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AI-Powered Content Generation App Masterplan

App Overview and Objectives

This Next.js application aims to automate the workflow of content creation by leveraging AI to process video clips, generate summaries, and create social media posts. The primary objectives are:

  1. Streamline the process of converting video content into written posts for various platforms
  2. Utilize AI for transcription and summarization of video clips
  3. Provide a user-friendly interface for managing the content generation process

Target Audience

  • Content creators
  • Social media managers
  • Individuals looking to repurpose video content for multiple platforms

Core Features and Functionality

  1. Video Upload

    • Upload multiple video clips
    • Store uploaded videos using UploadThing

  2. AI Processing

    • Transcribe videos using OpenAI's Whisper API
    • Summarize transcriptions into a 2,000-word summary using GPT-4

  3. Prompt Configuration

    • Create and edit prompts for different social media platforms

  4. Content Generation

    • Generate platform-specific posts based on video summaries and configured prompts

  5. Results Management

    • View and copy generated content for each platform

  6. Job Queue System

    • Manage and track the status of processing jobs

High-Level Technical Stack

  1. Frontend:

    • Next.js with ShadCN UI components
    • Clerk for authentication

  2. Backend:

    • Next.js API routes for main application logic
    • Flask backend for AI processing tasks

  3. Database:

    • PostgreSQL with Drizzle ORM

  4. File Storage:

    • UploadThing for video storage

  5. AI Services:

    • OpenAI APIs (Whisper for transcription, GPT-4 for summarization and content generation)

Conceptual Data Model

  1. User

    • ID
    • Name
    • Email

  2. Project

    • ID
    • Title
    • CreationDate
    • Status

  3. VideoClip

    • ID
    • ProjectID
    • FileName
    • UploadThingURL

  4. Transcription

    • ID
    • VideoClipID
    • Content

  5. Summary

    • ID
    • ProjectID
    • Content

  6. Prompt

    • ID
    • ProjectID
    • Platform
    • Content

  7. GeneratedPost

    • ID
    • ProjectID
    • Platform
    • Content

  8. Job

    • ID
    • ProjectID
    • Type (Transcription, Summarization, PostGeneration)
    • Status (Ready, Running, Completed, Failed)
    • CreationDate

User Interface Design Principles

  1. Clean and intuitive design using ShadCN components
  2. Clear separation of different stages (Upload, Config, Run, Result)
  3. Easy-to-use drag-and-drop interface for video uploads
  4. Simple text areas for prompt configuration
  5. Clear display of job status and progress
  6. Easy-to-copy generated content in the Results stage

Security Considerations

  1. User authentication and authorization using Clerk
  2. Secure handling of API keys for OpenAI and UploadThing
  3. Proper data sanitization and validation for user inputs
  4. Secure storage of sensitive information (e.g., transcriptions, summaries)

Development Phases

  1. Phase 1: Project Setup and Basic Infrastructure

    • Set up Next.js project using app directory with ShadCN
    • Implement Clerk authentication
    • Set up PostgreSQL database and Drizzle ORM
    • Implement basic project management (create, list, view)

  2. Phase 2: Video Upload and Storage

    • Integrate UploadThing for video storage
    • Implement video upload functionality
    • Create video clip management interface

  3. Phase 3: AI Processing Integration

    • Set up Flask backend for AI tasks
    • Integrate OpenAI APIs (Whisper and GPT-4)
    • Implement transcription and summarization logic

  4. Phase 4: Prompt Configuration and Content Generation

    • Create prompt configuration interface
    • Implement content generation logic using GPT-4
    • Develop job queue system for processing runs

  5. Phase 5: Results Management and UI Refinement

    • Create results display interface
    • Implement copy-to-clipboard functionality
    • Refine overall user interface and experience

  6. Phase 6: Testing, Optimization, and Deployment

    • Conduct thorough testing of all features
    • Optimize performance and resource usage
    • Prepare for deployment and launch

Potential Challenges and Solutions

  1. Challenge: Handling large video files Solution: Implement chunked uploads and processing

  2. Challenge: Managing long-running AI tasks Solution: Implement robust job queue system with status updates

  3. Challenge: Ensuring accuracy of AI-generated content Solution: Implement review and editing features for generated content

  4. Challenge: Scalability of the system Solution: Design with scalability in mind, consider serverless architecture for AI processing

Future Expansion Possibilities

  1. Direct integration with social media platforms for posting
  2. Support for additional content types (e.g., audio, images)
  3. Advanced analytics and performance tracking for generated content
  4. Collaborative features for team-based content creation
  5. Custom AI model fine-tuning for improved summarization and content generation