Storia-AI/sage

Feature request: Implement reciprocal rank fusion for combining multiple retriever outputs

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#55 opened on Oct 4, 2024

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good first issuehacktoberfest🔥 difficulty: 1

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Description

Right now when we are combining the outputs of a bm25 encoder and a dense retriever we simply do a weighted average of their scores. It's more standard to use reciprocal rank fusion methods to combine multiple scores.

We should implement this alternative hybrid scoring method

Contributor guide

Research direction
Research the reciprocal rank fusion (RRF) algorithm, understand how it combines ranked lists from different retrievers, and implement it as an alternative hybrid scoring method alongside the existing weighted average. Reference the linked Microsoft documentation and test with sample data.
Tech stack
python
Domain
backend
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonInformation Retrieval basics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
65