diff --git a/docs/docs/app-management.mdx b/docs/docs/app-management.mdx index e2a5976..75d484b 100644 --- a/docs/docs/app-management.mdx +++ b/docs/docs/app-management.mdx @@ -12,7 +12,7 @@ Manage your AppKit application throughout its lifecycle using the Databricks CLI ## Create app -See the [Quick start](./index.md#quick-start-options) section to create a new Databricks app with AppKit installed. +See the [Quick start](./index.md) section to create a new Databricks app with AppKit installed. ## Configuration diff --git a/docs/docs/development/ai-assisted-development.mdx b/docs/docs/development/_ai-assisted-development.mdx similarity index 100% rename from docs/docs/development/ai-assisted-development.mdx rename to docs/docs/development/_ai-assisted-development.mdx diff --git a/docs/docs/development/_prerequisites_app.mdx b/docs/docs/development/_prerequisites_app.mdx index 32ec33e..4423e23 100644 --- a/docs/docs/development/_prerequisites_app.mdx +++ b/docs/docs/development/_prerequisites_app.mdx @@ -2,4 +2,4 @@ - [Node.js](https://nodejs.org) environment - Databricks CLI: install and configure it according to the [official tutorial](https://docs.databricks.com/aws/en/dev-tools/cli/tutorial). -- A new Databricks app with AppKit installed. See [Bootstrap a new Databricks app](../index.md#quick-start-options) for more details. +- A new Databricks app with AppKit installed. See [Bootstrap a new Databricks app](../index.md) for more details. diff --git a/docs/docs/development/index.mdx b/docs/docs/development/index.mdx index 9c1c838..eb1aa46 100644 --- a/docs/docs/development/index.mdx +++ b/docs/docs/development/index.mdx @@ -15,8 +15,7 @@ AppKit provides multiple development workflows to suit different needs: local de There are multiple supported development flows available with AppKit: 1. **[Local development](./local-development.mdx)**: Run the development server with hot reload for both UI and backend code. This is the default development flow and is suitable for most use cases. -2. **[AI-assisted development](./ai-assisted-development.mdx)**: Use an AI coding assistant connected via the Databricks MCP server to explore data, run CLI commands, and scaffold your app interactively. -3. **[Remote Bridge](./remote-bridge.mdx)**: Create a remote bridge to a deployed backend while keeping your queries and UI local. This is useful for testing against production data or debugging deployed backend code without redeploying your app. +1. **[Remote Bridge](./remote-bridge.mdx)**: Create a remote bridge to a deployed backend while keeping your queries and UI local. This is useful for testing against production data or debugging deployed backend code without redeploying your app. ## See also diff --git a/docs/docs/development/local-development.mdx b/docs/docs/development/local-development.mdx index d2d56de..23a27fb 100644 --- a/docs/docs/development/local-development.mdx +++ b/docs/docs/development/local-development.mdx @@ -8,7 +8,7 @@ import Prerequisites from './_prerequisites_app.mdx'; -Once your app is bootstrapped according to the [Manual quick start](../index.md#manual-quick-start) guide, you can start the development server with hot reload for both UI and backend code. +Once your app is bootstrapped according to the [Manual quick start](../index.md) guide, you can start the development server with hot reload for both UI and backend code. In the application root directory, run the following command to start the development server: diff --git a/docs/docs/index.md b/docs/docs/index.md index b684f68..9830ef4 100644 --- a/docs/docs/index.md +++ b/docs/docs/index.md @@ -20,36 +20,7 @@ AppKit simplifies building data applications on Databricks by providing: -## Quick start options - -There are two ways to get started with AppKit: - -- **AI-assisted** (recommended): Use an AI coding assistant connected via the Databricks MCP server to explore data, run CLI commands, and scaffold your app interactively. -- **Manual**: Use the Databricks CLI directly to create, bootstrap, and deploy your app. - -Choose the path that best fits your workflow; both approaches produce the same kind of AppKit-based Databricks application. - -## AI-first quick start - -Databricks AppKit is designed to work with AI coding assistants through the Databricks MCP server. - -Install the Databricks MCP server and configure it for use with your preferred AI assistant: - -```bash -databricks experimental apps-mcp install -``` - -Once configured for your development environment, you can use your AI assistant to create and deploy new Databricks applications, as well as to iteratively evolve your app's codebase. - -Just prompt your AI assistant to create a new Databricks app, such as: - -``` -Create a new Databricks app that displays a dashboard of the nyc taxi trips dataset. -``` - -To learn more about the MCP server, see the [AI-assisted development](./development/ai-assisted-development.mdx) documentation. - -## Manual quick start +## Quick start Learn how to create and deploy a sample Databricks application that uses AppKit with the Databricks CLI. diff --git a/template/package.json b/template/package.json index 9347530..71db79c 100644 --- a/template/package.json +++ b/template/package.json @@ -28,8 +28,8 @@ "license": "Unlicensed", "description": "{{.app_description}}", "dependencies": { - "@databricks/appkit": "0.2.0", - "@databricks/appkit-ui": "0.2.0", + "@databricks/appkit": "0.3.0", + "@databricks/appkit-ui": "0.3.0", "@databricks/sdk-experimental": "^0.14.2", "clsx": "^2.1.1", "embla-carousel-react": "^8.6.0",