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
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
"""Configuration for automatic thread title generation."""
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from pydantic import BaseModel, ConfigDict, Field
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class TitleConfig(BaseModel):
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"""Configuration for automatic thread title generation."""
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model_config = ConfigDict(frozen=True)
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enabled: bool = Field(
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default=True,
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description="Whether to enable automatic title generation",
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)
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max_words: int = Field(
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default=6,
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ge=1,
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le=20,
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description="Maximum number of words in the generated title",
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)
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max_chars: int = Field(
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default=60,
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ge=10,
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le=200,
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description="Maximum number of characters in the generated title",
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)
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model_name: str | None = Field(
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default=None,
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description="Model name to use for title generation (None = use default model)",
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)
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prompt_template: str = Field(
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default=("Generate a concise title (max {max_words} words) for this conversation.\nUser: {user_msg}\nAssistant: {assistant_msg}\n\nReturn ONLY the title, no quotes, no explanation."),
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description="Prompt template for title generation",
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)
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