Lin / docs /prd /technical-constraints-and-integration-requirements.md
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feat: Add comprehensive architecture, product requirements, and sprint documentation, alongside initial frontend pages and components.
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Technical Constraints and Integration Requirements

Existing Technology Stack

Languages: Python 3.8+, JavaScript/TypeScript Frameworks: Flask (backend), React with Vite (frontend), Redux Toolkit for state management Database: Supabase (PostgreSQL) Infrastructure: Docker support with docker-compose, Redis for Celery task queue External Dependencies:

  • Supabase client library
  • Gradio client for AI interactions
  • LinkedIn API for social media integration
  • Tailwind CSS for styling
  • Hugging Face API for AI content generation

Integration Approach

Database Integration Strategy: New keyword analysis data will be stored in temporary tables or cached in Redis to avoid schema changes. The existing Supabase schema will remain unchanged to maintain compatibility.

API Integration Strategy:

  • New endpoints will be added to the existing backend API in backend/api/posts.py to handle keyword trend analysis
  • The FLUX.1-dev image generation will be integrated into the existing content_service.py
  • All new API endpoints will follow the existing authentication patterns using JWT tokens

Frontend Integration Strategy:

  • New React components will be added to the existing component structure in frontend/src/components/
  • The keyword analysis feature will be integrated into the Posts page (frontend/src/pages/Posts.jsx)
  • Redux store will be updated with new slices to handle keyword analysis state

Testing Integration Strategy:

  • New unit tests will be added following the existing testing patterns in backend/tests/
  • Integration tests will be created to verify the keyword analysis functionality
  • Frontend component tests will be added following existing patterns

Code Organization and Standards

File Structure Approach: New files will follow the existing organization pattern:

  • Backend: New modules in backend/services/ and new API endpoints in backend/api/
  • Frontend: New components in frontend/src/components/ and new services in frontend/src/services/

Naming Conventions: Will follow existing Python (snake_case) and JavaScript (camelCase) conventions

Coding Standards: Will adhere to existing linting standards (ESLint for frontend, flake8 for backend)

Documentation Standards: Will follow existing documentation patterns with JSDoc-style comments for JavaScript and Python docstrings

Deployment and Operations

Build Process Integration: The new features will integrate with the existing Vite build process for the frontend and standard Python packaging for the backend

Deployment Strategy: Features will be deployed using the existing Docker and docker-compose setup without requiring additional infrastructure changes

Monitoring and Logging: Will use existing logging mechanisms in both frontend and backend following current patterns

Configuration Management: New environment variables will be added to existing .env files following the current pattern

Risk Assessment and Mitigation

Technical Risks:

  • API rate limits for keyword analysis from news sources
  • Performance impact of keyword trend analysis on the user experience
  • Integration complexity with the FLUX.1-dev image generation service

Integration Risks:

  • Maintaining backward compatibility with existing features
  • Ensuring the new keyword analysis doesn't disrupt existing content generation workflows
  • Proper authentication and authorization for new API endpoints

Deployment Risks:

  • Ensuring the new image generation service is reliable
  • Managing dependencies for the new FLUX.1-dev client

Mitigation Strategies:

  • Implement caching for keyword analysis results to reduce API calls
  • Add timeout handling and fallback mechanisms for external API calls
  • Create comprehensive tests to ensure existing functionality remains intact
  • Use feature flags to gradually roll out new functionality
  • Implement proper error handling and user feedback for failed operations