import logging import os from pathlib import Path from typing import Any, Self import yaml from dotenv import load_dotenv from pydantic import BaseModel, ConfigDict, Field from deerflow.config.acp_config import load_acp_config_from_dict from deerflow.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict from deerflow.config.extensions_config import ExtensionsConfig from deerflow.config.guardrails_config import load_guardrails_config_from_dict from deerflow.config.memory_config import load_memory_config_from_dict from deerflow.config.model_config import ModelConfig from deerflow.config.sandbox_config import SandboxConfig from deerflow.config.skills_config import SkillsConfig from deerflow.config.subagents_config import load_subagents_config_from_dict from deerflow.config.summarization_config import load_summarization_config_from_dict from deerflow.config.title_config import load_title_config_from_dict from deerflow.config.token_usage_config import TokenUsageConfig from deerflow.config.tool_config import ToolConfig, ToolGroupConfig from deerflow.config.tool_search_config import ToolSearchConfig, load_tool_search_config_from_dict load_dotenv() logger = logging.getLogger(__name__) class AppConfig(BaseModel): """Config for the DeerFlow application""" log_level: str = Field(default="info", description="Logging level for deerflow modules (debug/info/warning/error)") token_usage: TokenUsageConfig = Field(default_factory=TokenUsageConfig, description="Token usage tracking configuration") models: list[ModelConfig] = Field(default_factory=list, description="Available models") sandbox: SandboxConfig = Field(description="Sandbox configuration") tools: list[ToolConfig] = Field(default_factory=list, description="Available tools") tool_groups: list[ToolGroupConfig] = Field(default_factory=list, description="Available tool groups") skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration") extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)") tool_search: ToolSearchConfig = Field(default_factory=ToolSearchConfig, description="Tool search / deferred loading configuration") model_config = ConfigDict(extra="allow", frozen=False) checkpointer: CheckpointerConfig | None = Field(default=None, description="Checkpointer configuration") @classmethod def resolve_config_path(cls, config_path: str | None = None) -> Path: """Resolve the config file path. Priority: 1. If provided `config_path` argument, use it. 2. If provided `DEER_FLOW_CONFIG_PATH` environment variable, use it. 3. Otherwise, first check the `config.yaml` in the current directory, then fallback to `config.yaml` in the parent directory. """ if config_path: path = Path(config_path) if not Path.exists(path): raise FileNotFoundError(f"Config file specified by param `config_path` not found at {path}") return path elif os.getenv("DEER_FLOW_CONFIG_PATH"): path = Path(os.getenv("DEER_FLOW_CONFIG_PATH")) if not Path.exists(path): raise FileNotFoundError(f"Config file specified by environment variable `DEER_FLOW_CONFIG_PATH` not found at {path}") return path else: # Check if the config.yaml is in the current directory path = Path(os.getcwd()) / "config.yaml" if not path.exists(): # Check if the config.yaml is in the parent directory of CWD path = Path(os.getcwd()).parent / "config.yaml" if not path.exists(): raise FileNotFoundError("`config.yaml` file not found at the current directory nor its parent directory") return path @classmethod def from_file(cls, config_path: str | None = None) -> Self: """Load config from YAML file. See `resolve_config_path` for more details. Args: config_path: Path to the config file. Returns: AppConfig: The loaded config. """ resolved_path = cls.resolve_config_path(config_path) with open(resolved_path, encoding="utf-8") as f: config_data = yaml.safe_load(f) or {} # Check config version before processing cls._check_config_version(config_data, resolved_path) config_data = cls.resolve_env_variables(config_data) # Load title config if present if "title" in config_data: load_title_config_from_dict(config_data["title"]) # Load summarization config if present if "summarization" in config_data: load_summarization_config_from_dict(config_data["summarization"]) # Load memory config if present if "memory" in config_data: load_memory_config_from_dict(config_data["memory"]) # Load subagents config if present if "subagents" in config_data: load_subagents_config_from_dict(config_data["subagents"]) # Load tool_search config if present if "tool_search" in config_data: load_tool_search_config_from_dict(config_data["tool_search"]) # Load guardrails config if present if "guardrails" in config_data: load_guardrails_config_from_dict(config_data["guardrails"]) # Load checkpointer config if present if "checkpointer" in config_data: load_checkpointer_config_from_dict(config_data["checkpointer"]) # Always refresh ACP agent config so removed entries do not linger across reloads. load_acp_config_from_dict(config_data.get("acp_agents", {})) # Load extensions config separately (it's in a different file) extensions_config = ExtensionsConfig.from_file() config_data["extensions"] = extensions_config.model_dump() result = cls.model_validate(config_data) return result @classmethod def _check_config_version(cls, config_data: dict, config_path: Path) -> None: """Check if the user's config.yaml is outdated compared to config.example.yaml. Emits a warning if the user's config_version is lower than the example's. Missing config_version is treated as version 0 (pre-versioning). """ try: user_version = int(config_data.get("config_version", 