jellydn / jellydn/flowly

Recommend model routing from evaluation results

Open
#155 0 comments 0 reactions 0 assignees View on GitHub
Dominant language
TypeScript
Stars
3
Forks
0
Avg merge
15h 21m
Merged PRs (30d)
31

Description

## Summary

Add explainable model-routing recommendations based on Flowly benchmark reports. This is an optional follow-up to #38.

## Scope

- Recommend models by workload type and configured quality, cost, and latency constraints
- Use compatible persisted reports and versioned suite lineage
- Explain the metrics and trade-offs behind each recommendation
- Fail closed when evidence is missing, stale, or not comparable

## Acceptance criteria

- [ ] Recommendations can target repository questions, issue work, PR reviews, and coding tasks
- [ ] Operators can set explicit quality, cost, and latency constraints
- [ ] Every recommendation cites the reports, suite lineage, and metrics used
- [ ] Incompatible or insufficient runs do not produce a confident recommendation
- [ ] Deterministic tests and documentation cover ranking and no-recommendation cases

## Non-goals

- Automatic provider credential changes
- Silent production routing changes
- Dashboard UI or hosted report sharing

Contributor guide

No contributing guide indexed for this repository

Research direction

Start by reviewing follow-up issue #38 and the existing persisted Flowly benchmark reports and versioned suite lineage. Define how workload, quality, cost, and latency constraints feed ranking, then verify deterministic tests and documentation cover explainable recommendations and no-recommendation cases.

Written by the indexing model from the issue text.

Assessment

Tech stack
typescript
Domain
ai
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
42/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.