enhance: Migrate PyMilvus orm to MilvusClient

.gitignore

@@ -13,6 +13,9 @@ venv/
 results/
 logs/
 
+# Worktrees
+.worktrees/
+
 # AI rules
 CLAUDE.md
 AGENTS.md

README.md

@@ -27,11 +27,6 @@ python >= 3.11
 pip install vectordb-bench
 ```
 
-**Install all database clients**
-
-``` shell
-pip install 'vectordb-bench[all]'
-```
 **Install the specific database client**
 
 ```shell
@@ -42,7 +37,6 @@ All the database client supported
 | Optional database client | install command                             |
 |--------------------------|---------------------------------------------|
 | pymilvus, zilliz_cloud (*default*)     | `pip install vectordb-bench`                |
-| all (*clients requirements might be conflict with each other*) | `pip install vectordb-bench[all]`           |
 | qdrant                   | `pip install vectordb-bench[qdrant]`        |
 | pinecone                 | `pip install vectordb-bench[pinecone]`      |
 | weaviate                 | `pip install vectordb-bench[weaviate]`      |
@@ -225,7 +219,6 @@ Options:
 
   --ondisk                        Ondisk mode with binary quantization(32x compression)
   --oversample-factor             Controls the degree of oversampling applied to minority classes in imbalanced datasets to improve model performance by balancing class distributions.(default 1.0)
-
 
   # Quantization Type
   --quantization-type TEXT        which type of quantization to use valid values [fp32, fp16, bq]
@@ -294,13 +287,13 @@ Options:
   # Connection
   --cloud-id TEXT                 Elastic Cloud ID  [required]
   --password TEXT                 Elastic Cloud password  [required]
-  
+
   # HNSW Index Parameters
   --m INTEGER                     HNSW M parameter  [default: 16]
   --ef-construction INTEGER       HNSW efConstruction parameter  [default: 100]
   --num-candidates INTEGER        Number of candidates for search  [default: 100]
   --element-type [float|byte]     Element type for vectors (float: 4 bytes, byte: 1 byte)  [default: float]
-  
+
   # Index Configuration
   --number-of-shards INTEGER      Number of shards  [default: 1]
   --number-of-replicas INTEGER    Number of replicas  [default: 0]
@@ -311,7 +304,7 @@ Options:
   --use-routing BOOLEAN           Whether to use routing  [default: False]
   --use-rescore BOOLEAN           Whether to use rescore  [default: False]
   --oversample-ratio FLOAT        Oversample ratio for rescore  [default: 2.0]
-  
+
   # Common Options
   --case-type [CapacityDim128|CapacityDim960|Performance768D100M|...]
                                   Case type

pyproject.toml

@@ -40,7 +40,6 @@ dependencies = [
     "pydantic<v2",
     "scikit-learn",
     "pymilvus", # with pandas, numpy, ujson
-    "ujson",
     "hdrhistogram>=0.10.1",
 ]
 dynamic = ["version"]
@@ -51,37 +50,7 @@ test = [
     "ruff",
     "pytest",
 ]
-restful = [ "flask" ]
-
-all = [
-    "grpcio==1.53.0", # for qdrant-client and pymilvus
-    "grpcio-tools==1.53.0", # for qdrant-client and pymilvus
-    "qdrant-client",
-    "pinecone",
-    "weaviate-client",
-    "elasticsearch",
-    "sqlalchemy",
-    "redis",
-    "chromadb",
-    "pgvector",
-    "psycopg",
-    "psycopg-binary",
-    "pgvecto_rs[psycopg3]>=0.2.2",
-    "opensearch-dsl",
-    "opensearch-py",
-    "memorydb",
-    "alibabacloud_ha3engine_vector",
-    "mariadb",
-    "PyMySQL",
-    "clickhouse-connect",
-    "pyvespa",
-    "lancedb",
-    "mysql-connector-python",
-    "turbopuffer[fast]",
-    'zvec',
-    "endee==0.1.10", # compatible with pydantic<2
-]
-
+restful         = [ "flask" ]
 qdrant          = [ "qdrant-client" ]
 pinecone        = [ "pinecone" ]
 weaviate        = [ "weaviate-client" ]

tests/pytest.ini

@@ -1,4 +1,5 @@
 [pytest]
 
-filterwarnings = 
+filterwarnings =
     ignore::UserWarning
+    ignore::DeprecationWarning

tests/test_bench_runner.py

@@ -1,5 +1,7 @@
 import time
 import logging
+
+import ujson
 from vectordb_bench.interface import BenchMarkRunner
 from vectordb_bench.models import (
     DB, IndexType, CaseType, TaskConfig, CaseConfig,
@@ -55,6 +57,5 @@ def test_performance_case_no_error(self):
         d = t.json(exclude={'db_config': {'password', 'api_key'}})
         log.info(f"{d}")
 
-        import ujson
         loads = ujson.loads(d)
         log.info(f"{loads}")

tests/test_milvus.py

@@ -0,0 +1,39 @@
+"""E2E test for Milvus client using MilvusClient API.
+
+Requires a running Milvus instance at localhost:19530.
+"""
+
+import logging
+
+from pydantic import SecretStr
+
+from vectordb_bench.backend.clients import DB
+from vectordb_bench.backend.clients.api import IndexType
+from vectordb_bench.backend.clients.milvus.config import MilvusConfig
+from vectordb_bench.backend.cases import CaseType
+from vectordb_bench.interface import BenchMarkRunner
+from vectordb_bench.models import CaseConfig, TaskConfig
+
+
+log = logging.getLogger(__name__)
+
+
+class TestMilvus:
+    """E2E test for Milvus using Performance1536D50K (OpenAI 50K dataset)."""
+
+    def test_performance_1536d_50k(self):
+        """Full benchmark: download dataset, insert, optimize (force merge), search."""
+        runner = BenchMarkRunner()
+
+        task_config = TaskConfig(
+            db=DB.Milvus,
+            db_config=MilvusConfig(uri=SecretStr("http://localhost:19530")),
+            db_case_config=DB.Milvus.case_config_cls(index_type=IndexType.Flat)(),
+            case_config=CaseConfig(case_id=CaseType.Performance1536D50K),
+        )
+
+        runner.run([task_config])
+        runner._sync_running_task()
+        result = runner.get_results()
+        log.info(f"test result: {result}")
+        assert len(result) > 0