Abstract model-selection policy into a ModelDecisionEngine#9
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rililive merged 2 commits intoJun 9, 2026
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Pull the scattered routing logic (classifyTurn, escalate-tool handoff,
stuck-detection) out of AgentLoop into a cohesive, injectable
ModelDecisionEngine interface. AgentLoop now keeps only mechanism and
delegates all "which model" decisions to the engine.
- Add src/agent/decision/{types,localFirst,index}.ts: the engine
interface plus LocalFirstModelEngine, the default policy. It reproduces
prior behavior and adds compute awareness (routes a local model that
won't fit RAM to the frontier) and cost awareness (costNote reporting).
- AgentLoop takes an optional `engine` instead of `escalationProvider` +
`router`; routing: 'off' injects no engine (single-provider path
unchanged).
- Wire the engine in repl.ts; export the new types from the public API.
- Adapt loop tests and add unit tests for the engine.
https://claude.ai/code/session_01T4UTQD35m11g4ChB8Cjd1w
rililive
merged commit 07992ba
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claude/local-model-cost-optimization-nzo2q6
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Pull the scattered routing logic (classifyTurn, escalate-tool handoff, stuck-detection) out of AgentLoop into a cohesive, injectable ModelDecisionEngine interface. AgentLoop now keeps only mechanism and delegates all "which model" decisions to the engine.
engineinstead ofescalationProvider+router; routing: 'off' injects no engine (single-provider path unchanged).https://claude.ai/code/session_01T4UTQD35m11g4ChB8Cjd1w