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feat:mysql adaptation for metadb (#28188)

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longbingljw
2025-11-20 09:44:39 +08:00
committed by GitHub
parent 012877d8d4
commit c0b7ffd5d0
131 changed files with 6312 additions and 2602 deletions
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64
api/core/rag/retrieval/dataset_retrieval.py
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@@ -7,8 +7,7 @@ from collections.abc import Generator, Mapping
from typing import Any, Union, cast
from flask import Flask, current_app
from sqlalchemy import Float, and_, or_, select, text
from sqlalchemy import cast as sqlalchemy_cast
from sqlalchemy import and_, or_, select
from core.app.app_config.entities import (
DatasetEntity,
@@ -1023,60 +1022,55 @@ class DatasetRetrieval:
self, sequence: int, condition: str, metadata_name: str, value: Any | None, filters: list
):
if value is None and condition not in ("empty", "not empty"):
return
return filters
json_field = DatasetDocument.doc_metadata[metadata_name].as_string()
key = f"{metadata_name}_{sequence}"
key_value = f"{metadata_name}_{sequence}_value"
match condition:
case "contains":
filters.append(
(text(f"documents.doc_metadata ->> :{key} LIKE :{key_value}")).params(
**{key: metadata_name, key_value: f"%{value}%"}
)
)
filters.append(json_field.like(f"%{value}%"))
case "not contains":
filters.append(
(text(f"documents.doc_metadata ->> :{key} NOT LIKE :{key_value}")).params(
**{key: metadata_name, key_value: f"%{value}%"}
)
)
filters.append(json_field.notlike(f"%{value}%"))
case "start with":
filters.append(
(text(f"documents.doc_metadata ->> :{key} LIKE :{key_value}")).params(
**{key: metadata_name, key_value: f"{value}%"}
)
)
filters.append(json_field.like(f"{value}%"))
case "end with":
filters.append(
(text(f"documents.doc_metadata ->> :{key} LIKE :{key_value}")).params(
**{key: metadata_name, key_value: f"%{value}"}
)
)
filters.append(json_field.like(f"%{value}"))
case "is" | "=":
if isinstance(value, str):
filters.append(DatasetDocument.doc_metadata[metadata_name] == f'"{value}"')
else:
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) == value)
filters.append(json_field == value)
elif isinstance(value, (int, float)):
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() == value)
case "is not" | "≠":
if isinstance(value, str):
filters.append(DatasetDocument.doc_metadata[metadata_name] != f'"{value}"')
else:
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) != value)
filters.append(json_field != value)
elif isinstance(value, (int, float)):
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() != value)
case "empty":
filters.append(DatasetDocument.doc_metadata[metadata_name].is_(None))
case "not empty":
filters.append(DatasetDocument.doc_metadata[metadata_name].isnot(None))
case "before" | "<":
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) < value)
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() < value)
case "after" | ">":
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) > value)
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() > value)
case "≤" | "<=":
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) <= value)
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() <= value)
case "≥" | ">=":
filters.append(sqlalchemy_cast(DatasetDocument.doc_metadata[metadata_name].astext, Float) >= value)
filters.append(DatasetDocument.doc_metadata[metadata_name].as_float() >= value)
case _:
pass
return filters
def _fetch_model_config(