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milvus.ipynb

@@ -0,0 +1,335 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pymilvus import connections, db\n",
+    "\n",
+    "conn = connections.connect(host=\"127.0.0.1\", port=19530)\n",
+    "\n",
+    "database = db.create_database(\"my_database\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['default', 'my_database']"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "db.list_database()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'auto_id': False, 'description': '', 'fields': [{'name': 'my_id', 'description': '', 'type': <DataType.INT64: 5>, 'is_primary': True, 'auto_id': False}, {'name': 'my_vector', 'description': '', 'type': <DataType.FLOAT_VECTOR: 101>, 'params': {'dim': 5}}, {'name': 'my_varchar', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 512}}], 'enable_dynamic_field': True}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pymilvus import MilvusClient, DataType\n",
+    "\n",
+    "client = MilvusClient(\n",
+    "    uri=\"http://localhost:19530\",\n",
+    "    token=\"root:Milvus\"\n",
+    ")\n",
+    "\n",
+    "schema = MilvusClient.create_schema(\n",
+    "    auto_id=False,\n",
+    "    enable_dynamic_field=True,\n",
+    ")\n",
+    "\n",
+    "schema.add_field(field_name=\"my_id\", datatype=DataType.INT64, is_primary=True)\n",
+    "schema.add_field(field_name=\"my_vector\", datatype=DataType.FLOAT_VECTOR, dim=5)\n",
+    "schema.add_field(field_name=\"my_varchar\", datatype=DataType.VARCHAR, max_length=512)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "index_params = client.prepare_index_params()\n",
+    "index_params.add_index(\n",
+    "    field_name=\"my_vector\", \n",
+    "    index_type=\"AUTOINDEX\",\n",
+    "    metric_type=\"COSINE\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'state': <LoadState: Loaded>}\n"
+     ]
+    }
+   ],
+   "source": [
+    "client.create_collection(\n",
+    "    collection_name=\"customized_setup_1\",\n",
+    "    schema=schema,\n",
+    "    index_params=index_params\n",
+    ")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'collection_name': 'customized_setup_1', 'auto_id': False, 'num_shards': 1, 'description': '', 'fields': [{'field_id': 100, 'name': 'my_id', 'description': '', 'type': <DataType.INT64: 5>, 'params': {}, 'is_primary': True}, {'field_id': 101, 'name': 'my_vector', 'description': '', 'type': <DataType.FLOAT_VECTOR: 101>, 'params': {'dim': 5}}, {'field_id': 102, 'name': 'my_varchar', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 512}}], 'functions': [], 'aliases': [], 'collection_id': 456238279677978972, 'consistency_level': 2, 'properties': {}, 'num_partitions': 1, 'enable_dynamic_field': True}\n"
+     ]
+    }
+   ],
+   "source": [
+    "res = client.describe_collection(\n",
+    "    collection_name=\"customized_setup_1\"\n",
+    ")\n",
+    "\n",
+    "print(res)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client.release_collection(\n",
+    "    collection_name=\"customized_setup_1\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client.load_collection(\\\n",
+    "    collection_name=\"customized_setup_1\",\n",
+    "    # highlight-next-line\n",
+    "    load_fields=[\"my_id\", \"my_vector\"], # Load only the specified fields\n",
+    "    skip_load_dynamic_field=True # Skip loading the dynamic field\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tạo db với vector nhị phân"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'auto_id': True, 'description': '', 'fields': [{'name': 'pk', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 100}, 'is_primary': True, 'auto_id': False}, {'name': 'ingredients', 'description': '', 'type': <DataType.BINARY_VECTOR: 100>, 'params': {'dim': 128}}, {'name': 'recipes', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 1000}}], 'enable_dynamic_field': False}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "schema = client.create_schema(\n",
