2026-1-6

venv/Lib/site-packages/dashvector/util/__init__.py

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+##
+#   Copyright 2021 Alibaba, Inc. and its affiliates. All Rights Reserved.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+#
+##
+
+# -*- coding: utf-8 -*-

venv/Lib/site-packages/dashvector/util/convertor.py

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+#   Copyright 2021 Alibaba, Inc. and its affiliates. All Rights Reserved.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+#
+##
+import collections
+import json
+
+# -*- coding: utf-8 -*-
+from typing import Dict, Optional
+
+from dashvector.util.validator import verify_sparse_vector
+
+
+def to_sorted_sparse_vector(sparse_vector: Optional[Dict[int, float]]) -> Optional[Dict[int, float]]:
+    if sparse_vector is None:
+        return
+    verify_sparse_vector(sparse_vector)
+    return dict(sorted(sparse_vector.items()))
+
+def to_sorted_sparse_vectors(sparse_vectors: Optional[Dict[str, Dict[int, float]]]) -> Optional[Dict[str, Dict[int, float]]]:
+    if sparse_vectors is None:
+        return
+    sorted_sparse_vectors = dict()
+    for key in sparse_vectors.keys():
+        sparse_vector = sparse_vectors[key]
+        verify_sparse_vector(sparse_vector)
+        sorted_sparse_vectors[key] = dict(sorted(sparse_vector.items()))
+
+    return sorted_sparse_vectors
+
+def to_json_without_ascii(obj) -> str:
+    return json.dumps(obj, ensure_ascii=False)

venv/Lib/site-packages/dashvector/util/validator.py

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+##
+#   Copyright 2021 Alibaba, Inc. and its affiliates. All Rights Reserved.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#       http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+#
+##
+
+# -*- coding: utf-8 -*-
+
+import re
+from typing import Dict, List, Optional, Union
+
+import numpy as np
+
+from dashvector.common.error import DashVectorCode, DashVectorException
+
+ENDPOINT_PATTERN = "^([a-zA-Z0-9-.]+)\.([a-z\.]{2,6})\/?$"
+UINT32_MAXVALUE = 2**32 - 1
+
+
+def verify_endpoint(endpoint: Optional[str]) -> bool:
+    """Verify endpoint is valid
+
+    verify_endpoint("dashvector.cn-hangzhou.aliyuncs.com") -> True
+    """
+    return endpoint and re.search(ENDPOINT_PATTERN, endpoint) is not None
+
+
+def verify_sparse_vector(sparse_vector: Dict[int, float]):
+    """Verify sparse vector
+
+    Verify sparse vector type and indices exceed max value of uint32
+    """
+    # TODO
+    #  1. SDK错误码需要重新开一个区间，解决gateway和sdk维护同区间错误码带来的混乱。
+    #  2. model下的参数校验收敛到该文件中实现复用
+    # 1. check sparse vector type
+    if not isinstance(sparse_vector, dict):
+        raise DashVectorException(
+            code=DashVectorCode.InvalidArgument,
+            reason=f"DashVectorSDK sparse_vector type({type(sparse_vector)}) is invalid and must be Dict[int, float]",
+        )
+
+    for key, value in sparse_vector.items():
+        # 2. check sparse vector key and value type (dict:[int, float])
+        if not isinstance(key, int) or not isinstance(value, float):
+            raise DashVectorException(
+                code=DashVectorCode.InvalidArgument,
+                reason="DashVectorSDK sparse_vector is invalid and must be Dict[int, float]",
+            )
+
+        # 3. check sparse indices exceed max value of uint32
+        if key > UINT32_MAXVALUE or key < 0:
+            raise DashVectorException(
+                code=DashVectorCode.InvalidSparseIndices,
+                reason=f"Sparse vector indices({key}) is invalid and must be in [0, {UINT32_MAXVALUE}]",
+            )
+
+
+def vector_is_empty(vector: Union[List[int], List[float], np.ndarray]) -> bool:
+    """Verify vector is empty"""
+    if isinstance(vector, list):
+        return not vector
+    if isinstance(vector, np.ndarray):
+        return vector.size == 0
+    return True