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Update Redis 8.2.0+ installation for multivector search notebook
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‎python-recipes/vector-search/05_multivector_search.ipynb‎

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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"### Install Redis Stack\n",
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"### Install Redis\n",
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"\n",
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"Later in this tutorial, Redis will be used to store, index, and query vector\n",
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"embeddings and full text fields. **We need to have a Redis\n",
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"instance available.**\n",
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"\n",
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"#### Local Redis\n",
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"Use the shell script below to download, extract, and install [Redis Stack](https://redis.io/docs/getting-started/install-stack/) directly from the Redis package archive."
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"Use the shell script below to download, extract, and install [Redis](https://redis.io/docs/latest/operate/oss_and_stack/install/install-stack/apt/) directly from the Redis package archive for a Linux environment."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": 20,
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"source": [
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"# NBVAL_SKIP\n",
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"%%sh\n",
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"sudo apt-get install lsb-release curl gpg\n",
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"curl -fsSL https://packages.redis.io/gpg | sudo gpg --dearmor -o /usr/share/keyrings/redis-archive-keyring.gpg\n",
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"sudo chmod 644 /usr/share/keyrings/redis-archive-keyring.gpg\n",
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"echo \"deb [signed-by=/usr/share/keyrings/redis-archive-keyring.gpg] https://packages.redis.io/deb $(lsb_release -cs) main\" | sudo tee /etc/apt/sources.list.d/redis.list\n",
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"sudo apt-get update > /dev/null 2>&1\n",
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"sudo apt-get install redis-stack-server > /dev/null 2>&1\n",
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"redis-stack-server --daemonize yes"
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"sudo apt-get update\n",
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"sudo apt-get install redis\n",
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"\n",
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"redis-server --version\n",
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"redis-server --daemonize yes --loadmodule /usr/lib/redis/modules/redisearch.so"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"#### Alternative Redis Access (Cloud, Docker, other)\n",
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"There are many ways to get the necessary redis-stack instance running\n",
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"1. On cloud, deploy a [FREE instance of Redis in the cloud](https://redis.com/try-free/). Or, if you have your\n",
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"own version of Redis Enterprise running, that works too!\n",
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"2. Per OS, [see the docs](https://redis.io/docs/latest/operate/oss_and_stack/install/install-stack/)\n",
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"3. With docker: `docker run -d --name redis-stack-server -p 6379:6379 redis/redis-stack-server:latest`"
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"3. With docker: `docker run -d --name redis -p 6379:6379 redis:latest`"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:24:43.601826Z",
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"start_time": "2025-12-09T15:24:43.599178Z"
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}
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},
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"source": [
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"import os\n",
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"\n",
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"\n",
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"# If SSL is enabled on the endpoint, use rediss:// as the URL prefix\n",
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"REDIS_URL = f\"redis://:{REDIS_PASSWORD}@{REDIS_HOST}:{REDIS_PORT}\""
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]
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],
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"outputs": [],
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"execution_count": 1
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},
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{
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:24:45.636539Z",
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"start_time": "2025-12-09T15:24:45.602099Z"
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}
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},
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"source": [
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"from redis import Redis\n",
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"\n",
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"client = Redis.from_url(REDIS_URL)\n",
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"client.ping()"
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],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 3,
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from redis import Redis\n",
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"\n",
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"client = Redis.from_url(REDIS_URL)\n",
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"client.ping()"
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]
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"execution_count": 2
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},
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:24:48.003249Z",
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"start_time": "2025-12-09T15:24:47.998789Z"
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}
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},
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"source": [
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"import json\n",
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"\n",
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"with open(\"resources/movies.json\", 'r') as file:\n",
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" movies = json.load(file)"
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]
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],
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"outputs": [],
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"execution_count": 3
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"14:45:04 datasets INFO PyTorch version 2.3.0 available.\n",
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"14:45:05 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"14:45:05 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/all-MiniLM-L6-v2\n",
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"14:45:07 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"14:45:07 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/all-mpnet-base-v2\n",
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"14:45:08 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"14:45:08 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2\n"
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]
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:25:17.968696Z",
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"start_time": "2025-12-09T15:24:51.320769Z"
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}
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],
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},
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"source": [
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"from redisvl.utils.vectorize import HFTextVectorizer\n",
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"from redisvl.extensions.cache.embeddings import EmbeddingsCache\n",
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" ),\n",
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" dtype=\"float32\"\n",
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")"
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]
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],
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/vishal.bala/PycharmProjects/redis-ai-resources/.venv/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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" from .autonotebook import tqdm as notebook_tqdm\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"16:24:55 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"16:24:55 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/all-MiniLM-L6-v2\n",
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"16:24:58 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"16:24:58 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/all-mpnet-base-v2\n",
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"16:25:01 sentence_transformers.SentenceTransformer INFO Use pytorch device_name: mps\n",