+    "    auto_id=True,\n",
+    "    enable_dynamic_fields=True,\n",
+    ")\n",
+    "\n",
+    "schema.add_field(field_name=\"pk\", datatype=DataType.VARCHAR, is_primary=True, max_length=100)\n",
+    "schema.add_field(field_name=\"ingredients\", datatype=DataType.BINARY_VECTOR, dim=128)\n",
+    "schema.add_field(field_name=\"recipes\", datatype=DataType.VARCHAR, max_length=1000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "index_params = client.prepare_index_params()\n",
+    "\n",
+    "index_params.add_index(\n",
+    "    field_name=\"ingredients\",\n",
+    "    index_name=\"ingredients_index\",\n",
+    "    index_type=\"BIN_IVF_FLAT\",\n",
+    "    metric_type=\"HAMMING\",\n",
+    "    params={\"nlist\": 128}\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client.create_collection(\n",
+    "    collection_name=\"cookbook_db\",\n",
+    "    schema=schema,\n",
+    "    index_params=index_params\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_bool_list_to_bytes(bool_list):\n",
+    "    if len(bool_list) % 8 != 0:\n",
+    "        raise ValueError(\"The length of a boolean list must be a multiple of 8\")\n",
+    "\n",
+    "    byte_array = bytearray(len(bool_list) // 8)\n",
+    "    for i, bit in enumerate(bool_list):\n",
+    "        if bit == 1:\n",
+    "            index = i // 8\n",
+    "            shift = i % 8\n",
+    "            byte_array[index] |= (1 << shift)\n",
+    "    return bytes(byte_array)\n",
+    "\n",
+    "\n",
+    "bool_vectors = [\n",
+    "    [1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0] + [0] * 112,\n",
+    "    [0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1] + [0] * 112,\n",
+    "]\n",
+    "\n",
+    "data = [{\"ingredients\": convert_bool_list_to_bytes(bool_vector), \"recipes\": f\"xin chao cac ban {i}\" } for i, bool_vector in enumerate(bool_vectors)]\n",
+    "\n",
+    "client.insert(\n",
+    "    collection_name=\"cookbook_db\",\n",
+    "    data=data\n",
+    ")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "search\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "data: [\"[{'id': '456238279677992491', 'distance': 0.0, 'entity': {'pk': '456238279677992491', 'recipes': 'xin chao cac ban'}}]\"]\n"
+     ]
+    }
+   ],
+   "source": [
+    "search_params = {\n",
+    "    \"params\": {\"nprobe\": 10}\n",
+    "}\n",
+    "\n",
+    "query_bool_list = [1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0] + [0] * 112\n",
+    "query_vector = convert_bool_list_to_bytes(query_bool_list)\n",
+    "\n",
+    "res = client.search(\n",
+    "    collection_name=\"cookbook_db\",\n",
+    "    data=[query_vector],\n",
+    "    anns_field=\"ingredients\",\n",
+    "    search_params=search_params,\n",
+    "    limit=1,\n",
+    "    output_fields=[\"pk\", \"recipes\"]\n",
+    ")\n",
+    "\n",
+    "print(res)\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

standalone.bat

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+@REM  Licensed to the LF AI & Data foundation under one
+@REM  or more contributor license agreements. See the NOTICE file
+@REM  distributed with this work for additional information
+@REM  regarding copyright ownership. The ASF licenses this file
+@REM  to you under the Apache License, Version 2.0 (the
+@REM  "License"); you may not use this file except in compliance
+@REM  with the License. You may obtain a copy of the License at
+@REM 
+@REM    http://www.apache.org/licenses/LICENSE-2.0
+@REM 
+@REM  Unless required by applicable law or agreed to in writing, software
+@REM  distributed under the License is distributed on an "AS IS" BASIS,
+@REM  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+@REM  See the License for the specific language governing permissions and
+@REM  limitations under the License.
