feat: Add abstract base class for vector database integration

- Created `VectorDBBase` as an abstract base class to standardize vector database operations.
- Added required methods for common vector database operations: `has_collection`, `delete_collection`, `insert`, `upsert`, `search`, `query`, `get`, `delete`, `reset`.
- The base class can now be extended by any vector database implementation (e.g., Qdrant, Pinecone) to ensure a consistent API across different database systems.

backend/open_webui/retrieval/vector/dbs/elasticsearch.py

@@ -2,7 +2,12 @@ from elasticsearch import Elasticsearch, BadRequestError
 from typing import Optional
 import ssl
 from elasticsearch.helpers import bulk, scan
-from open_webui.retrieval.vector.main import VectorItem, SearchResult, GetResult
+from open_webui.retrieval.vector.main import (
+    VectorDBBase,
+    VectorItem,
+    SearchResult,
+    GetResult,
+)
 from open_webui.config import (
     ELASTICSEARCH_URL,
     ELASTICSEARCH_CA_CERTS,
@@ -15,7 +20,7 @@ from open_webui.config import (
 )
 
 
-class ElasticsearchClient:
+class ElasticsearchClient(VectorDBBase):
     """
     Important:
     in order to reduce the number of indexes and since the embedding vector length is fixed, we avoid creating