diff --git a/qdrant-landing/content/advanced-search/advanced-search-features.md b/qdrant-landing/content/advanced-search/advanced-search-features.md index 746c7915c..50e9f0864 100644 --- a/qdrant-landing/content/advanced-search/advanced-search-features.md +++ b/qdrant-landing/content/advanced-search/advanced-search-features.md @@ -19,7 +19,7 @@ features: description: By combining dense vector embeddings with sparse vectors e.g. BM25, Qdrant powers semantic search to deliver context-aware results, transcending traditional keyword search by understanding the deeper meaning of data. link: text: Learn More - url: /documentation/tutorials/hybrid-search-fastembed/ + url: /documentation/beginner-tutorials/hybrid-search-fastembed/ - id: 2 icon: src: /icons/outline/selection-blue.svg @@ -28,12 +28,12 @@ features: description: Qdrant's capability extends to multi-modal search, indexing and retrieving various data forms (text, images, audio) once vectorized, facilitating a comprehensive search experience. link: text: View Tutorial - url: /documentation/tutorials/aleph-alpha-search/ + url: /documentation/tutorials/multimodal-search-fastembed/ - id: 3 icon: src: /icons/outline/filter-blue.svg alt: Filter - title: Single Stage filtering that Works + title: Single Stage filtering That Works description: Qdrant enhances search speeds and control and context understanding through filtering on any nested entry in our payload. Unique architecture allows Qdrant to avoid expensive pre-filtering and post-filtering stages, making search faster and accurate. link: text: Learn More diff --git a/qdrant-landing/content/advanced-search/advanced-search-use-cases.md b/qdrant-landing/content/advanced-search/advanced-search-use-cases.md index 4e43200f2..8c3b513cf 100644 --- a/qdrant-landing/content/advanced-search/advanced-search-use-cases.md +++ b/qdrant-landing/content/advanced-search/advanced-search-use-cases.md @@ -14,11 +14,11 @@ features: image: src: /img/advanced-search-use-cases/multimodal-semantic-search.svg alt: Multimodal Semantic Search - title: Multimodal Semantic Search with Aleph Alpha + title: Multimodal Semantic Search with FastEmbed description: This tutorial shows you how to run a proper multimodal semantic search system with a few lines of code, without the need to annotate the data or train your networks. link: text: View Tutorial - url: /documentation/examples/aleph-alpha-search/ + url: /documentation/tutorials/multimodal-search-fastembed/ - id: 2 image: src: /img/advanced-search-use-cases/simple-neural-search.svg @@ -27,7 +27,7 @@ features: description: This tutorial shows you how to build and deploy your own neural search service. link: text: View Tutorial - url: /documentation/tutorials/neural-search/ + url: /documentation/beginner-tutorials/neural-search/ - id: 3 image: src: /img/advanced-search-use-cases/image-classification.svg @@ -45,16 +45,16 @@ features: description: Build a semantic search engine for science fiction books in 5 mins. link: text: View Tutorial - url: /documentation/tutorials/search-beginners/ + url: /documentation/beginner-tutorials/search-beginners/ - id: 5 image: src: /img/advanced-search-use-cases/hybrid-search-service-fastembed.svg - alt: Create a Hybrid Search Service with Fastembed - title: Create a Hybrid Search Service with Fastembed - description: This tutorial guides you through building and deploying your own hybrid search service using Fastembed. + alt: Create a Hybrid Search Service with FastEmbed + title: Create a Hybrid Search Service with FastEmbed + description: This tutorial guides you through building and deploying your own hybrid search service using FastEmbed. link: text: View Tutorial - url: /documentation/tutorials/hybrid-search-fastembed/ + url: /documentation/beginner-tutorials/hybrid-search-fastembed/ sitemapExclude: true --- diff --git a/qdrant-landing/content/documentation/advanced-tutorials/_index.md b/qdrant-landing/content/documentation/advanced-tutorials/_index.md