+
+@echo off
+setlocal enabledelayedexpansion
+
+:main
+if "%1"=="" (
+    echo Please use standalone_embed.bat restart^|start^|stop^|delete
+    exit /b 1
+)
+
+if "%1"=="restart" (
+    call :stop
+    call :start
+) else if "%1"=="start" (
+    call :start
+) else if "%1"=="stop" (
+    call :stop
+) else if "%1"=="delete" (
+    call :delete
+) else (
+    echo Unknown command.
+    echo Please use standalone_embed.bat restart^|start^|stop^|upgrade^|delete
+    exit /b 1
+)
+goto :eof
+
+:run_embed
+(
+echo listen-client-urls: http://0.0.0.0:2379
+echo advertise-client-urls: http://0.0.0.0:2379
+echo quota-backend-bytes: 4294967296
+echo auto-compaction-mode: revision
+echo auto-compaction-retention: '1000'
+) > embedEtcd.yaml
+
+(
+echo # Extra config to override default milvus.yaml
+) > user.yaml
+
+docker run -d ^
+    --name milvus-standalone ^
+    --security-opt seccomp:unconfined ^
+    -e ETCD_USE_EMBED=true ^
+    -e ETCD_DATA_DIR=/var/lib/milvus/etcd ^
+    -e ETCD_CONFIG_PATH=/milvus/configs/embedEtcd.yaml ^
+    -e COMMON_STORAGETYPE=local ^
+    -v "%cd%\volumes\milvus:/var/lib/milvus" ^
+    -v "%cd%\embedEtcd.yaml:/milvus/configs/embedEtcd.yaml" ^
+    -v "%cd%\user.yaml:/milvus/configs/user.yaml" ^
+    -p 19530:19530 ^
+    -p 9091:9091 ^
+    -p 2379:2379 ^
+    --health-cmd="curl -f http://localhost:9091/healthz" ^
+    --health-interval=30s ^
+    --health-start-period=90s ^
+    --health-timeout=20s ^
+    --health-retries=3 ^
+    milvusdb/milvus:v2.4.13 ^
+    milvus run standalone >nul
+if %errorlevel% neq 0 (
+    echo Failed to start Milvus container.
+    exit /b 1
+)
+
+goto :eof
+
+:wait_for_milvus_running
+echo Wait for Milvus Starting...
+:wait_loop
+for /f "tokens=*" %%A in ('docker ps ^| findstr "milvus-standalone" ^| findstr "healthy"') do set running=1
+if "!running!"=="1" (
+    echo Start successfully.
+    echo To change the default Milvus configuration, edit user.yaml and restart the service.
+    goto :eof
+)
+timeout /t 1 >nul
+goto wait_loop
+
+:start
+for /f "tokens=*" %%A in ('docker ps ^| findstr "milvus-standalone" ^| findstr "healthy"') do (
+    echo Milvus is running.
+    exit /b 0
+)
+
+for /f "tokens=*" %%A in ('docker ps -a ^| findstr "milvus-standalone"') do set container_exists=1
+if defined container_exists (
+    docker start milvus-standalone >nul
+) else (
+    call :run_embed
+)
+
+if %errorlevel% neq 0 (
+    echo Start failed.
+    exit /b 1
+)
+
+call :wait_for_milvus_running
+goto :eof
+
+:stop
+docker stop milvus-standalone >nul
+if %errorlevel% neq 0 (
+    echo Stop failed.
+    exit /b 1
+)
+echo Stop successfully.
+goto :eof
+
+:delete_container
+for /f "tokens=*" %%A in ('docker ps ^| findstr "milvus-standalone"') do (
+    echo Please stop Milvus service before delete.
+    exit /b 1
+)
+docker rm milvus-standalone >nul
+if %errorlevel% neq 0 (
+    echo Delete Milvus container failed.
+    exit /b 1
+)
+echo Delete Milvus container successfully.
+goto :eof
+
+:delete
+call :delete_container
+rmdir /s /q "%cd%\volumes"
+del /q embedEtcd.yaml
+del /q user.yaml
+echo Delete successfully.
+goto :eof
+
+:EOF