47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from __future__ import annotations
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from src.config.config import global_config, model_config
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def resolve_embedding_dimension(fallback: int | None = None, *, sync_global: bool = True) -> int | None:
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"""获取当前配置的嵌入向量维度。
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优先顺序：
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1. 模型配置中 `model_task_config.embedding.embedding_dimension`
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2. 机器人配置中 `lpmm_knowledge.embedding_dimension`
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3. 调用方提供的 fallback
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"""
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candidates: list[int | None] = []
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if model_config is not None:
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try:
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embedding_task = getattr(model_config.model_task_config, "embedding", None)
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if embedding_task is not None:
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candidates.append(getattr(embedding_task, "embedding_dimension", None))
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except Exception:
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candidates.append(None)
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else:
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candidates.append(None)
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if global_config is not None:
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try:
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candidates.append(getattr(global_config.lpmm_knowledge, "embedding_dimension", None))
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except Exception:
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candidates.append(None)
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else:
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candidates.append(None)
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candidates.append(fallback)
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resolved: int | None = next((int(dim) for dim in candidates if dim and int(dim) > 0), None)
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if resolved and sync_global and global_config is not None:
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try:
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if getattr(global_config.lpmm_knowledge, "embedding_dimension", None) != resolved:
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global_config.lpmm_knowledge.embedding_dimension = resolved # type: ignore[attr-defined]
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except Exception:
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pass
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return resolved
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