mirror of
https://gitee.com/wanwujie/deer-flow
synced 2026-04-02 22:02:13 +08:00
* feat: add configurable log level and token usage tracking - Add `log_level` config to control deerflow module log level, synced to LangGraph Server via serve.sh `--server-log-level` - Add `token_usage.enabled` config with TokenUsageMiddleware that logs input/output/total tokens per LLM call from usage_metadata - Add .omc/ to .gitignore * fix: use info level for token usage logs since feature has its own toggle * fix: sort imports to pass lint check --------- Co-authored-by: greatmengqi <chenmengqi.0376@bytedance.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
339 lines
13 KiB
Python
339 lines
13 KiB
Python
import logging
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import os
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from pathlib import Path
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from typing import Any, Self
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import yaml
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from dotenv import load_dotenv
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from pydantic import BaseModel, ConfigDict, Field
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from deerflow.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict
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from deerflow.config.extensions_config import ExtensionsConfig
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from deerflow.config.guardrails_config import load_guardrails_config_from_dict
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from deerflow.config.memory_config import load_memory_config_from_dict
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from deerflow.config.model_config import ModelConfig
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from deerflow.config.sandbox_config import SandboxConfig
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from deerflow.config.skills_config import SkillsConfig
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from deerflow.config.subagents_config import load_subagents_config_from_dict
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from deerflow.config.summarization_config import load_summarization_config_from_dict
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from deerflow.config.title_config import load_title_config_from_dict
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from deerflow.config.token_usage_config import TokenUsageConfig
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from deerflow.config.tool_config import ToolConfig, ToolGroupConfig
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from deerflow.config.tool_search_config import ToolSearchConfig, load_tool_search_config_from_dict
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load_dotenv()
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logger = logging.getLogger(__name__)
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class AppConfig(BaseModel):
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"""Config for the DeerFlow application"""
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log_level: str = Field(default="info", description="Logging level for deerflow modules (debug/info/warning/error)")
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token_usage: TokenUsageConfig = Field(default_factory=TokenUsageConfig, description="Token usage tracking configuration")
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models: list[ModelConfig] = Field(default_factory=list, description="Available models")
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sandbox: SandboxConfig = Field(description="Sandbox configuration")
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tools: list[ToolConfig] = Field(default_factory=list, description="Available tools")
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tool_groups: list[ToolGroupConfig] = Field(default_factory=list, description="Available tool groups")
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skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration")
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extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)")
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tool_search: ToolSearchConfig = Field(default_factory=ToolSearchConfig, description="Tool search / deferred loading configuration")
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model_config = ConfigDict(extra="allow", frozen=False)
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checkpointer: CheckpointerConfig | None = Field(default=None, description="Checkpointer configuration")
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@classmethod
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def resolve_config_path(cls, config_path: str | None = None) -> Path:
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"""Resolve the config file path.
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Priority:
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1. If provided `config_path` argument, use it.
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2. If provided `DEER_FLOW_CONFIG_PATH` environment variable, use it.
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3. Otherwise, first check the `config.yaml` in the current directory, then fallback to `config.yaml` in the parent directory.
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"""
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if config_path:
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path = Path(config_path)
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if not Path.exists(path):
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raise FileNotFoundError(f"Config file specified by param `config_path` not found at {path}")
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return path
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elif os.getenv("DEER_FLOW_CONFIG_PATH"):
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path = Path(os.getenv("DEER_FLOW_CONFIG_PATH"))
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if not Path.exists(path):
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raise FileNotFoundError(f"Config file specified by environment variable `DEER_FLOW_CONFIG_PATH` not found at {path}")
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return path
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else:
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# Check if the config.yaml is in the current directory
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path = Path(os.getcwd()) / "config.yaml"
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if not path.exists():
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# Check if the config.yaml is in the parent directory of CWD
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path = Path(os.getcwd()).parent / "config.yaml"
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if not path.exists():
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raise FileNotFoundError("`config.yaml` file not found at the current directory nor its parent directory")
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return path
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@classmethod
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def from_file(cls, config_path: str | None = None) -> Self:
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"""Load config from YAML file.
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See `resolve_config_path` for more details.
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Args:
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config_path: Path to the config file.
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Returns:
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AppConfig: The loaded config.
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"""
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resolved_path = cls.resolve_config_path(config_path)
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with open(resolved_path, encoding="utf-8") as f:
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config_data = yaml.safe_load(f) or {}
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# Check config version before processing
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cls._check_config_version(config_data, resolved_path)
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config_data = cls.resolve_env_variables(config_data)
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# Load title config if present
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if "title" in config_data:
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load_title_config_from_dict(config_data["title"])
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# Load summarization config if present
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if "summarization" in config_data:
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load_summarization_config_from_dict(config_data["summarization"])
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# Load memory config if present
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if "memory" in config_data:
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load_memory_config_from_dict(config_data["memory"])
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# Load subagents config if present
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if "subagents" in config_data:
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load_subagents_config_from_dict(config_data["subagents"])
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# Load tool_search config if present
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if "tool_search" in config_data:
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load_tool_search_config_from_dict(config_data["tool_search"])
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# Load guardrails config if present
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if "guardrails" in config_data:
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load_guardrails_config_from_dict(config_data["guardrails"])
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# Load checkpointer config if present
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if "checkpointer" in config_data:
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load_checkpointer_config_from_dict(config_data["checkpointer"])
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# Load extensions config separately (it's in a different file)
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extensions_config = ExtensionsConfig.from_file()
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config_data["extensions"] = extensions_config.model_dump()
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result = cls.model_validate(config_data)
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return result
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@classmethod
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def _check_config_version(cls, config_data: dict, config_path: Path) -> None:
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"""Check if the user's config.yaml is outdated compared to config.example.yaml.
