Bump pyobvector to 0.2.15 (#24120)
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@@ -4,8 +4,8 @@ import math
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from typing import Any
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from pydantic import BaseModel, model_validator
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from pyobvector import VECTOR, ObVecClient # type: ignore
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from sqlalchemy import JSON, Column, String, func
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from pyobvector import VECTOR, FtsIndexParam, FtsParser, ObVecClient, l2_distance # type: ignore
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from sqlalchemy import JSON, Column, String
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from sqlalchemy.dialects.mysql import LONGTEXT
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from configs import dify_config
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@@ -119,14 +119,21 @@ class OceanBaseVector(BaseVector):
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)
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try:
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if self._hybrid_search_enabled:
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self._client.perform_raw_text_sql(f"""ALTER TABLE {self._collection_name}
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ADD FULLTEXT INDEX fulltext_index_for_col_text (text) WITH PARSER ik""")
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self._client.create_fts_idx_with_fts_index_param(
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table_name=self._collection_name,
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fts_idx_param=FtsIndexParam(
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index_name="fulltext_index_for_col_text",
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field_names=["text"],
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parser_type=FtsParser.IK,
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),
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)
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except Exception as e:
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raise Exception(
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"Failed to add fulltext index to the target table, your OceanBase version must be 4.3.5.1 or above "
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+ "to support fulltext index and vector index in the same table",
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e,
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)
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self._client.refresh_metadata([self._collection_name])
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redis_client.set(collection_exist_cache_key, 1, ex=3600)
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def _check_hybrid_search_support(self) -> bool:
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@@ -252,7 +259,7 @@ class OceanBaseVector(BaseVector):
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vec_column_name="vector",
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vec_data=query_vector,
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topk=topk,
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distance_func=func.l2_distance,
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distance_func=l2_distance,
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output_column_names=["text", "metadata"],
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with_dist=True,
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where_clause=_where_clause,
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