mirror of
https://github.com/allaunthefox/Research-Stack.git
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5290413080
AVMIsa fixes (all pre-existing errors from the upstream merge):
- Types.lean: add Repr to AvmTy
- Value.lean: replace `deriving Inhabited` with explicit instance (AnyVal
is a dependent structure; auto-derive can't pick a default ty+val pair);
add Repr instance that delegates to AvmVal.repr
- Instr.lean: add Repr to Prim and Instr
- State.lean: fix `List.set ⟨i, h⟩` → `List.set i` (List.set takes Nat,
not Fin); drop now-dead `h` binding; add Repr to State
- Step.lean: rewrite evalPrim branches to pattern-match directly on AnyVal
`⟨ty, val⟩` pairs instead of `if v.ty = T` + separate val match (Lean
can't unify `AvmVal v.ty` with `AvmVal T` from a propositional if-guard);
replace `List.get? pc` (removed in Lean 4.30) with `list[pc]?` subscript;
rename Q0_16.addSat/subSat → Q0_16.add/sub (no sat variants exist);
add Repr to StepError and Outcome
PIST.Trace fixes:
- Drop invalid `set_option pp.pretty true`
- MVarId.toNat → MVarId.name.toString
- List.size → List.length (then .toArray for Json.arr)
- Json.num takes JsonNumber {mantissa : Int, exponent : Int}; cast Nat → Int
- goals.mapM goalToJson: lift MetaM → TacticM via liftMetaM
Canary result: `#eval run 8 canaryNot canaryState` →
Outcome.ok { pc := 2, stack := [AvmVal.b true], halted := true }
Generated with [Devin](https://cli.devin.ai/docs)
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
68 lines
1.9 KiB
Text
68 lines
1.9 KiB
Text
import Lean
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open Lean Elab Tactic Meta
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/-!
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# PIST Trace — goal-state snapshotter for Tier 2 flexure recording.
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Provides a tactic `trace_state_json "tag"` that emits structured goal-state
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snapshots to `logInfo` with a `@@PIST_TRACE_JSON@@` sentinel that the Python
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trace bridge can parse from stdout.
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Usage:
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```lean
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import PIST.Trace
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theorem t (n : Nat) : n + 0 = n := by
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trace_state_json "step_0_before"
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simp
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trace_state_json "step_0_after"
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```
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-/
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namespace PIST.Trace
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private def natToJson (n : Nat) : Json :=
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Json.num { mantissa := (n : Int), exponent := 0 }
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private def goalToJson (g : MVarId) : MetaM Json := do
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let decl ← g.getDecl
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let target ← instantiateMVars decl.type
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let targetFmt ← ppExpr target
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let mut hyps : Array Json := #[]
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for localDecl in decl.lctx do
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if !localDecl.isImplementationDetail then
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let ty ← instantiateMVars localDecl.type
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let tyFmt ← ppExpr ty
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hyps := hyps.push <| Json.mkObj [
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("name", Json.str localDecl.userName.toString),
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("type", Json.str tyFmt.pretty)
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]
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return Json.mkObj [
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("target", Json.str targetFmt.pretty),
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("goal_id", Json.str g.name.toString),
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("hypotheses", Json.arr hyps),
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("hypothesis_count", natToJson hyps.size)
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]
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/-- Emit a structured goal-state snapshot tagged with `tag`.
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The output is prefixed with `@@PIST_TRACE_JSON@@` so the Python bridge
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can scrape it from Lean's stdout.
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-/
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elab "trace_state_json" tag:str : tactic => do
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let goals ← getGoals
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let goalJsons ← goals.mapM (fun g => liftMetaM (goalToJson g))
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let payload : Json := Json.mkObj [
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("event", Json.str "pist_trace_state"),
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("tag", Json.str tag.getString),
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("goal_count", natToJson goals.length),
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("goals", Json.arr goalJsons.toArray)
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]
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logInfo m!"@@PIST_TRACE_JSON@@{payload.compress}"
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end PIST.Trace
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