Forráskód Böngészése

fix: avoid unexpected error when create knowledge base with baidu vector database and wenxin embedding model (#10130)

Shili Cao 5 hónapja
szülő
commit
b61baa87ec

+ 2 - 0
api/configs/middleware/__init__.py

@@ -16,6 +16,7 @@ from configs.middleware.storage.supabase_storage_config import SupabaseStorageCo
 from configs.middleware.storage.tencent_cos_storage_config import TencentCloudCOSStorageConfig
 from configs.middleware.storage.tencent_cos_storage_config import TencentCloudCOSStorageConfig
 from configs.middleware.storage.volcengine_tos_storage_config import VolcengineTOSStorageConfig
 from configs.middleware.storage.volcengine_tos_storage_config import VolcengineTOSStorageConfig
 from configs.middleware.vdb.analyticdb_config import AnalyticdbConfig
 from configs.middleware.vdb.analyticdb_config import AnalyticdbConfig
+from configs.middleware.vdb.baidu_vector_config import BaiduVectorDBConfig
 from configs.middleware.vdb.chroma_config import ChromaConfig
 from configs.middleware.vdb.chroma_config import ChromaConfig
 from configs.middleware.vdb.couchbase_config import CouchbaseConfig
 from configs.middleware.vdb.couchbase_config import CouchbaseConfig
 from configs.middleware.vdb.elasticsearch_config import ElasticsearchConfig
 from configs.middleware.vdb.elasticsearch_config import ElasticsearchConfig
@@ -259,5 +260,6 @@ class MiddlewareConfig(
     UpstashConfig,
     UpstashConfig,
     TidbOnQdrantConfig,
     TidbOnQdrantConfig,
     OceanBaseVectorConfig,
     OceanBaseVectorConfig,
+    BaiduVectorDBConfig,
 ):
 ):
     pass
     pass

+ 26 - 11
api/core/rag/datasource/vdb/baidu/baidu_vector.py

@@ -3,11 +3,13 @@ import time
 import uuid
 import uuid
 from typing import Any
 from typing import Any
 
 
+import numpy as np
 from pydantic import BaseModel, model_validator
 from pydantic import BaseModel, model_validator
 from pymochow import MochowClient
 from pymochow import MochowClient
 from pymochow.auth.bce_credentials import BceCredentials
 from pymochow.auth.bce_credentials import BceCredentials
 from pymochow.configuration import Configuration
 from pymochow.configuration import Configuration
-from pymochow.model.enum import FieldType, IndexState, IndexType, MetricType, TableState
+from pymochow.exception import ServerError
+from pymochow.model.enum import FieldType, IndexState, IndexType, MetricType, ServerErrCode, TableState
 from pymochow.model.schema import Field, HNSWParams, Schema, VectorIndex
 from pymochow.model.schema import Field, HNSWParams, Schema, VectorIndex
 from pymochow.model.table import AnnSearch, HNSWSearchParams, Partition, Row
 from pymochow.model.table import AnnSearch, HNSWSearchParams, Partition, Row
 
 
@@ -116,6 +118,7 @@ class BaiduVector(BaseVector):
         self._db.table(self._collection_name).delete(filter=f"{key} = '{value}'")
         self._db.table(self._collection_name).delete(filter=f"{key} = '{value}'")
 
 
     def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
     def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
+        query_vector = [float(val) if isinstance(val, np.float64) else val for val in query_vector]
         anns = AnnSearch(
         anns = AnnSearch(
             vector_field=self.field_vector,
             vector_field=self.field_vector,
             vector_floats=query_vector,
             vector_floats=query_vector,
@@ -149,7 +152,13 @@ class BaiduVector(BaseVector):
         return docs
         return docs
 
 
     def delete(self) -> None:
     def delete(self) -> None:
-        self._db.drop_table(table_name=self._collection_name)
+        try:
+            self._db.drop_table(table_name=self._collection_name)
+        except ServerError as e:
+            if e.code == ServerErrCode.TABLE_NOT_EXIST:
+                pass
+            else:
+                raise
 
 
     def _init_client(self, config) -> MochowClient:
     def _init_client(self, config) -> MochowClient:
         config = Configuration(credentials=BceCredentials(config.account, config.api_key), endpoint=config.endpoint)
         config = Configuration(credentials=BceCredentials(config.account, config.api_key), endpoint=config.endpoint)
@@ -166,7 +175,14 @@ class BaiduVector(BaseVector):
         if exists:
         if exists:
             return self._client.database(self._client_config.database)
             return self._client.database(self._client_config.database)
         else:
         else:
-            return self._client.create_database(database_name=self._client_config.database)
+            try:
+                self._client.create_database(database_name=self._client_config.database)
+            except ServerError as e:
+                if e.code == ServerErrCode.DB_ALREADY_EXIST:
+                    pass
+                else:
+                    raise
+            return
 
 
     def _table_existed(self) -> bool:
     def _table_existed(self) -> bool:
         tables = self._db.list_table()
         tables = self._db.list_table()
@@ -175,7 +191,7 @@ class BaiduVector(BaseVector):
     def _create_table(self, dimension: int) -> None:
     def _create_table(self, dimension: int) -> None:
         # Try to grab distributed lock and create table
         # Try to grab distributed lock and create table
         lock_name = "vector_indexing_lock_{}".format(self._collection_name)
         lock_name = "vector_indexing_lock_{}".format(self._collection_name)
-        with redis_client.lock(lock_name, timeout=20):
+        with redis_client.lock(lock_name, timeout=60):
             table_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
             table_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
             if redis_client.get(table_exist_cache_key):
             if redis_client.get(table_exist_cache_key):
                 return
                 return
@@ -238,15 +254,14 @@ class BaiduVector(BaseVector):
                 description="Table for Dify",
                 description="Table for Dify",
             )
             )
 
 
+            # Wait for table created
+            while True:
+                time.sleep(1)
+                table = self._db.describe_table(self._collection_name)
+                if table.state == TableState.NORMAL:
+                    break
             redis_client.set(table_exist_cache_key, 1, ex=3600)
             redis_client.set(table_exist_cache_key, 1, ex=3600)
 
 
-        # Wait for table created
-        while True:
-            time.sleep(1)
-            table = self._db.describe_table(self._collection_name)
-            if table.state == TableState.NORMAL:
-                break
-
 
 
 class BaiduVectorFactory(AbstractVectorFactory):
 class BaiduVectorFactory(AbstractVectorFactory):
     def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> BaiduVector:
     def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> BaiduVector:

+ 1 - 43
api/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
 
 [[package]]
 [[package]]
 name = "aiohappyeyeballs"
 name = "aiohappyeyeballs"
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