Understanding Intermediate 200 in Routing
Intermediate 200 is a term used in routing evaluation that refers to the number of outcomes needed to meet specific accuracy criteria. It is part of a process to assess the effectiveness of a new target or expert in a routing system.
This guide explains the concept of intermediate 200, how it is measured, and its role in optimizing routing accuracy and effort savings.
What Is Intermediate 200?
Intermediate 200 relates to the evaluation process where a target with minimal configuration—only an id, kind, and cost—is added to a routing system. The goal is for this target to reach at least 90% of its hand-configured routing accuracy after 200 outcomes.
The evaluation measures how quickly and effectively the system learns to route requests to this new target, with the specific number 200 indicating the number of outcomes used in the assessment.
How Is Intermediate 200 Used in Routing Evaluation?
In routing evaluation, intermediate 200 serves as an exit criterion for testing new targets. When a target reaches the accuracy threshold after 200 outcomes, it indicates that the system can reliably incorporate new targets with minimal initial data.
The process involves cold-start exploration, where the router streams mixed traffic through itself with an explore rate (e.g., 0.1), and measures the accuracy after 200 requests. This helps determine if the target can be integrated into the routing system efficiently.
Measuring and Reproducing Intermediate 200
To reproduce the evaluation, one can run specific scripts such as python scripts/exit_criteria.py which simulate the process of adding a target and measuring outcomes. The cold_start_ratio() function is used to calculate the accuracy on prompts within a domain, based on 200 outcomes.
This process ensures that new targets meet the required accuracy threshold with minimal effort, supporting system scalability and reliability.
Practical Applications of Intermediate 200
Intermediate 200 is useful for engineers aiming to expand their routing system with new experts or targets. It provides a quantitative measure to decide whether a target is ready for production deployment.
By focusing on outcomes and accuracy after 200 interactions, engineers can optimize the integration process, reduce manual configuration, and improve overall routing efficiency.
