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AI Talk Show Gameplan ​

Overview ​

Create a TypeScript-based simulation of a talk show with two customizable AI personalities that react to topics in character.

Architecture & Tech Stack ​

  • Core: TypeScript/Node.js for backend logic
  • Libraries: readline for CLI, fs for config, possibly openai or similar for AI responses if integrating LLMs
  • Structure: Separate files for classes (e.g., ai.ts, topic.ts), main entry index.ts

Detailed Implementation ​

1. Define AI Personalities ​

  • Create TypeScript classes for each AI (e.g., HostAI and GuestAI)
  • Properties: name, personalityTraits (array of strings like "witty", "serious")
  • Methods: react(topic: Topic) to generate responses based on personality
  • Expansion: Include reaction templates (e.g., "witty": ["That's hilarious!", "Let's joke about it..."]), scoring system for topic relevance

2. Topic Handling ​

  • Implement a Topic class with title and description
  • AI reactions vary by traits (e.g., witty adds humor, serious provides analysis)
  • Expansion: Add categories (e.g., politics, tech), user input validation, dynamic topic generation

3. Conversation Simulation ​

  • Main loop in index.ts to alternate turns
  • Host introduces topic, Guest reacts, Host responds, etc.
  • Use random or scripted elements for natural flow
  • Expansion: Implement turn-based logic with timers, interrupt handling, conversation history storage

4. Personalization ​

  • Config file (e.g., config.json) for user-set traits
  • Load at startup to customize AI behaviors
  • Expansion: JSON schema for config, UI for editing traits in CLI

5. Output and Interaction ​

  • Compile to JS and run via Node.js
  • CLI prompts for topics/personalities using readline
  • Optional: Expand to web interface later

6. Testing and Iteration ​

  • Start with simple reactions and sample topics
  • Refine for coherence; use TypeScript for type safety

Features & User Stories ​

  • As a user, I want to set AI names and traits via config
  • As a user, I want real-time conversation output
  • As a user, I want to save/load conversation logs
  • Bonus: Voice synthesis, web UI with React

Dependencies & Setup ​

  • List npm packages: typescript, readline, @types/node
  • Installation steps, build commands (npm run build, npm run watch)

Challenges & Solutions ​

  • Natural language generation: Use predefined responses initially, upgrade to AI APIs later
  • Personality consistency: Implement stateful memory for past reactions
  • Performance: Optimize for CLI, avoid heavy computations

Testing Strategy ​

  • Unit tests for classes (Jest), integration tests for full simulation
  • Sample topics: "Climate Change", "AI Ethics" with expected reactions

Milestones & Timeline ​

  • Week 1: Basic classes and CLI
  • Week 2: Conversation logic and personalization
  • Week 3: Testing, refinements, and optional features

Future Enhancements ​

  • Multi-AI support, topic voting, integration with external APIs for dynamic content