Ragman: Software Infrastructure For Ai Assistants

Brief Description

A software infrastructure designed to rapidly develop and test aligned conversational AI assistants for specific tasks.

Full Description

Researchers at UCI have developed a comprehensive infrastructure for creating and evaluating conversational AI assistants, focusing on alignment with organizational values and expectations through advanced prompt engineering and behavioral testing. It aims to streamline the development process, reduce costs, and ensure the assistants' reliability and safety across various domains.

Suggested uses

• Education: AI tutors for personalized student support without giving out complete solutions. 
• Healthcare: AI assistants for clinical decision-making 
• Finance and Enterprise: Custom AI assistants for niche-specific information handling and task execution.

Advantages

• Configurable prompts and processing steps for rapid experimentation and development. 
• Automated generation of behavioral test cases to assess alignment with knowledge bases. 
• Reduces the need for extensive and costly user studies by automating behavioral configuration and testing. 
• Supports multiple Large Language Models (LLMs) beyond OpenAI, including Mistral and Llama.
• Designed with strong alignment guarantees to prevent the assistant from providing incorrect information or "hallucinations".