Sim2RL
Sim2RL: Realistic Persona Generation for AI Agent Training Testing customer service chatbots is hard - you need realistic users, not scripted scenarios.
Core trick
Generates personas from web-researched complaints, runs simulated chats against a live bot, and logs transcripts as RL training data.
Description
Sim2RL: Realistic Persona Generation for AI Agent Training
Testing customer service chatbots is hard - you need realistic users, not
scripted scenarios. We built a system that auto-generates authentic
customer personas by researching real complaints and interactions.
What we built:
- Web-powered persona creation (frustrated travelers, confused
passengers, etc.)
- Full conversation capture with screenshots
- RL training data pipeline from simulation results
- Live testing on Alaska Airlines chat
Demo: Complete flow from "create angry frequent flyer" → realistic
conversation → performance analysis → training data for chatbot
improvement.
This approach could prevent costly AI failures like the Air Canada
chatbot lawsuit by ensuring proper testing before deployment.
README excerpt
# Sim2RL: AI-Powered Simulation Agents for Reinforcement Learning *Generate realistic user personas for training conversational AI agents through advanced simulation and reinforcement learning* ## 🚀 Overview Sim2RL bridges the gap between AI evaluation and reinforcement learning by automatically generating authentic user personas that act as dynamic training environments. Instead of static test scripts, we create intelligent simulation agents that research real-world behaviors and adapt their interactions based on actual user patterns. ## ⚡ Key Features - **Autonomous Persona Research**: AI agents automatically discover and synthesize real user behaviors from web data - **Dynamic Simulation Environments**: Personas evolve and adapt during conversations, creating realistic training scenarios - **Multi-Modal RL Training Data**: Captures both conversational text and visual interface states for comprehensive agent training - **Real-World Integration**: Test against live production systems while generating training data - **Continuous Learning Pipeline**: Simulation results feed directly into RL training loops for autonomous improvement ## 🛠 Quick Start ```bash # Setup environment pip install -r requirements.txt playwright install # Configure API keys cp .env.example .env # Edit .env with your keys # Launch interactive persona generator python interactive_alaska_simulation.py ``` ## 🎯 How It Works 1. **Persona Genesis**: Describe a user type → AI researches real behavio