feat(ai-sdk): runnable iace-audit propose CLI + live LLM wiring (P2 slice 3)

Makes the offline proposer runnable end-to-end.

- BuildProposerInput (proposer_input.go): non-test engine->hazards path. The
  PatternMatch->Hazard converter is lifted out of the GT test files into
  production scope so both the tests and the CLI share one pipeline.
- iace-audit propose <narrative.json> [<ground-truth.json>]: detect candidates ->
  GT-screen survivors (when a ground truth is given) -> judge (HeuristicJudge by
  default, LLMJudge over ollama when IACE_PROPOSE_LLM=1) -> write the human-review
  queue to audit-reports/proposals.{md,json}. Propose-only.

Smoke run on a dishwasher narrative: 32 fired -> 3 candidates -> queue with a
confident duplicate, a confident distinct, and one punted to the LLM judge; GT
wall recall-safe. Live qwen is opt-in via env; the heuristic default keeps the
tool runnable (and CI deterministic) without a model. Proposal types 2-4
(foreign-framing gates, vocab->tag, coverage blind spots) remain for slice 4.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

ai-compliance-sdk/cmd/iace-audit/main.go

@@ -34,6 +34,8 @@ func main() {
 		cmdEcho(os.Args[2:])
 	case "hierarchy":
 		cmdHierarchy(os.Args[2:])
+	case "propose":
+		cmdPropose(os.Args[2:])
 	default:
 		usage()
 		os.Exit(2)
@@ -41,7 +43,7 @@ func main() {
 }
 
 func usage() {
-	fmt.Fprintln(os.Stderr, "Usage: iace-audit <reachability|consistency|vocabulary|echo|hierarchy> [args]")
+	fmt.Fprintln(os.Stderr, "Usage: iace-audit <reachability|consistency|vocabulary|echo|hierarchy|propose> [args]")
 }
 
 func cmdReachability(_ []string) {

ai-compliance-sdk/cmd/iace-audit/propose.go

@@ -0,0 +1,141 @@
+package main
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"os"
+	"strconv"
+
+	"github.com/breakpilot/ai-compliance-sdk/internal/iace"
+	"github.com/breakpilot/ai-compliance-sdk/internal/llm"
+)
+
+type narrativeInput struct {
+	MachineType  string   `json:"machine_type"`
+	Narrative    string   `json:"narrative"`
+	MachineTypes []string `json:"machine_types,omitempty"`
+}
+
+// cmdPropose — Method P: offline dedup-candidate proposer.
+//
+//	iace-audit propose <narrative.json> [<ground-truth.json>]
+//
+// Detect near-duplicate patterns, screen survivors against a ground truth (if
+// given), judge them (heuristic by default, LLM when enabled), and write the
+// human-review queue to audit-reports/proposals.{md,json}. Propose-only — it
+// writes a report and never mutates the pattern library.
+//
+// Env:
+//
+//	IACE_PROPOSE_THRESHOLD  candidate score threshold (default 0.30)
+//	IACE_PROPOSE_LLM=1      use the offline LLM judge instead of the heuristic
+//	OLLAMA_URL              ollama base URL (default http://localhost:11434)
+//	SELF_HOSTED_LLM_MODEL   model name (default qwen2.5:32b-instruct)
+func cmdPropose(args []string) {
+	if len(args) < 1 {
+		fmt.Fprintln(os.Stderr, "propose: usage: iace-audit propose <narrative.json> [<ground-truth.json>]")
+		os.Exit(2)
+	}
+
+	var in narrativeInput
+	must(readJSONFile(args[0], &in))
+	if in.Narrative == "" {
+		fmt.Fprintln(os.Stderr, "propose: narrative is empty")
+		os.Exit(2)
+	}
+
+	var gt *iace.GroundTruth
+	if len(args) >= 2 {
+		var g iace.GroundTruth
+		must(readJSONFile(args[1], &g))
+		gt = &g
+	}
+
+	threshold := envFloat("IACE_PROPOSE_THRESHOLD", 0.30)
+	hazards, mits, fired := iace.BuildProposerInput(in.Narrative, in.MachineType, in.MachineTypes)
+	candidates := iace.FindDedupCandidates(fired, threshold)
+
+	byID := make(map[string]iace.PatternMatch, len(fired))
+	for _, pm := range fired {
+		byID[pm.PatternID] = pm
+	}
+
+	judge := selectJudge(in.MachineType)
+	ctx := context.Background()
+
+	var proposals []iace.JudgedProposal
+	blocked := 0
+	for _, c := range candidates {
+		var sr iace.ScreenResult
+		if gt != nil {
+			sr = iace.ScreenSupersession(gt, hazards, mits, c.KeepHazardName, c.DropName)
+			if sr.RecallAfter < sr.RecallBefore || sr.DistinctGT {
+				blocked++
+				continue
+			}
+		}
+		v, conf, rat := judge.Judge(ctx, c, byID[c.KeepPattern], byID[c.DropPattern])
+		proposals = append(proposals, iace.JudgedProposal{
+			Candidate: c, Screen: sr, Verdict: v, Confidence: conf, Rationale: rat, Judge: judge.Name(),
+		})
+	}
+
+	writeText("audit-reports/proposals.md", iace.RenderProposalQueue(in.MachineType, proposals))
+	writeJSON("audit-reports/proposals.json", proposals)
+
+	printSummary("Method P — Dedup Proposer ("+judge.Name()+")", map[string]int{
+		"fired_patterns": len(fired),
+		"candidates":     len(candidates),
+		"in_queue":       len(proposals),
+		"gt_blocked":     blocked,
+	})
+	if gt == nil {
+		fmt.Fprintln(os.Stderr, "note: no ground truth provided — GT wall NOT applied (candidates not recall-screened)")
+	}
+}
+
+func selectJudge(machineClass string) iace.CandidateJudge {
+	if os.Getenv("IACE_PROPOSE_LLM") != "1" {
+		return iace.HeuristicJudge{}
+	}
+	base := envStr("OLLAMA_URL", "http://localhost:11434")
+	model := envStr("SELF_HOSTED_LLM_MODEL", "qwen2.5:32b-instruct")
+	reg := llm.NewProviderRegistry("ollama", "")
+	reg.Register(llm.NewOllamaAdapter(base, model))
+	fmt.Printf("using LLM judge (ollama %s, model %s)\n", base, model)
+	return iace.LLMJudge{Completer: iace.NewRegistryCompleter(reg, model), MachineClass: machineClass}
+}
+
+func readJSONFile(path string, v any) error {
+	raw, err := os.ReadFile(path)
+	if err != nil {
+		return err
+	}
+	return json.Unmarshal(raw, v)
+}
+
+func writeText(path, content string) {
+	_ = os.MkdirAll("audit-reports", 0o755)
+	if err := os.WriteFile(path, []byte(content), 0o644); err != nil {
+		fmt.Fprintln(os.Stderr, "warn: could not write", path, err)
+		return
+	}
+	fmt.Println("→ wrote", path)
+}
+
+func envStr(key, def string) string {
+	if v := os.Getenv(key); v != "" {
+		return v
+	}
+	return def
+}
+
+func envFloat(key string, def float64) float64 {
+	if v := os.Getenv(key); v != "" {
+		if f, err := strconv.ParseFloat(v, 64); err == nil {
+			return f
+		}
+	}
+	return def
+}

