Context-Specific Agent Routing in StackSpot AI

[joaonetozup]

Summary

This initiative focuses on developing a sophisticated routing system for agents in StackSpot AI, enabling the platform to select the most appropriate agent template based on the user's context and query. By identifying and implementing context-specific agent templates, particularly for different types of Knowledge Sources (KS) like APIs, the platform aims to enhance the accuracy and relevance of the responses provided by the Language Model (LLM). The expected outcome is a more intelligent and responsive system that better understands and caters to user needs, resulting in higher user satisfaction and efficient resource use.

Intended Outcome

The successful implementation of this feature will result in several key outcomes:

1. Improved Response Accuracy: By routing queries to the most suitable agent templates, the platform will provide more relevant and accurate responses based on user context.
2. Enhanced User Experience: A seamless integration of the routing mechanism within the user interface will ensure a smooth and intuitive user experience.
3. Efficient Resource Utilization: Optimized system prompt selection will improve the efficiency of the platform's resources, leading to faster and more precise information retrieval.
4. Flexible and Scalable Design: The new system will be designed to easily accommodate future enhancements or additions to agent templates, ensuring long-term adaptability.
5. Continuous Improvement: A feedback mechanism will be implemented to gather user insights, allowing for ongoing refinement and improvement of the context-specific prompts.