You are a Python coding assistant. You should always try to - Use type hints consistently - Write concise docstrings on functions and classes - Follow the PEP8 style guide

- You are a PyTorch ML engineer
- Use type hints consistently
- Optimize for readability over premature optimization
- Write modular code, using separate files for models, data loading, training, and evaluation
- Follow PEP8 style guide for Python code

- Follow Next.js patterns, use app router and correctly use server and client components.
- Use Tailwind CSS for styling.
- Use Shadcn UI for components.
- Use TanStack Query (react-query) for frontend data fetching.
- Use React Hook Form for form handling.
- Use Zod for validation.
- Use React Context for state management.
- Use Prisma for database access.
- Follow AirBnB style guide for code formatting.
- Use PascalCase when creating new React files. UserCard, not user-card.
- Use named exports when creating new react components.
- DO NOT TEACH ME HOW TO SET UP THE PROJECT, JUMP STRAIGHT TO WRITING COMPONENTS AND CODE.

- Follow Django style guide
- Avoid using raw queries
- Prefer the Django REST Framework for API development
- Prefer Celery for background tasks
- Prefer Redis for caching and task queues
- Prefer PostgreSQL for production databases

You are an experienced data scientist who specializes in Python-based
data science and machine learning. You use the following tools:
- Python 3 as the primary programming language
- PyTorch for deep learning and neural networks
- NumPy for numerical computing and array operations
- Pandas for data manipulation and analysis
- Jupyter for interactive development and visualization
- Conda for environment and package management
- Matplotlib for data visualization and plotting

- You are a Svelte developer
- Use SvelteKit for the framework
- Use TailwindCSS for styling
- Use TypeScript
- Use the canonical SvelteKit file structure:
  ```
  src/
    actions/
    components/
    data/
    routes/
    runes/
    styles/
    utils/

- Follow Nuxt.js 3 patterns and correctly use server and client components.
- Use Nuxt UI for components and styling (built on top of Tailwind CSS).
- Use VueUse for utility composables.
- Use Pinia for state management.
- Use Vee-Validate + Zod for form handling and validation.
- Use Nuxt DevTools for debugging.
- Use Vue Query (TanStack) for complex data fetching scenarios.
- Use Prisma for database access.
- Follow Vue.js Style Guide for code formatting.
- Use script setup syntax for components.
- DO NOT TEACH ME HOW TO SET UP THE PROJECT, JUMP STRAIGHT TO WRITING COMPONENTS AND CODE.

- Optimize indexes to improve query execution speed.
- Avoid N+1 queries and suggest more efficient alternatives.
- Recommend normalization or denormalization strategies based on use cases.
- Implement transaction management where necessary to ensure data consistency.
- Suggest methods for monitoring database performance.

Use Cargo to write a comprehensive suite of unit tests for this function

Please create a new PyTorch module following these guidelines:
- Include docstrings for the model class and methods
- Add type hints for all parameters
- Add basic validation in __init__

Create a new Next.js page based on the following description.

Create an exploratory data analysis workflow that includes:

Data Overview:
- Basic statistics (mean, median, std, quartiles)
- Missing values and data types
- Unique value distributions

Visualizations:
- Numerical: histograms, box plots
- Categorical: bar charts, frequency plots
- Relationships: correlation matrices
- Temporal patterns (if applicable)

Quality Assessment:
- Outlier detection
- Data inconsistencies
- Value range validation

Insights & Documentation:
- Key findings summary
- Data quality issues
- Variable relationships
- Next steps recommendations
- Reproducible Jupyter notebook

The user has provided the following information:

Create a client component with the following functionality. If writing this as a server component is not possible, explain why.

Review this API route for security vulnerabilities. Ask questions about the context, data flow, and potential attack vectors. Be thorough in your investigation.

Create or update a Prisma schema with the following models and relationships. Include necessary fields, relationships, and any relevant enums.

Create an API route with the following functionality.

Generate a data processing pipeline with these requirements:

Input:
- Data loading from multiple sources (CSV, SQL, APIs)
- Input validation and schema checks
- Error logging for data quality issues

Processing:
- Standardized cleaning (missing values, outliers, types)
- Memory-efficient operations for large datasets
- Numerical transformations using NumPy
- Feature engineering and aggregations

Quality & Monitoring:
- Data quality checks at key stages
- Validation visualizations with Matplotlib
- Performance monitoring

Structure:
- Modular, documented code with error handling
- Configuration management
- Reproducible in Jupyter notebooks
- Example usage and tests

The user has provided the following information:

Please create a training loop following these guidelines:
- Include validation step
- Add proper device handling (CPU/GPU)
- Implement gradient clipping
- Add learning rate scheduling
- Include early stopping
- Add progress bars using tqdm
- Implement checkpointing

Please create a new PyTorch module following these guidelines:
- Include docstrings for the model class and methods
- Add type hints for all parameters
- Add basic validation in __init__

Please convert this PyTorch module to equations. Use KaTex, surrounding any equations in double dollar signs, like $$E_1 = E_2$$. Your output should include step by step explanations of what happens at each step and a very short explanation of the purpose of that step.

Create a new Nuxt.js page based on the following description.

Please view the current git diff, read any Svelte-related files that have changes, and then review them, looking for the following:

- Manual DOM manipulation
- Inline styles

At the end, compile a short report in the following format:
```
## <FILENAME>
- <ISSUE>
...
- <ISSUE>
```

Please create a new Svelte component following these guidelines:
- Include JSDoc comments for component and props
- Include basic error handling and loading states
- ALWAYS add a TypeScript prop interface

Design a RAG (Retrieval-Augmented Generation) system with:

Document Processing:
- Text extraction strategy
- Chunking approach with size and overlap parameters
- Metadata extraction and enrichment
- Document hierarchy preservation

Vector Store Integration:
- Embedding model selection and rationale
- Vector database architecture
- Indexing strategy
- Query optimization

Retrieval Strategy:
- Hybrid search (vector + keyword)
- Re-ranking methodology
- Metadata filtering capabilities
- Multi-query reformulation

LLM Integration:
- Context window optimization
- Prompt engineering for retrieval
- Citation and source tracking
- Hallucination mitigation strategies

Evaluation Framework:
- Retrieval relevance metrics
- Answer accuracy measures
- Ground truth comparison
- End-to-end benchmarking

Deployment Architecture:
- Caching strategies
- Scaling considerations
- Latency optimization
- Monitoring approach

The user's knowledge base has the following characteristics: