] - } - result = memory_condenser.condense('Summarize this', mock_llm) - assert result == 'Condensed memory' - mock_llm.completion.assert_called_once_with( - messages=[{'content': 'Summarize this', 'role': 'user'}] +def mock_state() -> State: + """Mocks a State object with the only parameters needed for testing condensers: history and extra_data.""" + mock_state = MagicMock(spec=State) + mock_state.history = [] + mock_state.extra_data = {} + + return mock_state + + +def test_noop_condenser_from_config(): + """Test that the NoOpCondenser objects can be made from config.""" + config = NoOpCondenserConfig() + condenser = Condenser.from_config(config) + + assert isinstance(condenser, NoOpCondenser) + + +def test_noop_condenser(): + """Test that NoOpCondensers preserve their input events.""" + events = [ + create_test_event('Event 1'), + create_test_event('Event 2'), + create_test_event('Event 3'), + ] + + mock_state = MagicMock() + mock_state.history = events + + condenser = NoOpCondenser() + result = condenser.condensed_history(mock_state) + + assert result == events + + +def test_observation_masking_condenser_from_config(): + """Test that ObservationMaskingCondenser objects can be made from config.""" + attention_window = 5 + config = ObservationMaskingCondenserConfig(attention_window=attention_window) + condenser = Condenser.from_config(config) + + assert isinstance(condenser, ObservationMaskingCondenser) + assert condenser.attention_window == attention_window + + +def test_observation_masking_condenser_respects_attention_window(mock_state): + """Test that ObservationMaskingCondenser only masks events outside the attention window.""" + attention_window = 3 + condenser = ObservationMaskingCondenser(attention_window=attention_window) + + events = [ + create_test_event('Event 1'), + Observation('Observation 1'), + create_test_event('Event 3'), + create_test_event('Event 4'), + Observation('Observation 2'), + ] + + mock_state.history = events + result = condenser.condensed_history(mock_state) + + assert len(result) == len(events) + + for index, (event, condensed_event) in enumerate(zip(events, result)): + # If we're outside the attention window, observations should be masked. + if index < len(events) - attention_window: + if isinstance(event, Observation): + assert '' in str(condensed_event) + + # If we're within the attention window, events are unchanged. + else: + assert event == condensed_event + + +def test_recent_events_condenser_from_config(): + """Test that RecentEventsCondenser objects can be made from config.""" + max_events = 5 + keep_first = True + config = RecentEventsCondenserConfig(keep_first=keep_first, max_events=max_events) + condenser = Condenser.from_config(config) + + assert isinstance(condenser, RecentEventsCondenser) + assert condenser.max_events == max_events + assert condenser.keep_first == keep_first + + +def test_recent_events_condenser(): + """Test that RecentEventsCondensers keep just the most recent events.""" + events = [ + create_test_event('Event 1'), + create_test_event('Event 2'), + create_test_event('Event 3'), + create_test_event('Event 4'), + create_test_event('Event 5'), + ] + + mock_state = MagicMock() + mock_state.history = events + + # If the max_events are larger than the number of events, equivalent to a NoOpCondenser. + condenser = RecentEventsCondenser(max_events=len(events)) + result = condenser.condensed_history(mock_state) + + assert result == events + + # If the max_events are smaller than the number of events, only keep the last few. + max_events = 2 + condenser = RecentEventsCondenser(max_events=max_events) + result = condenser.condensed_history(mock_state) + + assert len(result) == max_events + assert result[0]._message == 'Event 4' + assert result[1]._message == 'Event 5' + + # If the keep_first flag is set, the first event will always be present. + keep_first = 1 + max_events = 2 + condenser = RecentEventsCondenser(keep_first=keep_first, max_events=max_events) + result = condenser.condensed_history(mock_state) + + assert len(result) == max_events + assert result[0]._message == 'Event 1' + assert result[1]._message == 'Event 5' + + # We should be able to keep more of the initial events. + keep_first = 2 + max_events = 3 + condenser = RecentEventsCondenser(keep_first=keep_first, max_events=max_events) + result = condenser.condensed_history(mock_state) + + assert len(result) == max_events + assert result[0]._message == 'Event 1' + assert result[1]._message == 'Event 2' + assert result[2]._message == 'Event 5' + + +def test_llm_condenser_from_config(): + """Test that LLMCondensers can be made from config.""" + config = LLMSummarizingCondenserConfig( + llm_config=LLMConfig( + model='gpt-4o', + api_key='test_key', + ) ) + condenser = Condenser.from_config(config) + assert isinstance(condenser, LLMSummarizingCondenser) + assert condenser.llm.config.model == 'gpt-4o' + assert condenser.llm.config.api_key == 'test_key' -def test_condense_exception(memory_condenser, mock_llm): - mock_llm.completion.side_effect = LLMResponseError('LLM error') - with pytest.raises(LLMResponseError, match='LLM error'): - memory_condenser.condense('Summarize this', mock_llm) +def test_llm_condenser(mock_llm, mock_state): + """Test that LLMCondensers use the LLM to generate a summary event.""" + events = [ + create_test_event('Event 1'), + create_test_event('Event 2'), + ] + mock_state.history = events -@patch('openhands.memory.condenser.logger') -def test_condense_logs_error(mock_logger, memory_condenser, mock_llm): - mock_llm.completion.side_effect = LLMResponseError('LLM error') - with pytest.raises(LLMResponseError): - memory_condenser.condense('Summarize this', mock_llm) - mock_logger.error.assert_called_once_with( - 'Error condensing thoughts: %s', 'LLM error', exc_info=False + mock_llm.metrics = MagicMock() + mock_llm.metrics.get.return_value = {'test_metric': 1.0} + + mock_llm.set_mock_response_content('Summary of events') + + condenser = LLMSummarizingCondenser(llm=mock_llm) + result = condenser.condensed_history(mock_state) + + assert len(result) == 1 + assert result[0].content == 'Summary of events' + + # Verify LLM was called with correct prompt. + mock_llm.completion.assert_called_once() + call_args = mock_llm.completion.call_args[1] + assert 'messages' in call_args + assert len(call_args['messages']) == 1 + assert 'Event 1' in call_args['messages'][0]['content'] + assert 'Event 2' in call_args['messages'][0]['content'] + + # Verify metrics were added to state + assert 'condenser_meta' in mock_state.extra_data + assert len(mock_state.extra_data['condenser_meta']) == 1 + assert mock_state.extra_data['condenser_meta'][0]['metrics'] == {'test_metric': 1.0} + + +def test_llm_condenser_error(): + """Test that LLM errors are propagated during condensation.""" + events = [create_test_event('Event 1', datetime(2024, 1, 1, 10, 0))] + + mock_state = MagicMock() + mock_state.history = events + + mock_llm = MagicMock() + mock_llm.completion.side_effect = Exception('LLM error') + + condenser = LLMSummarizingCondenser(llm=mock_llm) + + try: + condenser.condensed_history(mock_state) + raise AssertionError('Expected exception was not raised.') + except Exception as e: + assert str(e) == 'LLM error' + + +def test_amortized_forgetting_condenser_from_config(): + """Test that AmortizedForgettingCondenser objects can be made from config.""" + max_size = 50 + keep_first = 10 + config = AmortizedForgettingCondenserConfig( + max_size=max_size, keep_first=keep_first ) + condenser = Condenser.from_config(config) + + assert isinstance(condenser, AmortizedForgettingCondenser) + assert condenser.max_size == max_size + assert condenser.keep_first == keep_first + + +def test_amortized_forgetting_condenser_invalid_config(): + """Test that AmortizedForgettingCondenser raises error when keep_first > max_size.""" + pytest.raises(ValueError, AmortizedForgettingCondenser, max_size=4, keep_first=2) + pytest.raises(ValueError, AmortizedForgettingCondenser, max_size=0) + pytest.raises(ValueError, AmortizedForgettingCondenser, keep_first=-1) + + +def test_amortized_forgetting_condenser_grows_to_max_size(): + """Test that AmortizedForgettingCondenser correctly maintains an event context up to max size.""" + max_size = 15 + condenser = AmortizedForgettingCondenser(max_size=max_size) + + mock_state = MagicMock() + mock_state.extra_data = {} + mock_state.history = [] + + for i in range(max_size): + event = create_test_event(f'Event {i}') + mock_state.history.append(event) + results = condenser.condensed_history(mock_state) + assert len(results) == i + 1 + + +def