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chore: import upstream snapshot with attribution
2026-07-13 13:03:45 +08:00

33 行
1.6 KiB
Python

from typing import Any, Dict
from pydantic import BaseModel, ConfigDict, Field, model_validator
class ValkeyConfig(BaseModel):
"""Configuration for Valkey vector store."""
valkey_url: str = Field(..., description="Valkey server URL (e.g., redis://localhost:6379)")
collection_name: str = Field(..., description="Name of the index / collection")
embedding_model_dims: int = Field(..., description="Dimensions of the embedding model")
timezone: str = Field("UTC", description="Timezone for timestamp handling")
index_type: str = Field("hnsw", description="Index type: 'hnsw' (default) or 'flat'")
hnsw_m: int = Field(16, description="HNSW: number of connections per layer")
hnsw_ef_construction: int = Field(200, description="HNSW: search width during index construction")
hnsw_ef_runtime: int = Field(10, description="HNSW: search width during queries")
cluster_mode: bool = Field(False, description="Enable cluster mode for Valkey cluster (CME) deployments")
@model_validator(mode="before")
@classmethod
def validate_extra_fields(cls, values: Dict[str, Any]) -> Dict[str, Any]:
allowed_fields = set(cls.model_fields.keys())
input_fields = set(values.keys())
extra_fields = input_fields - allowed_fields
if extra_fields:
raise ValueError(
f"Extra fields not allowed: {', '.join(extra_fields)}. "
f"Please input only the following fields: {', '.join(allowed_fields)}"
)
return values
model_config = ConfigDict(arbitrary_types_allowed=False)