databricks-apps-streamlit-vibe-coding-starter

How to custom-style a Streamlit application with a modern, stable theming stack — reusable theme TOML files, self-hosted fonts, light/dark modes, sidebar theming, chart palettes, shared page bootstrap, and scoped CSS for custom component variants. Use this skill PROACTIVELY whenever the user wants to style, theme, brand, or customize the appearance of a Streamlit app — including changing colors, fonts, buttons, sidebar look, dark mode, chart colors, or adding custom CSS. Also use when the user mentions config.toml theming, Streamlit design systems, or asks how to make a Streamlit app look professional/branded. Even if the user only asks about one aspect (e.g. "change the sidebar color"), apply this skill because the answer depends on which styling layer is appropriate.

Quick reference for building full-stack Databricks Apps with apx (React + FastAPI). Use when working on apx projects, creating routes, adding components, or managing dev servers.

Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Multi-Agent Supervisors (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.

Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources

Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.

Deploy and query Databricks Model Serving endpoints. Use when (1) deploying MLflow models or AI agents to endpoints, (2) creating ChatAgent/ResponsesAgent agents, (3) integrating UC Functions or Vector Search tools, (4) querying deployed endpoints, (5) checking endpoint status. Covers classical ML models, custom pyfunc, and GenAI agents.

Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures.

Generate realistic synthetic data using Faker and Spark, with non-linear distributions, integrity constraints, and save to Databricks. Use when creating test data, demo datasets, or synthetic tables.

Generate synthetic PDF documents for RAG and unstructured data use cases. Use when creating test PDFs, demo documents, or evaluation datasets for retrieval systems.

Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC. Use when creating producers that write directly to Unity Catalog tables without a message bus, working with the Zerobus Ingest SDK in Python/Java/Go/TypeScript/Rust, generating Protobuf schemas from UC tables, or implementing stream-based ingestion with ACK handling and retry logic.

Build production-grade Streamlit apps. Used when creating, editing, debugging, or deploying Streamlit applications. Routes to specialized sub-skills for performance, layouts, design, data display, and more.

Building dashboards in Streamlit. Use when creating KPI displays, metric cards, or data-heavy layouts. Covers borders, cards, responsive layouts, and dashboard composition.

Connecting Streamlit apps to Snowflake. Use when setting up database connections, managing secrets, or querying Snowflake from a Streamlit app.

Creating and customizing Streamlit themes. Use when changing app colors, fonts, or appearance, or aligning apps to brand guidelines. Covers config.toml configuration, design principles, and CSS avoidance.

Setting up Python environments for Streamlit apps. Use when creating a new project or managing dependencies. Covers uv for dependency management and running apps.