jevrag
ajanm007
Replaces hardcoded RAG thresholds with explicit calibrated decision points. Five primitives (retrieval stopping, chunk splitting, context selection, answer abstention, cache trust) behind one swappable state → Decision → confidence → action interface, each evaluated on real datasets with a calibration harness that reports honestly.
- License
- MIT
- GitHub Stars
- 0
- Source reviewed
- —
Where Jev makes a decision
jevrag/decision.py — the `ask(state, questions) -> DecisionResult` method calls `api.typesafe.ai/v1/systemone` via the Jev backend. All five primitives in `jevrag/primitives/` route through this method.
What this project offers
Adds structured choices or scores to the workflow; performance and cost benefits have not been independently verified.
Review scope
Author and repository text is preserved where clear; missing languages are enriched automatically. Checks establish source-level Jev integration, not runtime, safety, or performance validation.
Sources and implementation
- ajanm007/jevrag/blob/2b5563a9a4a68c592e727fc390890798dd5be2fb/README.md
- ajanm007/jevrag/blob/2b5563a9a4a68c592e727fc390890798dd5be2fb/jevrag/adapters/rag_jev_selector.py
- ajanm007/jevrag/blob/2b5563a9a4a68c592e727fc390890798dd5be2fb/scripts/eval_rag_jev.py
- ajanm007/jevrag/blob/2b5563a9a4a68c592e727fc390890798dd5be2fb/scripts/eval_scifact_ragjev.py
- ajanm007/jevrag/blob/2b5563a9a4a68c592e727fc390890798dd5be2fb/jevrag/decision.py
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