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Emits a warning if the user's config_version is lower than the example's.
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Missing config_version is treated as version 0 (pre-versioning).
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"""
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try:
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user_version = int(config_data.get("config_version", 0))
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except (TypeError, ValueError):
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user_version = 0
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# Find config.example.yaml by searching config.yaml's directory and its parents
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example_path = None
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search_dir = config_path.parent
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for _ in range(5): # search up to 5 levels
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candidate = search_dir / "config.example.yaml"
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if candidate.exists():
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example_path = candidate
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break
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parent = search_dir.parent
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if parent == search_dir:
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break
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search_dir = parent
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if example_path is None:
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return
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try:
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with open(example_path, encoding="utf-8") as f:
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example_data = yaml.safe_load(f)
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raw = example_data.get("config_version", 0) if example_data else 0
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try:
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example_version = int(raw)
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except (TypeError, ValueError):
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example_version = 0
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except Exception:
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return
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if user_version < example_version:
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logger.warning(
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"Your config.yaml (version %d) is outdated — the latest version is %d. Run `make config-upgrade` to merge new fields into your config.",
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user_version,
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example_version,
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)
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@classmethod
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def resolve_env_variables(cls, config: Any) -> Any:
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"""Recursively resolve environment variables in the config.
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Environment variables are resolved using the `os.getenv` function. Example: $OPENAI_API_KEY
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Args:
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config: The config to resolve environment variables in.
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Returns:
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The config with environment variables resolved.
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"""
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if isinstance(config, str):
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if config.startswith("$"):
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env_value = os.getenv(config[1:])
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if env_value is None:
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raise ValueError(f"Environment variable {config[1:]} not found for config value {config}")
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return env_value
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return config
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elif isinstance(config, dict):
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return {k: cls.resolve_env_variables(v) for k, v in config.items()}
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elif isinstance(config, list):
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return [cls.resolve_env_variables(item) for item in config]
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return config
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def get_model_config(self, name: str) -> ModelConfig | None:
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"""Get the model config by name.
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Args:
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name: The name of the model to get the config for.
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Returns:
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The model config if found, otherwise None.
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"""
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return next((model for model in self.models if model.name == name), None)
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def get_tool_config(self, name: str) -> ToolConfig | None:
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"""Get the tool config by name.
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Args:
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name: The name of the tool to get the config for.
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Returns:
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The tool config if found, otherwise None.
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"""
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return next((tool for tool in self.tools if tool.name == name), None)
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def get_tool_group_config(self, name: str) -> ToolGroupConfig | None:
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"""Get the tool group config by name.
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Args:
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name: The name of the tool group to get the config for.
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Returns:
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The tool group config if found, otherwise None.
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"""
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return next((group for group in self.tool_groups if group.name == name), None)
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_app_config: AppConfig | None = None
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_app_config_path: Path | None = None
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_app_config_mtime: float | None = None
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_app_config_is_custom = False
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def _get_config_mtime(config_path: Path) -> float | None:
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"""Get the modification time of a config file if it exists."""
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try:
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return config_path.stat().st_mtime
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except OSError:
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return None
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def _load_and_cache_app_config(config_path: str | None = None) -> AppConfig:
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"""Load config from disk and refresh cache metadata."""
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global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
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resolved_path = AppConfig.resolve_config_path(config_path)
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_app_config = AppConfig.from_file(str(resolved_path))
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_app_config_path = resolved_path
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_app_config_mtime = _get_config_mtime(resolved_path)
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_app_config_is_custom = False
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return _app_config
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def get_app_config() -> AppConfig:
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"""Get the DeerFlow config instance.
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Returns a cached singleton instance and automatically reloads it when the
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underlying config file path or modification time changes. Use
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`reload_app_config()` to force a reload, or `reset_app_config()` to clear
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the cache.
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"""
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global _app_config, _app_config_path, _app_config_mtime
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if _app_config is not None and _app_config_is_custom:
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return _app_config
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resolved_path = AppConfig.resolve_config_path()
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current_mtime = _get_config_mtime(resolved_path)
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should_reload = (
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_app_config is None
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or _app_config_path != resolved_path
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or _app_config_mtime != current_mtime
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)
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if should_reload:
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if (
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_app_config_path == resolved_path
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and _app_config_mtime is not None
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and current_mtime is not None
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and _app_config_mtime != current_mtime
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):
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logger.info(
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"Config file has been modified (mtime: %s -> %s), reloading AppConfig",
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_app_config_mtime,
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current_mtime,
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)
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_load_and_cache_app_config(str(resolved_path))
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return _app_config
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def reload_app_config(config_path: str | None = None) -> AppConfig:
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"""Reload the config from file and update the cached instance.
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This is useful when the config file has been modified and you want
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to pick up the changes without restarting the application.
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Args:
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config_path: Optional path to config file. If not provided,
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uses the default resolution strategy.
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Returns:
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The newly loaded AppConfig instance.
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"""
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return _load_and_cache_app_config(config_path)
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def reset_app_config() -> None:
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"""Reset the cached config instance.
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This clears the singleton cache, causing the next call to
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`get_app_config()` to reload from file. Useful for testing
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or when switching between different configurations.
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"""
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global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
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_app_config = None
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_app_config_path = None
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_app_config_mtime = None
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_app_config_is_custom = False
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def set_app_config(config: AppConfig) -> None:
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"""Set a custom config instance.
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This allows injecting a custom or mock config for testing purposes.
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Args:
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config: The AppConfig instance to use.
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"""
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global _app_config, _app_config_path, _app_config_mtime, _app_config_is_custom
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_app_config = config
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_app_config_path = None
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_app_config_mtime = None
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_app_config_is_custom = True
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