greatmengqi
edf345cd72
- Freeze all config models (AppConfig + 15 sub-configs) with frozen=True - Purify from_file() — remove 9 load_*_from_dict() side-effect calls - Replace mtime/reload/push/pop machinery with single ContextVar + init_app_config() - Delete 10 sub-module globals and their getters/setters/loaders - Migrate 50+ consumers from get_*_config() to get_app_config().xxx - Expand DeerFlowContext: app_config + thread_id + agent_name (frozen dataclass) - Wire into Gateway runtime (worker.py) and DeerFlowClient via context= parameter - Remove sandbox_id from runtime.context — flows through ThreadState.sandbox only - Middleware/tools access runtime.context directly via Runtime[DeerFlowContext] generic - resolve_context() retained at server entry points for LangGraph Server fallback
42 lines
2.1 KiB
Python
42 lines
2.1 KiB
Python
from pydantic import BaseModel, ConfigDict, Field
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class ModelConfig(BaseModel):
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"""Config section for a model"""
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name: str = Field(..., description="Unique name for the model")
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display_name: str | None = Field(..., default_factory=lambda: None, description="Display name for the model")
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description: str | None = Field(..., default_factory=lambda: None, description="Description for the model")
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use: str = Field(
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...,
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description="Class path of the model provider(e.g. langchain_openai.ChatOpenAI)",
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)
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model: str = Field(..., description="Model name")
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model_config = ConfigDict(extra="allow", frozen=True)
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use_responses_api: bool | None = Field(
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default=None,
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description="Whether to route OpenAI ChatOpenAI calls through the /v1/responses API",
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)
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output_version: str | None = Field(
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default=None,
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description="Structured output version for OpenAI responses content, e.g. responses/v1",
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)
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supports_thinking: bool = Field(default_factory=lambda: False, description="Whether the model supports thinking")
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supports_reasoning_effort: bool = Field(default_factory=lambda: False, description="Whether the model supports reasoning effort")
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when_thinking_enabled: dict | None = Field(
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default_factory=lambda: None,
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description="Extra settings to be passed to the model when thinking is enabled",
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)
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when_thinking_disabled: dict | None = Field(
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default_factory=lambda: None,
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description="Extra settings to be passed to the model when thinking is disabled",
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)
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supports_vision: bool = Field(default_factory=lambda: False, description="Whether the model supports vision/image inputs")
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thinking: dict | None = Field(
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default_factory=lambda: None,
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description=(
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"Thinking settings for the model. If provided, these settings will be passed to the model when thinking is enabled. "
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"This is a shortcut for `when_thinking_enabled` and will be merged with `when_thinking_enabled` if both are provided."
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),
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)
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