> browse/registry

> outlines

You are an expert in Outlines, the Python library for reliable structured text generation with LLMs. You help developers generate guaranteed-valid JSON, regex-matching text, and grammar-constrained output from open-source models — using finite state machine guided generation that constrains the token sampling process to produce only valid output on the first try.

> moviepy

Edit and compose video with Python using MoviePy. Use when a user asks to programmatically edit videos, create video montages, add text overlays, build automated video pipelines, composite multiple clips, apply video effects, generate social media videos from templates, concatenate clips, extract audio, create GIFs, build slideshows, add transitions, resize and crop videos, or integrate video editing into Python applications. Covers MoviePy 2.x for compositing, effects, text, and rendering.

> celery

Run background tasks in Python with Celery. Use when a user asks to process tasks asynchronously, schedule periodic jobs, run background workers, build task queues in Python, or offload heavy processing from web requests.

> jupyter

Assists with interactive data analysis, visualization, and reproducible research using Jupyter notebooks. Use when building notebooks that combine code with rich output, managing kernels, converting to reports, or parameterizing notebooks for batch execution. Trigger words: jupyter, notebook, jupyterlab, ipynb, nbconvert, papermill.

> pandera

Expert guidance for Pandera, the Python library for validating pandas and Polars DataFrames with expressive schemas. Helps developers define data contracts, validate data pipelines, and catch data quality issues before they corrupt downstream systems.

> modal

Serverless GPU compute platform for running Python functions in the cloud. Deploy ML models, run training jobs, and serve inference endpoints without managing infrastructure. Supports A100/H100 GPUs, custom container images, and scales to zero automatically.

> instructor

You are an expert in Instructor, the library for getting structured, validated output from LLMs. You help developers extract typed data from unstructured text using Pydantic models (Python) or Zod schemas (TypeScript), with automatic retries on validation failures, streaming partial objects, and support for OpenAI, Anthropic, Google, and local models — turning LLMs into reliable data extraction engines.

> ruff

Lint and format Python with Ruff. Use when a user asks to set up Python linting, replace flake8/black/isort, configure code quality rules, or speed up Python code formatting.

> microsoft-word

Create, edit, and manipulate Word documents (.docx) programmatically. Use when someone asks to "generate a Word document", "create a report in docx", "mail merge", "fill Word template", "extract text from Word", "convert markdown to Word", "add tables to Word", or "automate document generation". Covers python-docx for file manipulation, docxtpl for templates, and Microsoft Graph API for cloud documents.

> powerpoint

Create, edit, and manipulate PowerPoint (.pptx) files programmatically using python-pptx. Use when a user asks to generate a PPTX, modify slides, extract text from a presentation, add charts or tables to PowerPoint, build slides from data, convert content to PPTX, or automate PowerPoint file creation.

> pytest

Test Python code with pytest. Use when a user asks to write unit tests, set up test fixtures, mock dependencies, run async tests, measure coverage, or implement test-driven development in Python.

> pydantic

Validate and serialize data with Pydantic. Use when a user asks to validate API inputs, parse JSON/env config, define data models in Python, serialize objects, or implement data validation with type hints.

> pytorch

Assists with building, training, and deploying neural networks using PyTorch. Use when designing architectures for computer vision, NLP, or tabular data, optimizing training with mixed precision and distributed strategies, or exporting models for production inference. Trigger words: pytorch, torch, neural network, deep learning, training loop, cuda.

> bptools-writer

Create, edit, and validate biology-problems bptools Python question generators and supporting YAML content. Use when requests involve authoring question scripts, updating files under problems/*-problems, tuning randomization or anti-cheat behavior, or debugging BBQ/QTI output that depends on bptools.py and qti_package_maker.

> meilisearch

Add fast, typo-tolerant full-text search with Meilisearch. Use when a user asks to add search to an app, implement full-text search, set up a search engine, replace Elasticsearch with something simpler, add autocomplete or instant search, build a product catalog search, index documents for search, configure search relevancy, add faceted filtering, or deploy a self-hosted search engine. Covers indexing, querying, facets, filtering, sorting, multi-tenancy, and integration with Node.js, Python, and

> gradio

Python library for building ML demo UIs with minimal code. Create interactive web interfaces for models with text, image, audio, and video inputs/outputs. Share demos via public links or deploy to Hugging Face Spaces.

> test-generator

Generate unit, integration, and end-to-end tests for existing code. Use when a user asks to write tests, add test coverage, create unit tests, generate integration tests, build e2e tests, improve code coverage, write specs, or add testing to a project. Supports Jest, Vitest, Pytest, Playwright, React Testing Library, and Cypress. Analyzes code to produce meaningful assertions, edge cases, and mock setups.

> triton

NVIDIA Triton Inference Server for deploying AI models at scale. Supports multiple frameworks (ONNX, TensorRT, PyTorch, TensorFlow), model ensembles, dynamic batching, model versioning, and GPU/CPU inference with high throughput and low latency.

> great-expectations

Great Expectations is a Python framework for data quality testing and validation. Learn to define expectations, create validation suites, build data docs, and integrate with data pipelines for automated quality checks.

> django

Django is a batteries-included Python web framework that follows the model-template-view pattern. It provides an ORM, admin interface, authentication, and everything needed to build full-featured web applications rapidly and securely.