test_amortized_forgetting_condenser_forgets_when_larger_than_max_size(): + """Test that the AmortizedForgettingCondenser forgets events when the context grows too large.""" + max_size = 2 + condenser = AmortizedForgettingCondenser(max_size=max_size) + + mock_state = MagicMock() + mock_state.extra_data = {} + mock_state.history = [] + + for i in range(max_size * 10): + event = create_test_event(f'Event {i}') + mock_state.history.append(event) + results = condenser.condensed_history(mock_state) + + # The last event in the results is always the event we just added. + assert results[-1] == event + + # The number of results should bounce back and forth between 1, 2, 1, 2, ... + assert len(results) == (i % 2) + 1 + + +def test_amortized_forgetting_condenser_keeps_first_events(): + """Test that the AmortizedForgettingCondenser keeps the right number of initial events when forgetting.""" + max_size = 4 + keep_first = 1 + condenser = AmortizedForgettingCondenser(max_size=max_size, keep_first=keep_first) + + first_event = create_test_event('Event 0') + + mock_state = MagicMock() + mock_state.extra_data = {} + mock_state.history = [first_event] + + for i in range(max_size * 10): + event = create_test_event(f'Event {i+1}', datetime(2024, 1, 1, 10, i + 1)) + mock_state.history.append(event) + results = condenser.condensed_history(mock_state) + + # The last event is always the event we just added. + assert results[-1] == event + + # The first event is always the first event. + assert results[0] == first_event + + # The number of results should bounce back between 2, 3, 4, 2, 3, 4, ... + print(len(results)) + assert len(results) == (i % 3) + 2 + + +def test_llm_attention_condenser_from_config(): + """Test that LLMAttentionCondenser objects can be made from config.""" + config = LLMAttentionCondenserConfig( + max_size=50, + keep_first=10, + llm_config=LLMConfig( + model='gpt-4o', + api_key='test_key', + ), + ) + condenser = Condenser.from_config(config) + + assert isinstance(condenser, LLMAttentionCondenser) + assert condenser.llm.config.model == 'gpt-4o' + assert condenser.llm.config.api_key == 'test_key' + assert condenser.max_size == 50 + assert condenser.keep_first == 10 + + +def test_llm_attention_condenser_invalid_config(): + """Test that LLMAttentionCondenser raises an error if the configured LLM doesn't support response schema.""" + config = LLMAttentionCondenserConfig( + max_size=50, + keep_first=10, + llm_config=LLMConfig( + model='claude-2', # Older model that doesn't support response schema + api_key='test_key', + ), + ) + + pytest.raises(ValueError, LLMAttentionCondenser.from_config, config) + + +def test_llm_attention_condenser_keeps_first_events(mock_llm, mock_state): + """Test that the LLMAttentionCondenser keeps the right number of initial events when forgetting.""" + max_size = 4 + condenser = LLMAttentionCondenser(max_size=max_size, keep_first=1, llm=mock_llm) + + first_event = create_test_event('Event 0', id=0) + mock_state.history.append(first_event) + + for i in range(max_size * 10): + event = create_test_event(f'Event {i+1}', id=i + 1) + mock_state.history.append(event) + + mock_llm.set_mock_response_content( + ImportantEventSelection( + ids=[event.id for event in mock_state.history] + ).model_dump_json() + ) + results = condenser.condensed_history(mock_state) + + # The first event is always the first event. + assert results[0] == first_event + + +def test_llm_attention_condenser_grows_to_max_size(mock_llm, mock_state): + """Test that LLMAttentionCondenser correctly maintains an event context up to max size.""" + max_size = 15 + condenser = LLMAttentionCondenser(max_size=max_size, llm=mock_llm) + + for i in range(max_size): + event = create_test_event(f'Event {i}') + mock_state.history.append(event) + mock_llm.set_mock_response_content( + ImportantEventSelection(ids=[event.id for event in mock_state.history]) + ) + results = condenser.condensed_history(mock_state) + assert len(results) == i + 1 + + +def test_llm_attention_condenser_forgets_when_larger_than_max_size( + mock_llm, mock_state +): + """Test that the LLMAttentionCondenser forgets events when the context grows too large.""" + max_size = 2 + condenser = LLMAttentionCondenser(max_size=max_size, llm=mock_llm) + + for i in range(max_size * 10): + event = create_test_event(f'Event {i}', id=i) + mock_state.history.append(event) + + mock_llm.set_mock_response_content( + ImportantEventSelection( + ids=[event.id for event in mock_state.history] + ).model_dump_json() + ) + + results = condenser.condensed_history(mock_state) + + # The number of results should bounce back and forth between 1, 2, 1, 2, ... + assert len(results) == (i % 2) + 1 + + +def test_llm_attention_condenser_handles_events_outside_history(mock_llm, mock_state): + """Test that the LLMAttentionCondenser handles event IDs that aren't from the event history.""" + max_size = 2 + condenser = LLMAttentionCondenser(max_size=max_size, llm=mock_llm) + + for i in range(max_size * 10): + event = create_test_event(f'Event {i}', id=i) + mock_state.history.append(event) + + mock_llm.set_mock_response_content( + ImportantEventSelection( + ids=[event.id for event in mock_state.history] + [-1, -2, -3, -4] + ).model_dump_json() + ) + results = condenser.condensed_history(mock_state) + + # The number of results should bounce back and forth between 1, 2, 1, 2, ... + assert len(results) == (i % 2) + 1 + + +def test_llm_attention_condenser_handles_too_many_events(mock_llm, mock_state): + """Test that the LLMAttentionCondenser handles when the response contains too many event IDs.""" + max_size = 2 + condenser = LLMAttentionCondenser(max_size=max_size, llm=mock_llm) + + for i in range(max_size * 10): + event = create_test_event(f'Event {i}', id=i) + mock_state.history.append(event) + mock_llm.set_mock_response_content( + ImportantEventSelection( + ids=[event.id for event in mock_state.history] + + [event.id for event in mock_state.history] + ).model_dump_json() + ) + results = condenser.condensed_history(mock_state) + + # The number of results should bounce back and forth between 1, 2, 1, 2, ... + assert len(results) == (i % 2) + 1 + + +def test_llm_attention_condenser_handles_too_few_events(mock_llm, mock_state): + """Test that the LLMAttentionCondenser handles when the response contains too few event IDs.""" + max_size = 2 + condenser = LLMAttentionCondenser(max_size=max_size, llm=mock_llm) + + for i in range(max_size * 10): + event = create_test_event(f'Event {i}', id=i) + mock_state.history.append(event) + + mock_llm.set_mock_response_content( + ImportantEventSelection(ids=[]).model_dump_json() + ) + + results = condenser.condensed_history(mock_state) + + # The number of results should bounce back and forth between 1, 2, 1, 2, ... + assert len(results) == (i % 2) + 1 diff --git a/tests/unit/test_config.py b/tests/unit/test_config.py index d1306ca63114..44a76145cf6e 100644 --- a/tests/unit/test_config.py +++ b/tests/unit/test_config.py @@ -13,6 +13,9 @@ load_from_env, load_from_toml, ) +from openhands.core.config.condenser_config import ( + NoOpCondenserConfig, +) from openhands.core.logger import openhands_logger @@ -618,6 +621,13 @@ def test_cache_dir_creation(default_config, tmpdir): assert os.path.exists(default_config.cache_dir) +def test_agent_config_condenser_default(): + """Test that default agent condenser is NoOpCondenser.""" + config = AppConfig() + agent_config = config.get_agent_config() + assert isinstance(agent_config.condenser, NoOpCondenserConfig) + + def test_api_keys_repr_str(): # Test LLMConfig llm_config = LLMConfig( diff --git a/tests/unit/test_prompt_caching.py b/tests/unit/test_prompt_caching.py index 7e577c2bca5e..ea4eeb59935d 100644 --- a/tests/unit/test_prompt_caching.py +++ b/tests/unit/test_prompt_caching.py @@ -75,7 +75,7 @@ def test_get_messages(codeact_agent: CodeActAgent): codeact_agent.reset() messages = codeact_agent._get_messages( - Mock(history=history, max_iterations=5, iteration=0) + Mock(history=history, max_iterations=5, iteration=0, extra_data={}) ) assert ( @@ -111,7 +111,7 @@ def test_get_messages_prompt_caching(codeact_agent: CodeActAgent): codeact_agent.reset() messages = codeact_agent._get_messages( - Mock(history=history, max_iterations=10, iteration=5) + Mock(history=history, max_iterations=10, iteration=5, extra_data={}) ) # Check that only the last two user messages have cache_prompt=True @@ -144,6 +144,7 @@ def test_prompt_caching_headers(codeact_agent: CodeActAgent): mock_state.history = history mock_state.max_iterations = 5 mock_state.iteration = 0 + mock_state.extra_data = {} codeact_agent.reset()