Neural Mastery
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#190. Dense-Sparse Hybrid Rankereasy

#190. Dense-Sparse Hybrid Ranker

easyRAG Fundamentals⏱ 10–15 min
⚡ Libraries allowed · Pure Python earns +10 bonus XP
🎯 Mission
Implement #190. Dense-Sparse Hybrid Ranker to master core AI engineering concepts in RAG Fundamentals.

Task

Implement `dense_sparse_hybrid_ranker` in Python. Test cases verify edge cases and functional requirements.

Function Signature

dense_sparse_hybrid_ranker(*args, **kwargs)

Examples

Example 1: Basic Execution
Input: {}
Output: true
Explanation: Verifies core execution for #190. Dense-Sparse Hybrid Ranker.

Constraints

  • Libraries (NumPy, PyTorch, SciPy) are allowed and accepted normally.
  • Pure Python (no external libraries) earns +10 Bonus XP!
  • Must handle edge cases cleanly.
Python3Saved ✓
def dense_sparse_hybrid_ranker(*args, **kwargs):
"""
RAG Fundamentals - Problem #190: Dense-Sparse Hybrid Ranker
Implement solution for Dense-Sparse Hybrid Ranker in the Neural Mastery AI Engineering curriculum.
"""
# Implement core solution logic here
pass

Case 1: Basic Execution
Input: {}
Expected: true