add content

qdrant-landing/content/documentation/advanced-tutorials/_index.md

@@ -0,0 +1,20 @@
+---
+title: Advanced Retrieval
+weight: 17
+# If the index.md file is empty, the link to the section will be hidden from the sidebar
+is_empty: false
+aliases:
+  - how-to
+  - tutorials
+partition: qdrant
+---
+
+# Advanced Tutorials 
+
+These tutorials demonstrate different ways you can build vector search into your applications. 
+
+| Essential How-Tos                                                                      | Description                                                       | Stack                                       |   
+|---------------------------------------------------------------------------------|-------------------------------------------------------------------|---------------------------------------------|
+| [Collaborative Ffiltering](/documentation/tutorials/collaborative-filtering/)                 | Set up a recommendation engine purely with vector search               | Qdrant                                      | 
+| [Multimodal Search](/documentation/tutorials/multimodal-search-fastembed/)                                | Create a simple multimodal search engine.                                      | Qdrant                                      |  
+| [Search Through Code](/documentation/tutorials/code-search/)      | Implement semantic search application for code search tasks        | Qdrant, Python, sentence-transformers, Jina |

qdrant-landing/content/documentation/advanced-tutorials/code-search.md

@@ -1,6 +1,6 @@
 ---
-title: Semantic code search
-weight: 22
+title: Semantic Search Over Code
+weight: 2
 ---
 
 # Use semantic search to navigate your codebase

qdrant-landing/content/documentation/advanced-tutorials/collaborative-filtering.md

@@ -1,10 +1,10 @@
 ---
-title: Collaborative filtering
+title: Collaborative Filtering
 short_description: "Build an effective movie recommendation system using collaborative filtering and Qdrant's similarity search."
 description: "Build an effective movie recommendation system using collaborative filtering and Qdrant's similarity search." 
 preview_image: /blog/collaborative-filtering/social_preview.png
 social_preview_image: /blog/collaborative-filtering/social_preview.png
-weight: 23
+weight: 3
 ---
 
 # Create a collaborative filtering system

qdrant-landing/content/documentation/advanced-tutorials/multimodal-search-fastembed.md

@@ -1,6 +1,6 @@
 ---
 title: Multimodal Search
-weight: 4
+weight: 1
 ---
 
 # Multimodal Search with Qdrant and FastEmbed

qdrant-landing/content/documentation/beginner-tutorials/_index.md

@@ -1,6 +1,6 @@
 ---
-title: Tutorials
-weight: 10
+title: Vector Search Basics
+weight: 16
 # If the index.md file is empty, the link to the section will be hidden from the sidebar
 is_empty: false
 aliases:
@@ -9,7 +9,7 @@ aliases:
 partition: qdrant
 ---
 
-# Tutorials 
+# Beginner Tutorials 
 
 These tutorials demonstrate different ways you can build vector search into your applications. 
 
@@ -18,11 +18,5 @@ These tutorials demonstrate different ways you can build vector search into your
 | [Semantic Search for Beginners](/documentation/tutorials/search-beginners/)                 | Create a simple search engine locally in minutes.                 | Qdrant                                      | 
 | [Simple Neural Search](/documentation/tutorials/neural-search/)                             | Build and deploy a neural search that browses startup data.       | Qdrant, BERT, FastAPI                       | 
 | [Neural Search with FastEmbed](/documentation/tutorials/neural-search-fastembed/)                                 | Build and deploy a neural search with our FastEmbed library.               | Qdrant                                      | 
-| [Multimodal Search](/documentation/tutorials/multimodal-search-fastembed/)                                | Create a simple multimodal search.                                      | Qdrant                                      |  
-| [Bulk Upload Vectors](/documentation/tutorials/bulk-upload/)                                | Upload a large scale dataset.                                     | Qdrant                                      | 
-| [Asynchronous API](/documentation/tutorials/async-api/)                                     | Communicate with Qdrant server asynchronously with Python SDK.    | Qdrant, Python                              |
-| [Create Dataset Snapshots](/documentation/tutorials/create-snapshot/)                       | Turn a dataset into a snapshot by exporting it from a collection. | Qdrant                                      | 
-| [Load HuggingFace Dataset](/documentation/tutorials/huggingface-datasets/)                      | Load a Hugging Face dataset to Qdrant                             | Qdrant, Python, datasets                    |
 | [Measure Retrieval Quality](/documentation/tutorials/retrieval-quality/)                    | Measure and fine-tune the retrieval quality                       | Qdrant, Python, datasets                    |
-| [Search Through Code](/documentation/tutorials/code-search/)      | Implement semantic search application for code search tasks        | Qdrant, Python, sentence-transformers, Jina |
-| [Setup Collaborative Filtering](/documentation/tutorials/collaborative-filtering/)      | Implement a collaborative filtering system for recommendation engines        | Qdrant|
+

qdrant-landing/content/documentation/beginner-tutorials/hybrid-search-fastembed.md

