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fix: use enum .value strings in retrieval-setting API to fix JSON serialization error (#26785)

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Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
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fenglin 2025-10-13 13:01:44 +08:00 committed by GitHub
parent 44d36f2460
commit d1de3cfb94
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1 changed files with 75 additions and 87 deletions
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162
api/controllers/console/datasets/datasets.py
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@ -45,6 +45,79 @@ def _validate_name(name: str) -> str:
return name return name
def _get_retrieval_methods_by_vector_type(vector_type: str | None, is_mock: bool = False) -> dict[str, list[str]]:
"""
Get supported retrieval methods based on vector database type.
Args:
vector_type: Vector database type, can be None
is_mock: Whether this is a Mock API, affects MILVUS handling
Returns:
Dictionary containing supported retrieval methods
Raises:
ValueError: If vector_type is None or unsupported
"""
if vector_type is None:
raise ValueError("Vector store type is not configured.")
# Define vector database types that only support semantic search
semantic_only_types = {
VectorType.RELYT,
VectorType.TIDB_VECTOR,
VectorType.CHROMA,
VectorType.PGVECTO_RS,
VectorType.VIKINGDB,
VectorType.UPSTASH,
}
# Define vector database types that support all retrieval methods
full_search_types = {
VectorType.QDRANT,
VectorType.WEAVIATE,
VectorType.OPENSEARCH,
VectorType.ANALYTICDB,
VectorType.MYSCALE,
VectorType.ORACLE,
VectorType.ELASTICSEARCH,
VectorType.ELASTICSEARCH_JA,
VectorType.PGVECTOR,
VectorType.VASTBASE,
VectorType.TIDB_ON_QDRANT,
VectorType.LINDORM,
VectorType.COUCHBASE,
VectorType.OPENGAUSS,
VectorType.OCEANBASE,
VectorType.TABLESTORE,
VectorType.HUAWEI_CLOUD,
VectorType.TENCENT,
VectorType.MATRIXONE,
VectorType.CLICKZETTA,
VectorType.BAIDU,
VectorType.ALIBABACLOUD_MYSQL,
}
semantic_methods = {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
full_methods = {
"retrieval_method": [
RetrievalMethod.SEMANTIC_SEARCH.value,
RetrievalMethod.FULL_TEXT_SEARCH.value,
RetrievalMethod.HYBRID_SEARCH.value,
]
}
if vector_type == VectorType.MILVUS:
return semantic_methods if is_mock else full_methods
if vector_type in semantic_only_types:
return semantic_methods
elif vector_type in full_search_types:
return full_methods
else:
raise ValueError(f"Unsupported vector db type {vector_type}.")
@console_ns.route("/datasets") @console_ns.route("/datasets")
class DatasetListApi(Resource): class DatasetListApi(Resource):
@api.doc("get_datasets") @api.doc("get_datasets")
@ -777,50 +850,7 @@ class DatasetRetrievalSettingApi(Resource):
@account_initialization_required @account_initialization_required
def get(self): def get(self):
vector_type = dify_config.VECTOR_STORE vector_type = dify_config.VECTOR_STORE
match vector_type: return _get_retrieval_methods_by_vector_type(vector_type, is_mock=False)
case (
VectorType.RELYT
| VectorType.TIDB_VECTOR
| VectorType.CHROMA
| VectorType.PGVECTO_RS
| VectorType.VIKINGDB
| VectorType.UPSTASH
):
return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH]}
case (
VectorType.QDRANT
| VectorType.WEAVIATE
| VectorType.OPENSEARCH
| VectorType.ANALYTICDB
| VectorType.MYSCALE
| VectorType.ORACLE
| VectorType.ELASTICSEARCH
| VectorType.ELASTICSEARCH_JA
| VectorType.PGVECTOR
| VectorType.VASTBASE
| VectorType.TIDB_ON_QDRANT
| VectorType.LINDORM
| VectorType.COUCHBASE
| VectorType.MILVUS
| VectorType.OPENGAUSS
| VectorType.OCEANBASE
| VectorType.TABLESTORE
| VectorType.HUAWEI_CLOUD
| VectorType.TENCENT
| VectorType.MATRIXONE
| VectorType.CLICKZETTA
| VectorType.BAIDU
| VectorType.ALIBABACLOUD_MYSQL
):
return {
"retrieval_method": [
RetrievalMethod.SEMANTIC_SEARCH,
RetrievalMethod.FULL_TEXT_SEARCH,
RetrievalMethod.HYBRID_SEARCH,
]
}
case _:
raise ValueError(f"Unsupported vector db type {vector_type}.")
@console_ns.route("/datasets/retrieval-setting/<string:vector_type>") @console_ns.route("/datasets/retrieval-setting/<string:vector_type>")
@ -833,49 +863,7 @@ class DatasetRetrievalSettingMockApi(Resource):
@login_required @login_required
@account_initialization_required @account_initialization_required
def get(self, vector_type): def get(self, vector_type):
match vector_type: return _get_retrieval_methods_by_vector_type(vector_type, is_mock=True)
case (
VectorType.MILVUS
| VectorType.RELYT
| VectorType.TIDB_VECTOR
| VectorType.CHROMA
| VectorType.PGVECTO_RS
| VectorType.VIKINGDB
| VectorType.UPSTASH
):
return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH]}
case (
VectorType.QDRANT
| VectorType.WEAVIATE
| VectorType.OPENSEARCH
| VectorType.ANALYTICDB
| VectorType.MYSCALE
| VectorType.ORACLE
| VectorType.ELASTICSEARCH
| VectorType.ELASTICSEARCH_JA
| VectorType.COUCHBASE
| VectorType.PGVECTOR
| VectorType.VASTBASE
| VectorType.LINDORM
| VectorType.OPENGAUSS
| VectorType.OCEANBASE
| VectorType.TABLESTORE
| VectorType.TENCENT
| VectorType.HUAWEI_CLOUD
| VectorType.MATRIXONE
| VectorType.CLICKZETTA
| VectorType.BAIDU
| VectorType.ALIBABACLOUD_MYSQL
):
return {
"retrieval_method": [
RetrievalMethod.SEMANTIC_SEARCH,
RetrievalMethod.FULL_TEXT_SEARCH,
RetrievalMethod.HYBRID_SEARCH,
]
}
case _:
raise ValueError(f"Unsupported vector db type {vector_type}.")
@console_ns.route("/datasets/<uuid:dataset_id>/error-docs") @console_ns.route("/datasets/<uuid:dataset_id>/error-docs")