dashboard_test

Imported from codeprotege/dashboard_test (AGENTS.md). Install upstream with npx skills add codeprotege/dashboard_test. Copyright stays with the author.

Agent Instructions for Financial Dashboard

This file provides guidance for AI agents working on this project.

General Guidelines

1. Follow the plan: Adhere to the established project plan and phases.
2. Modular Code: Write modular and reusable code.
3. Testing: Implement unit and integration tests for all new features.
4. Documentation: Keep documentation (code comments, API docs, user guides) up-to-date.
5. Commit Messages: Write clear and descriptive commit messages (e.g., Conventional Commits).
6. Dependencies: Add new dependencies to requirements.txt using pip freeze > requirements.txt after installation in the active virtual environment.

Backend (FastAPI)

• Organize code into routers (e.g., in a backend/routers directory).
• Use Pydantic models for request/response validation (backend/schemas.py).
• Implement proper error handling and logging.
• Follow RESTful API design principles.
• Database models go into backend/models.py.
• Database connection and session management in backend/database.py.
• Configuration using .env and Pydantic settings in backend/config.py.

Frontend (Streamlit)

• Keep the UI clean and intuitive (frontend/app.py and frontend/pages/).
• Ensure responsiveness across different screen sizes.
• Optimize for performance, especially with large datasets.
• Store session state variables using st.session_state.

Data

• Handle data securely, especially API keys and user data. Store API keys in .env.
• Implement efficient data caching strategies (e.g., Streamlit's caching, database caching).

Forecasting

• Clearly document the forecasting models used and their assumptions.
• Provide metrics for forecast accuracy if possible.

Specific Tasks

• API Integration: When integrating with external financial APIs, store API keys securely using environment variables loaded via backend/config.py from the .env file. Do not commit API keys to the repository. The .env file is in .gitignore.
• Database: Use SQLAlchemy for database interactions. Define models in backend/models.py and Pydantic schemas in backend/schemas.py. Initialize database tables from backend/main.py (on startup for dev) or using Alembic for migrations in production.
• Authentication: Implement JWT-based authentication. Store SECRET_KEY in .env.
• WebSockets: Ensure WebSocket connections are handled robustly and efficiently for real-time updates.