🧪TDD Challenge·intermediate·⏱️ 30–45m·⭐ 150 XP
M-031Compare Embedding Models for Domain-Specific RAG
Description
MedTech AI's RAG system uses a general-purpose embedding model (MiniLM) but struggles with medical terminology. 'myocardial infarction' and 'heart attack' aren't recognized as similar. Test different embedding models and measure which performs best on medical queries.
Test Cases (3)
Compares multiple models
Should test and score multiple embedding models
Input:JSON.stringify(recommendModel({MiniLM:{precision:0.5,recall:0.6,dimensions:384},BioBERT:{precision:0.85,recall:0.9,dimensions:768},OpenAI:{precision:0.7,recall:0.75,dimensions:1536}}))
Expected:CONTAINS:f1Score
Identifies best model
Should identify which model performs best on domain queries
Input:recommendModel({MiniLM:{precision:0.5,recall:0.6,dimensions:384},BioBERT:{precision:0.85,recall:0.9,dimensions:768}}).recommended
Expected:CONTAINS:BioBERT
Measures similarity correctly
Should compute meaningful F1 scores
Input:recommendModel({A:{precision:0.7,recall:0.8,dimensions:384}}).f1Score > 0
Expected:CONTAINS:true
Related Lessons
Click Run / Check to validate your solution