renames HybridQuery in docs

Author: justin-cechmanek

docs/user_guide/11_advanced_queries.ipynb

@@ -9,7 +9,7 @@
     "In this notebook, we will explore advanced query types available in RedisVL:\n",
     "\n",
     "1. **`TextQuery`**: Full text search with advanced scoring\n",
-    "2. **`HybridQuery`**: Combines text and vector search for hybrid retrieval\n",
+    "2. **`AggregateHybridQuery`**: Combines text and vector search for hybrid retrieval\n",
     "3. **`MultiVectorQuery`**: Search over multiple vector fields simultaneously\n",
     "\n",
     "These query types are powerful tools for building sophisticated search applications that go beyond simple vector similarity search.\n",
@@ -550,9 +550,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 2. HybridQuery: Combining Text and Vector Search\n",
+    "## 2. AggregateHybridQuery: Combining Text and Vector Search\n",
     "\n",
-    "The `HybridQuery` combines text search and vector similarity to provide the best of both worlds:\n",
+    "The `AggregateHybridQuery` combines text search and vector similarity to provide the best of both worlds:\n",
     "- **Text search**: Finds exact keyword matches\n",
     "- **Vector search**: Captures semantic similarity\n",
     "\n",
@@ -569,7 +569,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Basic Hybrid Query\n",
+    "### Basic Aggregate Hybrid Query\n",
     "\n",
     "Let's search for \"running\" with both text and semantic search:"
    ]
@@ -593,10 +593,10 @@
     }
    ],
    "source": [
-    "from redisvl.query import HybridQuery\n",
+    "from redisvl.query import AggregateHybridQuery\n",
     "\n",
     "# Create a hybrid query\n",
-    "hybrid_query = HybridQuery(\n",
+    "hybrid_query = AggregateHybridQuery(\n",
     "    text=\"running shoes\",\n",
     "    text_field_name=\"brief_description\",\n",
     "    vector=[0.1, 0.2, 0.1],  # Query vector\n",
@@ -648,7 +648,7 @@
    ],
    "source": [
     "# More emphasis on vector search (alpha=0.9)\n",
-    "vector_heavy_query = HybridQuery(\n",
+    "vector_heavy_query = AggregateHybridQuery(\n",
     "    text=\"comfortable\",\n",
     "    text_field_name=\"brief_description\",\n",
     "    vector=[0.15, 0.25, 0.15],\n",
@@ -667,7 +667,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Hybrid Query with Filters\n",
+    "### Aggregate Hybrid Query with Filters\n",
     "\n",
     "You can also combine hybrid search with filters:"
    ]
@@ -692,7 +692,7 @@
    ],
    "source": [
     "# Hybrid search with a price filter\n",
-    "filtered_hybrid_query = HybridQuery(\n",
+    "filtered_hybrid_query = AggregateHybridQuery(\n",
     "    text=\"professional equipment\",\n",
     "    text_field_name=\"brief_description\",\n",
     "    vector=[0.9, 0.1, 0.05],\n",
@@ -712,7 +712,7 @@
    "source": [
     "### Using Different Text Scorers\n",
     "\n",
-    "HybridQuery supports the same text scoring algorithms as TextQuery:"
+    "AggregateHybridQuery supports the same text scoring algorithms as TextQuery:"
    ]
   },
   {
@@ -734,8 +734,8 @@
     }
    ],
    "source": [
-    "# Hybrid query with TFIDF scorer\n",
-    "hybrid_tfidf = HybridQuery(\n",
+    "# Aggregate Hybrid query with TFIDF scorer\n",
+    "hybrid_tfidf = AggregateHybridQuery(\n",
     "    text=\"shoes support\",\n",
     "    text_field_name=\"brief_description\",\n",
     "    vector=[0.12, 0.18, 0.12],\n",
@@ -999,7 +999,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "HybridQuery Results (text + vector):\n"
+      "AggregateHybridQuery Results (text + vector):\n"
      ]
     },
     {
@@ -1023,8 +1023,8 @@
     }
    ],
    "source": [
-    "# HybridQuery - combines text and vector search\n",
-    "hybrid_q = HybridQuery(\n",
+    "# AggregateHybridQuery - combines text and vector search\n",
+    "hybrid_q = AggregateHybridQuery(\n",
     "    text=\"shoes\",\n",
     "    text_field_name=\"brief_description\",\n",
     "    vector=[0.1, 0.2, 0.1],\n",
@@ -1033,7 +1033,7 @@
     "    num_results=3\n",
     ")\n",
     "\n",
-    "print(\"HybridQuery Results (text + vector):\")\n",
+    "print(\"AggregateHybridQuery Results (text + vector):\")\n",
     "result_print(index.query(hybrid_q))\n",
     "print()"
    ]
@@ -1103,7 +1103,7 @@
     "   - When text relevance scoring is important\n",
     "   - Example: Product search, document retrieval\n",
     "\n",
-    "2. **`HybridQuery`**:\n",
+    "2. **`AggregateHybridQuery`**:\n",
     "   - When you want to combine keyword and semantic search\n",
     "   - For improved search quality over pure text or vector search\n",
     "   - When you have both text and vector representations of your data\n",