Support Local Small Language Models for Reasoning and Decision Optimization
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Quiet
- Tech stack
- python
- Domain
- ai, machine-learning
Research direction
No files, tests, or entry points are named. Start by surveying the repository's Python model and agent interfaces, then identify where local inference, offline execution, and model selection belong; done means a local model interface exists, a Phi integration sample is available, and offline mode is validated.
Written by the indexing model from the issue text.
Description
Summary
Allow Agent Learning to leverage local SLMs for reasoning, scoring, decision support, and action selection.
Candidate Models
Microsoft Phi family
Future MAI models
Open-weight local reasoning models
Proposed Work
Local inference abstraction
Offline execution mode
Quantization guidance
Pluggable model architecture
Acceptance Criteria
Local model interface implemented
Phi integration sample available
Offline mode validated
- Dominant language
- Python
- Stars
- 10
- Forks
- 9
- Avg merge
- 1d 19h
- Merged PRs (30d)
- 4
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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