0)) except (TypeError, ValueError): user_version = 0 # Find config.example.yaml by searching config.yaml's directory and its parents example_path = None search_dir = config_path.parent for _ in range(5): # search up to 5 levels candidate = search_dir / "config.example.yaml" if candidate.exists(): example_path = candidate break parent = search_dir.parent if parent == search_dir: break search_dir = parent if example_path is None: return try: with open(example_path, encoding="utf-8") as f: example_data = yaml.safe_load(f) raw = example_data.get("config_version", 0) if example_data else 0 try: example_version = int(raw) except (TypeError, ValueError): example_version = 0 except Exception: return if user_version < example_version: logger.warning( "Your config.yaml (version %d) is outdated — the latest version is %d. Run `make config-upgrade` to merge new fields into your config.", user_version, example_version, ) @classmethod def resolve_env_variables(cls, config: Any) -> Any: """Recursively resolve environment variables in the config. Environment variables are resolved using the `os.getenv` function. Example: $OPENAI_API_KEY Args: config: The config to resolve environment variables in. Returns: The config with environment variables resolved. """ if isinstance(config, str): if config.startswith("$"): env_value = os.getenv(config[1:]) if env_value is None: raise ValueError(f"Environment variable {config[1:]} not found for config value {config}") return env_value return config elif isinstance(config, dict): return {k: cls.resolve_env_variables(v) for k, v in config.items()} elif isinstance(config, list): return [cls.resolve_env_variables(item) for item in config] return config def get_model_config(self, name: str) -> ModelConfig | None: """Get the model config by name. Args: name: The name of the model to get the config for. Returns: The model config if found, otherwise None. """ return next((model for model in self.models if model.name == name), None) def get_tool_config(self, name: str) -> ToolConfig | None: """Get the tool config by name. Args: name: The name of the tool to get the config for. Returns: The tool config if found, otherwise None. """ return next((tool for tool in self.tools if tool.name == name), None) def get_tool_group_config(self, name: str) -> ToolGroupConfig | None: """Get the tool group config by name. Args: name: The name of the tool group to get the config for. Returns: The tool group config if found, otherwise None. """ return next((group for group in self.tool_groups if group.name == name), None) _app_config: AppConfig | None = None _app_config_path: Path | None = None _app_config_mtime: float | None = None _app_config_is_custom = False def _get_config_mtime(config_path: Path) -> float | None: """Get the modification time of a config file if it exists.""" try: return config_path.stat().st_mtime except OSError: return None def _load_and_cache_app_config(config_path: str | None = None) -> AppConfig: """Load config from disk and refresh cache metadata.""" global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom resolved_path = AppConfig.resolve_config_path(config_path) _app_config = AppConfig.from_file(str(resolved_path)) _app_config_path = resolved_path _app_config_mtime = _get_config_mtime(resolved_path) _app_config_is_custom = False return _app_config def get_app_config() -> AppConfig: """Get the DeerFlow config instance. Returns a cached singleton instance and automatically reloads it when the underlying config file path or modification time changes. Use `reload_app_config()` to force a reload, or `reset_app_config()` to clear the cache. """ global _app_config, _app_config_path, _app_config_mtime if _app_config is not None and _app_config_is_custom: return _app_config resolved_path = AppConfig.resolve_config_path() current_mtime = _get_config_mtime(resolved_path) should_reload = _app_config is None or _app_config_path != resolved_path or _app_config_mtime != current_mtime if should_reload: if _app_config_path == resolved_path and _app_config_mtime is not None and current_mtime is not None and _app_config_mtime != current_mtime: logger.info( "Config file has been modified (mtime: %s -> %s), reloading AppConfig", _app_config_mtime, current_mtime, ) _load_and_cache_app_config(str(resolved_path)) return _app_config def reload_app_config(config_path: str | None = None) -> AppConfig: """Reload the config from file and update the cached instance. This is useful when the config file has been modified and you want to pick up the changes without restarting the application. Args: config_path: Optional path to config file. If not provided, uses the default resolution strategy. Returns: The newly loaded AppConfig instance. """ return _load_and_cache_app_config(config_path) def reset_app_config() -> None: """Reset the cached config instance. This clears the singleton cache, causing the next call to `get_app_config()` to reload from file. Useful for testing or when switching between different configurations. """ global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom _app_config = None _app_config_path = None _app_config_mtime = None _app_config_is_custom = False def set_app_config(config: AppConfig) -> None: """Set a custom config instance. This allows injecting a custom or mock config for testing purposes. Args: config: The AppConfig instance to use. """ global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom _app_config = config _app_config_path = None _app_config_mtime = None _app_config_is_custom = True