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docs: reorganize the Use Cases tab by what each example builds
The tab is Use Cases now, grouped General, Search, RAG, Feature Engineering, Training, World Models -- one page per example, named for the example rather than for its position in a tree. The gallery pages that listed external notebooks become the More Examples entry of the category they belong to, instead of standing in front of the real tutorials. The top-level overview stops linking to itself through three levels of index page and names the categories directly. Branch experiments move to Feature Engineering, which is what they are an experiment in. The agent plugin leads General, since it applies to everything else in the tab. LeRobotDataset moves to the Datasets tab, where the LeRobot datasets already are, and Robotics moves to the top of that tab.
This commit is contained in:
Jack Ye
@@ -1,6 +1,6 @@
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---
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title: "Run experiments on branches"
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sidebarTitle: "Run experiments on branches"
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sidebarTitle: "Branch Experiments"
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description: "Use LanceDB branches to isolate agent-driven experiments from main, evaluate them on a fixed test set, and promote only the winner."
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icon: "flask"
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keywords: ["AI agents", "branches", "experiments", "embeddings", "evaluation"]
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@@ -1,6 +1,6 @@
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---
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title: "Tutorial: Use the LanceDB agent plugin"
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sidebarTitle: "LanceDB agent plugin"
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sidebarTitle: "Agent Plugin"
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description: "Install the LanceDB plugin and use an AI coding agent to quickly build a multimodal ingestion pipeline."
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icon: "robot"
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keywords: ["AI agents", "agent plugins", "multimodal", "Pydantic", "branches", "embeddings"]
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+31
-34
@@ -308,48 +308,45 @@
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]
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},
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{
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"tab": "Tutorials and Use Cases",
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"tab": "Use Cases",
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"groups": [
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{
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"group": "Tutorials",
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"group": "General",
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"pages": [
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"tutorials/index",
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{
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"group": "Search",
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"expanded": true,
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"pages": [
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"tutorials/search/index",
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"tutorials/search/multivector-needle-in-a-haystack"
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]
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},
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{
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"group": "RAG & Agents",
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"expanded": true,
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"pages": [
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"tutorials/agents/index",
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"tutorials/agents/nvidia-rag-blueprint/index",
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"tutorials/agents/time-travel-rag/index",
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"tutorials/agents/multimodal-agent/index"
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]
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},
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"tutorials/feature-engineering/index",
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"build-with-ai-agents"
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]
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},
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{
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"group": "Search",
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"pages": [
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"tutorials/search/multivector-needle-in-a-haystack",
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"tutorials/search/index"
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]
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},
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{
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"group": "RAG",
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"pages": [
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"tutorials/agents/nvidia-rag-blueprint/index",
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"tutorials/agents/time-travel-rag/index",
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"tutorials/agents/multimodal-agent/index",
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"tutorials/agents/index"
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]
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},
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{
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"group": "Feature Engineering",
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"pages": [
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"agent-branch-experiments",
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"tutorials/feature-engineering/index"
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]
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},
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{
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"group": "Training",
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"pages": [
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"training/object-detection",
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"training/vlm-finetuning"
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]
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},
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{
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"group": "AI Agents",
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"pages": [
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"build-with-ai-agents",
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"agent-branch-experiments"
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]
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},
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{
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"group": "Robotics",
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"pages": [
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"integrations/lerobotdataset"
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]
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},
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{
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"group": "World Models",
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"pages": [
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@@ -1,6 +1,6 @@
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---
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title: "Object Detection for AV Perception"
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sidebarTitle: "Example: Object Detection"
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sidebarTitle: "Object Detection"
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description: End-to-end fine-tuning of a Faster R-CNN object detector on curated dashcam slices, using LanceDB as the data backbone from raw frames to checkpoints.
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icon: car
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---
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@@ -1,6 +1,6 @@
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---
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title: "Fine-tuning a VLM on TextVQA"
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sidebarTitle: "Example: VLM finetuning"
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sidebarTitle: "VLM Fine-tuning"
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description: End-to-end fine-tuning of Qwen2.5-VL on a curated TextVQA slice, using LanceDB and Geneva to materialize expensive vision-language features once and train from cached columns.
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icon: image
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---
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@@ -1,7 +1,7 @@
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---
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title: "RAG and Agents"
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sidebarTitle: "Notebooks"
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description: "Explore a variety of RAG (Retrieval-Augmented Generation) and agent applications built with LanceDB."
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title: "More RAG examples"
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sidebarTitle: "More Examples"
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description: "Notebooks covering contextual RAG, HyDE, late chunking, agentic RAG and more."
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---
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The table below lists example notebooks we've prepared for a variety of RAG (Retrieval-Augmented Generation)
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@@ -1,7 +1,7 @@
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---
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title: "Feature Engineering"
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sidebarTitle: "Feature Engineering"
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description: "Learn how to build features for your data in LanceDB."
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title: "More feature engineering examples"
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sidebarTitle: "More Examples"
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description: "Notebooks covering derived features and materialized views."
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layout: wide
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---
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@@ -1,23 +1,27 @@
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---
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title: "Tutorials"
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title: "Use cases"
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sidebarTitle: "Overview"
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description: "Step-by-step tutorials for building applications with LanceDB"
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description: "Worked examples of building with LanceDB, by what you are building."
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---
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Explore tutorials organized by use case:
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Each page here is one worked example, grouped by what it builds. The
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documentation explains how a feature works; these show it doing something.
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| Tutorial | Description |
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| | |
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|:---------|:------------|
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| [Search & advanced retrieval](/tutorials/search/) | Learn how to perform vector search and use advanced retrieval techniques. |
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| [Agents](/tutorials/agents/) | Build Retrieval-Augmented Generation (RAG) applications and agents with LanceDB. |
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| [Working with tables in LanceDB](/tables/) | Learn the basics of working with tables in LanceDB: creation, ingestion and schema evolution. |
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| [Search](/tutorials/search/multivector-needle-in-a-haystack) | Vector, multi-vector, hybrid and full-text retrieval. |
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| [RAG](/tutorials/agents/nvidia-rag-blueprint/) | Retrieval-augmented generation and agent applications. |
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| [Feature engineering](/tutorials/feature-engineering/) | Deriving columns, materialized views, and experimenting on branches. |
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| [Training](/training/object-detection) | Curating data and training models directly on a table. |
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Each category also has a **More examples** page collecting runnable notebooks
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that live in the recipes repository rather than here.
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## Recipes {#recipes}
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If you're looking for ideas and hands-on code examples, we've worked on a collection of practical
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projects in the repository linked below.
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If you are looking for ideas and hands-on code, the repository below collects
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practical projects beyond the ones documented here.
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<Card icon="code" title="VectorDB recipes" href="https://github.com/lancedb/vectordb-recipes">
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Check out past code examples and tutorials [here](https://github.com/lancedb/vectordb-recipes)
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on GitHub.
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Past code examples and tutorials on GitHub.
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</Card>
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@@ -1,7 +1,7 @@
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---
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title: "Search Tutorials"
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sidebarTitle: "Overview"
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description: "Learn how vector, full-text and hybrid search work in LanceDB."
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title: "More search examples"
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sidebarTitle: "More Examples"
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description: "Notebooks covering hybrid search, multi-vector retrieval, video search and more."
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layout: wide
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---
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@@ -1,6 +1,6 @@
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---
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title: "Finding the Needle in a Haystack: Comparing Multi-vector Search Strategies"
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sidebarTitle: "Multi-vector search: Needle in a Haystack"
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sidebarTitle: "Needle in a Haystack"
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description: "Tutorial on token-level retrieval with LanceDB multivector search."
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---
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