Fix RRF algorithm to match AI Search algo

[pamelafox]

This algorithm matches what AI Search describes. I stepped through the results with the debugger and they seemed reasonable.

Pull Request Overview

This PR updates the reciprocal rank fusion implementation to align with the AI Search algorithm. The changes include:

• Replacing the previous weighted fusion (using alpha) with an RRF scoring approach using a k offset.
• Updating the hybrid_search function to use the new fusion mechanism.
• Modifying sample user query strings in both the Spanish and English versions.

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
spanish/rag_documents_hybrid.py	Updates the reciprocal_rank_fusion function and sample query string.
rag_documents_hybrid.py	Updates the reciprocal_rank_fusion function and sample query string.

Comments suppressed due to low confidence (2)

spanish/rag_documents_hybrid.py:85

• [nitpick] Consider using (i+1+k) instead of (i+k) to properly reflect 1-indexed ranks for RRF scoring, ensuring no off-by-one error.

scores[doc["id"]] += 1 / (i + k)

rag_documents_hybrid.py:85

• [nitpick] Consider using (i+1+k) instead of (i+k) so that the ranking starts at 1 as expected by standard RRF implementations, which may avoid off-by-one issues.

scores[doc["id"]] += 1 / (i + k)