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ac8b5e7934
Co-authored-by: openhands <openhands@all-hands.dev> Co-authored-by: Boxuan Li <liboxuan@connect.hku.hk>
99 lines
4.5 KiB
Python
99 lines
4.5 KiB
Python
from __future__ import annotations
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from pydantic import BaseModel, Field, ValidationError
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from openhands.core.config.condenser_config import CondenserConfig, NoOpCondenserConfig
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from openhands.core.logger import openhands_logger as logger
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class AgentConfig(BaseModel):
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"""Configuration for the agent.
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Attributes:
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function_calling: Whether function calling is enabled. Default is True.
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codeact_enable_browsing: Whether browsing delegate is enabled in the action space. Default is False. Only works with function calling.
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codeact_enable_llm_editor: Whether LLM editor is enabled in the action space. Default is False. Only works with function calling.
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codeact_enable_jupyter: Whether Jupyter is enabled in the action space. Default is False.
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llm_config: The name of the llm config to use. If specified, this will override global llm config.
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enable_prompt_extensions: Whether to use prompt extensions (e.g., microagents, inject runtime info). Default is True.
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disabled_microagents: A list of microagents to disable (by name, without .py extension, e.g. ["github", "lint"]). Default is None.
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condenser: Configuration for the memory condenser. Default is NoOpCondenserConfig.
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enable_history_truncation: Whether history should be truncated to continue the session when hitting LLM context length limit.
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enable_som_visual_browsing: Whether to enable SoM (Set of Marks) visual browsing. Default is False.
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"""
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llm_config: str | None = Field(default=None)
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codeact_enable_browsing: bool = Field(default=True)
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codeact_enable_llm_editor: bool = Field(default=False)
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codeact_enable_jupyter: bool = Field(default=True)
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enable_prompt_extensions: bool = Field(default=True)
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disabled_microagents: list[str] = Field(default_factory=list)
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enable_history_truncation: bool = Field(default=True)
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enable_som_visual_browsing: bool = Field(default=True)
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condenser: CondenserConfig = Field(
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default_factory=lambda: NoOpCondenserConfig(type='noop')
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)
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model_config = {'extra': 'forbid'}
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@classmethod
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def from_toml_section(cls, data: dict) -> dict[str, AgentConfig]:
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"""
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Create a mapping of AgentConfig instances from a toml dictionary representing the [agent] section.
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The default configuration is built from all non-dict keys in data.
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Then, each key with a dict value is treated as a custom agent configuration, and its values override
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the default configuration.
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Example:
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Apply generic agent config with custom agent overrides, e.g.
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[agent]
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enable_prompt_extensions = false
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[agent.BrowsingAgent]
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enable_prompt_extensions = true
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results in prompt_extensions being true for BrowsingAgent but false for others.
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Returns:
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dict[str, AgentConfig]: A mapping where the key "agent" corresponds to the default configuration
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and additional keys represent custom configurations.
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"""
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# Initialize the result mapping
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agent_mapping: dict[str, AgentConfig] = {}
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# Extract base config data (non-dict values)
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base_data = {}
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custom_sections: dict[str, dict] = {}
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for key, value in data.items():
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if isinstance(value, dict):
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custom_sections[key] = value
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else:
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base_data[key] = value
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# Try to create the base config
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try:
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base_config = cls.model_validate(base_data)
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agent_mapping['agent'] = base_config
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except ValidationError as e:
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logger.warning(f'Invalid base agent configuration: {e}. Using defaults.')
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# If base config fails, create a default one
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base_config = cls()
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# Still add it to the mapping
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agent_mapping['agent'] = base_config
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# Process each custom section independently
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for name, overrides in custom_sections.items():
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try:
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# Merge base config with overrides
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merged = {**base_config.model_dump(), **overrides}
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custom_config = cls.model_validate(merged)
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agent_mapping[name] = custom_config
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except ValidationError as e:
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logger.warning(
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f'Invalid agent configuration for [{name}]: {e}. This section will be skipped.'
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)
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# Skip this custom section but continue with others
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continue
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return agent_mapping
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