new file mode 100644 index 000000000..69887fd6d --- /dev/null +++ b/qdrant-landing/content/documentation/advanced-tutorials/_index.md @@ -0,0 +1,18 @@ +--- +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 + +| | +|----------------------------------------------------------| +| [Use Collaborative Filtering to Build a Movie Recommendation System with Qdrant](/documentation/advanced-tutorials/collaborative-filtering/) | +| [Build a Text/Image Multimodal Search System with Qdrant and FastEmbed](/documentation/advanced-tutorials/multimodal-search-fastembed/) | +| [Navigate Your Codebase with Semantic Search and Qdrant](/documentation/advanced-tutorials/code-search/) | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials/code-search.md b/qdrant-landing/content/documentation/advanced-tutorials/code-search.md similarity index 99% rename from qdrant-landing/content/documentation/tutorials/code-search.md rename to qdrant-landing/content/documentation/advanced-tutorials/code-search.md index 8e0a31b77..169133370 100644 --- a/qdrant-landing/content/documentation/tutorials/code-search.md +++ b/qdrant-landing/content/documentation/advanced-tutorials/code-search.md @@ -1,9 +1,11 @@ --- -title: Semantic code search -weight: 22 +title: Search Through Your Codebase +aliases: + - /documentation/tutorials/code-search/ +weight: 2 --- -# Use semantic search to navigate your codebase +# Navigate Your Codebase with Semantic Search and Qdrant | Time: 45 min | Level: Intermediate | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/qdrant/examples/blob/master/code-search/code-search.ipynb) | | |--------------|---------------------|--|----| diff --git a/qdrant-landing/content/documentation/tutorials/collaborative-filtering.md b/qdrant-landing/content/documentation/advanced-tutorials/collaborative-filtering.md similarity index 97% rename from qdrant-landing/content/documentation/tutorials/collaborative-filtering.md rename to qdrant-landing/content/documentation/advanced-tutorials/collaborative-filtering.md index 83c8e0b1b..8e871f05c 100644 --- a/qdrant-landing/content/documentation/tutorials/collaborative-filtering.md +++ b/qdrant-landing/content/documentation/advanced-tutorials/collaborative-filtering.md @@ -1,13 +1,15 @@ --- -title: Collaborative filtering +title: Build a Recommendation System with Collaborative Filtering +aliases: + - /documentation/tutorials/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 +# Use Collaborative Filtering to Build a Movie Recommendation System with Qdrant | Time: 45 min | Level: Intermediate | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/qdrant/examples/blob/master/collaborative-filtering/collaborative-filtering.ipynb) | | |--------------|---------------------|--|----| diff --git a/qdrant-landing/content/documentation/tutorials/multimodal-search-fastembed.md b/qdrant-landing/content/documentation/advanced-tutorials/multimodal-search-fastembed.md similarity index 98% rename from qdrant-landing/content/documentation/tutorials/multimodal-search-fastembed.md rename to qdrant-landing/content/documentation/advanced-tutorials/multimodal-search-fastembed.md index 717882bf7..b9006deb3 100644 --- a/qdrant-landing/content/documentation/tutorials/multimodal-search-fastembed.md +++ b/qdrant-landing/content/documentation/advanced-tutorials/multimodal-search-fastembed.md @@ -1,9 +1,11 @@ --- -title: Multimodal Search -weight: 4 +title: Setup Text/Image Multimodal Search +aliases: + - /documentation/tutorials/multimodal-search-fastembed/ +weight: 1 --- -# Multimodal Search with Qdrant and FastEmbed +# Build a Multimodal Search System with Qdrant and FastEmbed | Time: 15 min | Level: Beginner |Output: [GitHub](https://github.com/qdrant/examples/blob/master/multimodal-search/Multimodal_Search_with_FastEmbed.ipynb)|[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/qdrant/examples/blob/master/multimodal-search/Multimodal_Search_with_FastEmbed.ipynb) | | --- | ----------- | ----------- | ----------- | diff --git a/qdrant-landing/content/documentation/beginner-tutorials/_index.md b/qdrant-landing/content/documentation/beginner-tutorials/_index.md new file mode 100644 index 000000000..428f22200 --- /dev/null +++ b/qdrant-landing/content/documentation/beginner-tutorials/_index.md @@ -0,0 +1,21 @@ +--- +title: Vector Search Basics +aliases: + - /documentation/tutorials/ +weight: 16 +# 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 +--- + +# Beginner Tutorials + +| | +|----------------------------------------------------| +| [Build Your First Semantic Search Engine in 5 Minutes](/documentation/beginner-tutorials/search-beginners/) | +| [Build a Neural Search Service with Sentence Transformers and Qdrant](/documentation/beginner-tutorials/neural-search/) | +| [Build a Hybrid Search Service with FastEmbed and Qdrant](/documentation/beginner-tutorials/hybrid-search-fastembed/) | +| [Measure and Improve Retrieval Quality in Semantic Search](/documentation/beginner-tutorials/retrieval-quality/) | diff --git a/qdrant-landing/content/documentation/tutorials/hybrid-search-fastembed.md b/qdrant-landing/content/documentation/beginner-tutorials/hybrid-search-fastembed.md similarity index 98% rename from qdrant-landing/content/documentation/tutorials/hybrid-search-fastembed.md rename to qdrant-landing/content/documentation/beginner-tutorials/hybrid-search-fastembed.md index 2ff6ea518..7d5391593 100644 --- a/qdrant-landing/content/documentation/tutorials/hybrid-search-fastembed.md +++ b/qdrant-landing/content/documentation/beginner-tutorials/hybrid-search-fastembed.md @@ -1,12 +1,11 @@ --- -title: Hybrid Search with Fastembed -weight: 2 - +title: Setup Hybrid Search with FastEmbed aliases: - - /documentation/tutorials/neural-search-fastembed/ + - /documentation/tutorials/hybrid-search-fastembed/ +weight: 3 --- -# Create a Hybrid Search Service with Fastembed +# Build a Hybrid Search Service with FastEmbed and Qdrant | Time: 20 min | Level: Beginner | Output: [GitHub](https://github.com/qdrant/qdrant_demo/) | | --- | ----------- | ----------- |----------- | diff --git a/qdrant-landing/content/documentation/tutorials/neural-search.md b/qdrant-landing/content/documentation/beginner-tutorials/neural-search.md similarity index 97% rename from qdrant-landing/content/documentation/tutorials/neural-search.md rename to qdrant-landing/content/documentation/beginner-tutorials/neural-search.md index 0234d6f13..495e1273e 100644 --- a/qdrant-landing/content/documentation/tutorials/neural-search.md +++ b/qdrant-landing/content/documentation/beginner-tutorials/neural-search.md @@ -1,22 +1,22 @@ --- -title: Neural Search Service -weight: 1 +title: Build a Neural Search Service +aliases: + - /documentation/tutorials/neural-search/ +weight: 2 --- -# Create a Simple Neural Search Service +# Build a Neural Search Service with Sentence Transformers and Qdrant | Time: 30 min | Level: Beginner | Output: [GitHub](https://github.com/qdrant/qdrant_demo/tree/sentense-transformers) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1kPktoudAP8Tu8n8l-iVMOQhVmHkWV_L9?usp=sharing) | | --- | ----------- | ----------- |----------- | - - This tutorial shows you how to build and deploy your own neural search service to look through descriptions of companies from [startups-list.com](https://www.startups-list.com/) and pick the most similar ones to your query. The website contains the company names, descriptions, locations, and a picture for each entry. A neural search service uses artificial neural networks to improve the accuracy and relevance of search results. Besides offering simple keyword results, this system can retrieve results by meaning. It can understand and interpret complex search queries and provide more contextually relevant output, effectively enhancing the user's search experience. diff --git a/qdrant-landing/content/documentation/tutorials/retrieval-quality.md