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Master Vue 3 Composition API reactivity patterns including ref, reactive, computed properties, and deep reactivity for building modern Vue applications.

Master React's three-phase rendering process (trigger, render, commit) by analyzing components and understanding when and why React updates the DOM.

Generate comprehensive documentation for Next.js Server Components, explaining rendering strategies, when to use Server vs Client Components, data passing patterns, and best practices for the App Router.

Expert guidance on implementing and working with React Server Components, including async patterns, client-server composition, and data fetching strategies.

Manage complex React state by combining useReducer with Context API to avoid prop drilling and centralize state logic across component trees.

Track and visualize machine learning experiments with W&B. Log metrics, hyperparameters, and model artifacts for ML training runs.

Comprehensive reference guide for all built-in React hooks including state management, effects, context, refs, and performance optimization hooks with usage examples.

Format Python code with Black, the uncompromising code formatter. Automatically applies PEP 8 compliant opinionated formatting for consistent, readable code.

Add optional static typing to Python programs using mypy. Catch programming errors through static analysis without running code. Supports type inference, gradual typing, generics, and union types.

Install and use scikit-learn, a comprehensive Python library for machine learning and data mining built on NumPy and SciPy with classification, regression, clustering, and dimensionality reduction capabilities.

State-of-the-art pretrained models for text, vision, audio, and multimodal ML tasks. Unified API for inference and training with PyTorch, supporting 1M+ model checkpoints on Hugging Face Hub.

Install and set up PyTorch (torch) - Python deep learning framework with GPU acceleration for tensor computation and neural networks

Python client for Qdrant vector database. Supports local and cloud modes, FastEmbed integration, async operations, and both REST and gRPC protocols.

Analyze and work with the LanceDB Python library for vector database operations

Set up and use ChromaDB, the open-source embedding database for LLM applications with semantic search and memory capabilities.

Microsoft's AI orchestration SDK for building agents, multi-agent systems, and AI workflows with Python. Supports OpenAI, Azure, Hugging Face, and 20+ LLM providers.

Analyze PyPI packages and extract structured information

A guidance language for controlling large language models with interleaved generation, prompting, and logical control in a single continuous flow.

GenAI agent framework for building production-grade applications with LLMs using Pydantic validation, type safety, and dependency injection

Extract reliable structured JSON from LLMs using Pydantic models for validation, type safety, and automatic retries with the Instructor library