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"16:25:01 sentence_transformers.SentenceTransformer INFO Load pretrained SentenceTransformer: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2\n"
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]
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}
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],
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"execution_count": 4
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Generating multiple embeddings for movies...\n",
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"Generated embeddings for 20 movies\n"
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]
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:25:27.857788Z",
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"start_time": "2025-12-09T15:25:24.034106Z"
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}
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],
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},
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"source": [
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"# Generate multiple embeddings for each movie\n",
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"print(\"Generating multiple embeddings for movies...\")\n",
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" multi_vector_movie_data.append(movie_with_vectors)\n",
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"\n",
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"print(f\"Generated embeddings for {len(multi_vector_movie_data)} movies\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Multi-vector index created and populated successfully!\n"
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"Generating multiple embeddings for movies...\n",
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"Generated embeddings for 20 movies\n"
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]
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}
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],
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"execution_count": 5
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},
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{
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"cell_type": "code",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:25:27.891696Z",
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"start_time": "2025-12-09T15:25:27.864579Z"
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}
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},
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"source": [
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"from redisvl.schema import IndexSchema\n",
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"from redisvl.index import SearchIndex\n",
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"# Load the multi-vector data\n",
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"multi_vector_index.load(multi_vector_movie_data)\n",
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"print(\"Multi-vector index created and populated successfully!\")"
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]
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Multi-vector index created and populated successfully!\n"
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]
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}
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],
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"execution_count": 6
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},
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1. The Incredibles \n",
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" Genre: comedy, Rating: 8\n",
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" Description: A family of undercover superheroes, while trying to live the quiet suburban life, are forced into ac...\n",
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"\n",
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"2. The Avengers \n",
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" Genre: action, Rating: 8\n",
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" Description: Earth's mightiest heroes come together to stop an alien invasion that threatens the entire planet....\n",
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"\n",
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"3. Mad Max: Fury Road \n",
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" Genre: action, Rating: 8\n",
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" Description: In a post-apocalyptic wasteland, Max teams up with Furiosa to escape a tyrant's clutches and find fr...\n",
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"\n",
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"4. John Wick \n",
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" Genre: action, Rating: 8\n",
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" Description: A retired hitman seeks vengeance against those who wronged him, leaving a trail of destruction in hi...\n",
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"\n",
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"5. The Dark Knight \n",
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" Genre: action, Rating: 9\n",
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" Description: Batman faces off against the Joker, a criminal mastermind who threatens to plunge Gotham into chaos....\n",
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"\n"
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]
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:25:31.125875Z",
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"start_time": "2025-12-09T15:25:30.346516Z"
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}
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],
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},
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"source": [
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"from redisvl.query import Vector, MultiVectorQuery\n",
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"query_text = \"action movie with superheroes and explosions\"\n",
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" print(f\" Genre: {result['genre']}, Rating: {result['rating']}\")\n",
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" print(f\" Description: {result['description'][:100]}...\")\n",
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" print()"
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]
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1. The Incredibles \n",
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" Genre: comedy, Rating: 8\n",
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" Description: A family of undercover superheroes, while trying to live the quiet suburban life, are forced into ac...\n",
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"\n",
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"2. The Avengers \n",
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" Genre: action, Rating: 8\n",
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" Description: Earth's mightiest heroes come together to stop an alien invasion that threatens the entire planet....\n",
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"\n",
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"3. Mad Max: Fury Road \n",
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" Genre: action, Rating: 8\n",
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" Description: In a post-apocalyptic wasteland, Max teams up with Furiosa to escape a tyrant's clutches and find fr...\n",
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"\n",
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"4. John Wick \n",
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" Genre: action, Rating: 8\n",
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" Description: A retired hitman seeks vengeance against those who wronged him, leaving a trail of destruction in hi...\n",
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"\n",
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"5. The Dark Knight \n",
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" Genre: action, Rating: 9\n",
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" Description: Batman faces off against the Joker, a criminal mastermind who threatens to plunge Gotham into chaos....\n",
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"\n"
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]
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}
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],
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"execution_count": 7
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"cell_type": "markdown",
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},
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-12-09T15:25:33.245401Z",
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"start_time": "2025-12-09T15:25:33.242415Z"
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}
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},
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"source": [
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"# clean up!\n",
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"multi_vector_index.delete()"
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]
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],
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"outputs": [],
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"execution_count": 8
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}
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],
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"metadata": {

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