Add notebooks for multi-vector search course

course-multi-vector-search/module-0/installing-dependencies.ipynb

@@ -0,0 +1,117 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "# Module 0: Installing Dependencies",
+   "id": "9af5bc4b49d17ebc"
+  },
+  {
+   "cell_type": "markdown",
+   "id": "mli6s9xkllr",
+   "source": "We need `qdrant-client` for interacting with Qdrant and `fastembed` for generating vector embeddings locally.",
+   "metadata": {}
+  },
+  {
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    }
+   },
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": 1,
+   "source": "!pip install -q \"qdrant-client==1.16.2\" \"fastembed==0.7.4\"",
+   "id": "466eb04e8e447feb"
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6u2wb574s8n",
+   "source": "Let's verify that both packages were installed correctly by importing them.",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8e66867cd6ebf200",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All dependencies installed successfully!\n"
+     ]
+    }
+   ],
+   "source": [
+    "from qdrant_client import QdrantClient\n",
+    "from fastembed import TextEmbedding\n",
+    "\n",
+    "print(\"All dependencies installed successfully!\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "uvxeas5v8er",
+   "source": "Connect to your Qdrant instance. Replace the URL and API key with your own Qdrant Cloud credentials, or use a local instance.",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1ea6882564a624f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Connected to Qdrant: collections=[]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# For Qdrant Cloud\n",
+    "client = QdrantClient(\n",
+    "    url=\"https://your-cluster-url.cloud.qdrant.io\",\n",
+    "    api_key=\"your-api-key\"\n",
+    ")\n",
+    "\n",
+    "# For local Qdrant\n",
+    "# client = QdrantClient(url=\"http://localhost:6333\")\n",
+    "\n",
+    "print(f\"Connected to Qdrant: {client.get_collections()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a9bdeae2-ae97-4110-92f4-531168f3b31c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}