b/qdrant-landing/content/documentation/beginner-tutorials/retrieval-quality.md similarity index 98% rename from qdrant-landing/content/documentation/tutorials/retrieval-quality.md rename to qdrant-landing/content/documentation/beginner-tutorials/retrieval-quality.md index 307a315b3..2a9eee8bc 100644 --- a/qdrant-landing/content/documentation/tutorials/retrieval-quality.md +++ b/qdrant-landing/content/documentation/beginner-tutorials/retrieval-quality.md @@ -1,9 +1,11 @@ --- -title: Measure retrieval quality -weight: 21 +title: Measure Search Quality +aliases: + - /documentation/tutorials/retrieval-quality/ +weight: 4 --- -# Measure retrieval quality +# Measure and Improve Retrieval Quality in Semantic Search | Time: 30 min | Level: Intermediate | | | |--------------|---------------------|--|----| diff --git a/qdrant-landing/content/documentation/tutorials/search-beginners.md b/qdrant-landing/content/documentation/beginner-tutorials/search-beginners.md similarity index 98% rename from qdrant-landing/content/documentation/tutorials/search-beginners.md rename to qdrant-landing/content/documentation/beginner-tutorials/search-beginners.md index 1cf7dbdba..09eebf3d2 100644 --- a/qdrant-landing/content/documentation/tutorials/search-beginners.md +++ b/qdrant-landing/content/documentation/beginner-tutorials/search-beginners.md @@ -1,11 +1,12 @@ --- title: Semantic Search 101 -weight: -100 +weight: 1 aliases: - /documentation/tutorials/mighty.md/ + - /documentation/tutorials/search-beginners/ --- -# Semantic Search for Beginners +# Build Your First Semantic Search Engine in 5 Minutes | Time: 5 - 15 min | Level: Beginner | | | | --- | ----------- | ----------- |----------- | diff --git a/qdrant-landing/content/documentation/build-tab.md b/qdrant-landing/content/documentation/build-tab.md index dd44344cc..7488f5b19 100644 --- a/qdrant-landing/content/documentation/build-tab.md +++ b/qdrant-landing/content/documentation/build-tab.md @@ -24,7 +24,7 @@ content: title: Search description: Build a simple neural search service with Qdrant and FastEmbed. Learn how to upload data, create indexes, and run search queries. link: - url: /documentation/tutorials/hybrid-search-fastembed/ + url: /documentation/beginner-tutorials/hybrid-search-fastembed/ text: Read More - id: 2 image: diff --git a/qdrant-landing/content/documentation/database-tutorials/_index.md b/qdrant-landing/content/documentation/database-tutorials/_index.md new file mode 100644 index 000000000..ebd9f535f --- /dev/null +++ b/qdrant-landing/content/documentation/database-tutorials/_index.md @@ -0,0 +1,19 @@ +--- +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 + +| | +|--------------------------------------------| +| [Bulk Upload Vectors to a Qdrant Collection](/documentation/database-tutorials/bulk-upload/) | +| [Backup and Restore Qdrant Collections Using Snapshots](/documentation/database-tutorials/create-snapshot/) | +| [Load and Search Hugging Face Datasets with Qdrant](/documentation/database-tutorials/huggingface-datasets/) | +| [Using Qdrant’s Async API for Efficient Python Applications](/documentation/database-tutorials/async-api/) | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials/async-api.md b/qdrant-landing/content/documentation/database-tutorials/async-api.md similarity index 96% rename from qdrant-landing/content/documentation/tutorials/async-api.md rename to qdrant-landing/content/documentation/database-tutorials/async-api.md index 911671730..a2646df12 100644 --- a/qdrant-landing/content/documentation/tutorials/async-api.md +++ b/qdrant-landing/content/documentation/database-tutorials/async-api.md @@ -1,9 +1,11 @@ --- -title: Asynchronous API -weight: 14 +title: Build With Async API +aliases: + - /documentation/tutorials/async-api/ +weight: 4 --- -# Using Qdrant asynchronously +# Using Qdrant’s Async API for Efficient Python Applications Asynchronous programming is being broadly adopted in the Python ecosystem. Tools