dominodatalab plugin for Claude

Debug Domino proxy and routing issues for web applications. Analyzes vite.config.js, package.json, and app.sh for misconfigurations.

Set up MLflow experiment tracking for traditional ML. Configures unique experiment names and auto-logging.

Set up GenAI tracing for an agent or LLM application. Adds Domino SDK imports, @add_tracing decorators, and DominoRun context.

Access external LLM providers through Domino AI Gateway - a secure proxy with centralized API key management, usage monitoring, and compliance. Supports OpenAI, AWS Bedrock, Azure OpenAI, Anthropic, and more. Use when…

Introduction to calling Domino platform APIs. Covers authentication (API proxy, PAT, service account), which host to use for which API, pagination limits, and common errors. Use before any other Domino API, SDK, app,…

Deploy web applications to Domino Data Lab with expertise in React apps (Vite) behind Domino's reverse proxy. Covers app.sh configuration, port configuration, base path handling for SPAs, CI/CD with GitHub Actions, an…

Connect Domino workloads to external data sources including AWS S3 (via Mountpoint CSI driver), credential propagation with AWS IRSA and Azure Entra ID, and External Data Volumes. Use when configuring S3 access, setti…

Use the domino-data Python SDK (dominodatalab-data) for programmatic data access in Domino. Covers DataSourceClient for SQL queries and object storage, DatasetClient for dataset files, TrainingSets for ML data version…

Work with Domino Datasets - high-performance, versioned filesystem storage. Covers dataset creation, snapshots for versioning, sharing across projects, mounting paths (/domino/datasets/), and performance optimization.…

Work with distributed computing frameworks in Domino including Apache Spark, Ray, and Dask clusters. Covers cluster configuration, on-demand clusters, choosing between frameworks, PySpark usage, and scaling workloads.…

Create and customize Domino Compute Environments - Docker containers defining tools, packages, and configurations. Covers Dockerfile customization, package installation, IDE configuration, DSE (Domino Standard Environ…

Track traditional ML experiments in Domino using the MLflow-based Experiment Manager. Covers experiment setup, auto-logging for sklearn/TensorFlow/PyTorch, manual logging, artifact storage, run comparison, and model r…

Build and operate Domino UI Extensions (mount Domino Apps in the shell with page context). Covers extension_manifest.json, official installer vs manual Extension API, publish and identity requirements, auth and host s…

Orchestrate multi-step ML workflows using Domino Flows (built on Flyte). Define DAGs with typed inputs/outputs, heterogeneous environments, automatic lineage, and reproducibility. Use when building data pipelines, mul…

Trace and evaluate GenAI applications including LLM calls, agents, RAG pipelines, and multi-step AI systems in Domino. Uses the Domino SDK (@add_tracing decorator, DominoRun context) with MLflow 3.2.0. Captures token…

Manage model risk governance in Domino using policies, bundles, and evidence. Covers creating governance bundles, attaching model artifacts and MLflow results as evidence, progressing through policy stages, and docume…

Create, run, and manage Domino Jobs - batch executions for scripts, training, and data processing. Covers job configuration, hardware tiers, scheduled jobs (cron), monitoring status, viewing logs, and API-driven execu…

Create Domino Launchers - parameterized web forms for self-service job execution. Enable business users to run analyses, generate reports, and trigger batch predictions without coding. Covers parameter types, email no…

Deploy and monitor model API endpoints in Domino. Covers creating prediction endpoints, version management, Grafana dashboards for latency/errors/resources, alerting, and GPU inference with NVIDIA Triton. Use when dep…

Monitor deployed models in Domino including drift detection, model quality tracking, and alerting. Covers data drift analysis, prediction capture, baseline comparison, alert configuration, and remediation workflows. U…

Deploy, invoke, and retire Domino model APIs and registered models via REST. Covers modelServing lifecycle, registered-models v1 vs v2 paths, MLflow tracking vs registry API, inference URLs vs management API, and GenA…

Enable AI-assisted model development within Domino by writing needed model and training code and using MCP (Model Context Protocol) servers to execute domino jobs. AI coding assistants like Cursor and GitHub Copilot c…

Work with Domino Projects including Git integration, DFS vs Git-based projects, collaboration, and version control. Covers project creation, Git provider setup (GitHub, GitLab, Bitbucket), branch management, collabora…

Programmatically interact with Domino using python-domino SDK and REST APIs. Covers authentication, running jobs, managing projects, file operations, model deployment, and automation. Use when automating Domino workfl…

Bootstrap or retrofit a Vite + React 18 + TypeScript project so it uses the Domino design system (`@dominodatalab/extensions-tools`). Scoped to projects that are (or will be) a **fully standalone SPA frontend for a Do…

Build Domino-styled web applications matching the Domino Design System. Use when creating or styling Domino apps (Dash, Streamlit, Flask, FastAPI+HTML), generating UI components, reviewing UX, or when the user mention…

Work with Domino Workspaces - interactive development environments including Jupyter, JupyterLab, VS Code, and RStudio. Covers launching workspaces, configuring hardware tiers, environment selection, volume mounting,…

Work with Domino Volumes for NetApp ONTAP - enterprise-grade, multi-terabyte storage with near-instant snapshots. Covers volume creation, snapshot versioning with commit messages, cross-project sharing, mount paths (/…

Manage Domino tags and properties via the Taxonomy API. Covers tags/namespaces (create, list, update, delete; tag entities — project, model, dataset, app, project_template, netapp_volume; query by tag; autocomplete; m…