@@ -1,6 +1,6 @@
 ---
-title: Hybrid Search with Fastembed
-weight: 2
+title: Hybrid Search with FastEmbed
+weight: 3
 
 aliases:
   - /documentation/tutorials/neural-search-fastembed/

qdrant-landing/content/documentation/beginner-tutorials/neural-search.md

@@ -1,6 +1,6 @@
 ---
 title: Neural Search Service
-weight: 1
+weight: 2
 ---
 
 # Create a Simple Neural Search Service

qdrant-landing/content/documentation/beginner-tutorials/retrieval-quality.md

@@ -1,6 +1,6 @@
 ---
-title: Measure retrieval quality
-weight: 21
+title: Measure Search Quality
+weight: 4
 ---
 
 # Measure retrieval quality

qdrant-landing/content/documentation/beginner-tutorials/search-beginners.md

@@ -1,6 +1,6 @@
 ---
 title: Semantic Search 101
-weight: -100
+weight: 1
 aliases:
   - /documentation/tutorials/mighty.md/
 ---

qdrant-landing/content/documentation/database-tutorials/_index.md

@@ -0,0 +1,22 @@
+---
+title: Using the Database
+weight: 18
+# If the index.md file is empty, the link to the section will be hidden from the sidebar
+is_empty: false
+aliases:
+  - how-to
+  - tutorials
+partition: qdrant
+---
+
+# Database Tutorials 
+
+These tutorials demonstrate different ways you can build vector search into your applications. 
+
+| Essential How-Tos                                                                      | Description                                                       | Stack                                       |   
+|---------------------------------------------------------------------------------|-------------------------------------------------------------------|---------------------------------------------|
+| [Bulk Upload Vectors](/documentation/tutorials/bulk-upload/)                                | Upload a large scale dataset.                                     | Qdrant                                      | 
+| [Asynchronous API](/documentation/tutorials/async-api/)                                     | Communicate with Qdrant server asynchronously with Python SDK.    | Qdrant, Python                              |
+| [Create Dataset Snapshots](/documentation/tutorials/create-snapshot/)                       | Turn a dataset into a snapshot by exporting it from a collection. | Qdrant                                      | 
+| [Load HuggingFace Dataset](/documentation/tutorials/huggingface-datasets/)                      | Load a Hugging Face dataset to Qdrant                             | Qdrant, Python, datasets                    |
+

qdrant-landing/content/documentation/database-tutorials/async-api.md

@@ -1,6 +1,6 @@
 ---
-title: Asynchronous API
-weight: 14
+title: Using the Async API
+weight: 4
 ---
 
 # Using Qdrant asynchronously

qdrant-landing/content/documentation/database-tutorials/bulk-upload.md

@@ -1,6 +1,6 @@
 ---
 title: Bulk Upload Vectors
-weight: 13
+weight: 1
 ---
 
 # Bulk upload a large number of vectors

qdrant-landing/content/documentation/database-tutorials/create-snapshot.md

@@ -1,6 +1,6 @@
 ---
-title: Create and restore from snapshot
-weight: 14
+title: Create & Restore Snapshots
+weight: 2
 ---
 
 # Create and restore collections from snapshot

qdrant-landing/content/documentation/database-tutorials/huggingface-datasets.md

@@ -1,6 +1,6 @@
 ---
-title: Load Hugging Face dataset
-weight: 19
+title: Load a HuggingFace Dataset
+weight: 3
 ---
 
 # Loading a dataset from Hugging Face hub

qdrant-landing/content/documentation/dl-tutorials.md

@@ -0,0 +1,11 @@
+---
+#Delimiter files are used to separate the list of documentation pages into sections.
+title: "Tutorials"
+type: delimiter
+weight: 15 # Change this weight to change order of sections
+sitemapExclude: True
+_build:
+  publishResources: false
+  render: never
+partition: qdrant
+---