such as FastAPI [have embraced this new paradigm](https://fastapi.tiangolo.com/async/), but it is also becoming a standard for ML models served as SaaS. For example, the Cohere SDK diff --git a/qdrant-landing/content/documentation/tutorials/bulk-upload.md b/qdrant-landing/content/documentation/database-tutorials/bulk-upload.md similarity index 97% rename from qdrant-landing/content/documentation/tutorials/bulk-upload.md rename to qdrant-landing/content/documentation/database-tutorials/bulk-upload.md index 2a7d35a9a..d931ba0bf 100644 --- a/qdrant-landing/content/documentation/tutorials/bulk-upload.md +++ b/qdrant-landing/content/documentation/database-tutorials/bulk-upload.md @@ -1,9 +1,11 @@ --- title: Bulk Upload Vectors -weight: 13 +aliases: + - /documentation/tutorials/bulk-upload/ +weight: 1 --- -# Bulk upload a large number of vectors +# Bulk Upload Vectors to a Qdrant Collection Uploading a large-scale dataset fast might be a challenge, but Qdrant has a few tricks to help you with that. diff --git a/qdrant-landing/content/documentation/tutorials/create-snapshot.md b/qdrant-landing/content/documentation/database-tutorials/create-snapshot.md similarity index 98% rename from qdrant-landing/content/documentation/tutorials/create-snapshot.md rename to qdrant-landing/content/documentation/database-tutorials/create-snapshot.md index 670bdd796..d4a0163e1 100644 --- a/qdrant-landing/content/documentation/tutorials/create-snapshot.md +++ b/qdrant-landing/content/documentation/database-tutorials/create-snapshot.md @@ -1,9 +1,11 @@ --- -title: Create and restore from snapshot -weight: 14 +title: Create & Restore Snapshots +aliases: + - /documentation/tutorials/create-snapshot/ +weight: 2 --- -# Create and restore collections from snapshot +# Backup and Restore Qdrant Collections Using Snapshots | Time: 20 min | Level: Beginner | | | |--------------|-----------------|--|----| diff --git a/qdrant-landing/content/documentation/tutorials/huggingface-datasets.md b/qdrant-landing/content/documentation/database-tutorials/huggingface-datasets.md similarity index 95% rename from qdrant-landing/content/documentation/tutorials/huggingface-datasets.md rename to qdrant-landing/content/documentation/database-tutorials/huggingface-datasets.md index b0ea612ae..c43943d2e 100644 --- a/qdrant-landing/content/documentation/tutorials/huggingface-datasets.md +++ b/qdrant-landing/content/documentation/database-tutorials/huggingface-datasets.md @@ -1,9 +1,11 @@ --- -title: Load Hugging Face dataset -weight: 19 +title: Load a HuggingFace Dataset +aliases: + - /documentation/tutorials/huggingface-datasets/ +weight: 3 --- -# Loading a dataset from Hugging Face hub +# Load and Search Hugging Face Datasets with Qdrant [Hugging Face](https://huggingface.co/) provides a platform for sharing and using ML models and datasets. [Qdrant](https://huggingface.co/Qdrant) also publishes datasets along with the diff --git a/qdrant-landing/content/documentation/dl-tutorials.md b/qdrant-landing/content/documentation/dl-tutorials.md new file mode 100644 index 000000000..d28bd356e --- /dev/null +++ b/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 +--- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials/_index.md b/qdrant-landing/content/documentation/tutorials/_index.md deleted file mode 100644 index 055ed698a..000000000 --- a/qdrant-landing/content/documentation/tutorials/_index.md +++ /dev/null @@ -1,28 +0,0 @@ ---- -title: Tutorials -weight: 10 -# 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 ---- - -# Tutorials - -These tutorials demonstrate different ways you can build vector search into your applications. - -| Essential How-Tos | Description | Stack | -|---------------------------------------------------------------------------------|-------------------------------------------------------------------|---------------------------------------------| -| [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|