ai-compliance-sdk/internal/iace/gt_kistenhub_test.go

@@ -7,8 +7,6 @@ import (
 	"path/filepath"
 	"sort"
 	"testing"
-
-	"github.com/google/uuid"
 )
 
 // TestKistenhub_GTCoverage runs the Kistenhubgeraet ground truth (37 entries)
@@ -110,65 +108,6 @@ func TestKistenhub_GTCoverage(t *testing.T) {
 // patternsToHazardsAndMitigations converts a pattern match output into the
 // Hazard/Mitigation shapes that CompareBenchmark expects. Mirrors what
 // iace_handler_init.go does in production but without DB writes.
-func patternsToHazardsAndMitigations(out *MatchOutput) ([]Hazard, []Mitigation) {
-	hazards := make([]Hazard, 0, len(out.MatchedPatterns))
-	patternToHazard := make(map[string]uuid.UUID, len(out.MatchedPatterns))
-
-	for _, pm := range out.MatchedPatterns {
-		cat := ""
-		if len(pm.HazardCats) > 0 {
-			cat = pm.HazardCats[0]
-		}
-		zone := pm.ZoneDE
-		lifecycle := ""
-		if len(pm.ApplicableLifecycles) > 0 {
-			lifecycle = pm.ApplicableLifecycles[0]
-		}
-		h := Hazard{
-			ID:             uuid.New(),
-			Name:           pm.ScenarioDE,
-			Category:       cat,
-			Description:    pm.ScenarioDE,
-			Scenario:       pm.ScenarioDE,
-			TriggerEvent:   pm.TriggerDE,
-			PossibleHarm:   pm.HarmDE,
-			AffectedPerson: pm.AffectedDE,
-			HazardousZone:  zone,
-			LifecyclePhase: lifecycle,
-		}
-		if h.Name == "" {
-			h.Name = pm.PatternName
-		}
-		hazards = append(hazards, h)
-		patternToHazard[pm.PatternID] = h.ID
-	}
-
-	measureNames := make(map[string]string)
-	for _, m := range GetProtectiveMeasureLibrary() {
-		measureNames[m.ID] = m.Name
-	}
-
-	var mitigations []Mitigation
-	for _, sm := range out.SuggestedMeasures {
-		name := measureNames[sm.MeasureID]
-		if name == "" {
-			name = sm.MeasureID
-		}
-		for _, srcPattern := range sm.SourcePatterns {
-			hid, ok := patternToHazard[srcPattern]
-			if !ok {
-				continue
-			}
-			mitigations = append(mitigations, Mitigation{
-				ID:       uuid.New(),
-				HazardID: hid,
-				Name:     name,
-			})
-		}
-	}
-	return hazards, mitigations
-}
-
 func abbrev(s string, max int) string {
 	if len(s) <= max {
 		return s

ai-compliance-sdk/internal/iace/proposer_input.go

@@ -0,0 +1,123 @@
+package iace
+
+import "github.com/google/uuid"
+
+// Non-test plumbing for the offline proposer (P2 slice 3): run the engine for a
+// narrative and produce the fired patterns + the engine-built hazards/mitigations
+// the dedup proposer and GT screen consume. This is the same pipeline the GT
+// benchmark tests use, lifted out of test scope so the dev-time CLI can call it.
+
+// universalLifecyclePhases are appended so patterns gated to a specific lifecycle
+// (maintenance/cleaning/setup/fault clearing) still fire — the proposer wants the
+// full hazard picture, not only normal-operation hazards.
+var universalLifecyclePhases = []string{"normal_operation", "maintenance", "cleaning", "setup", "fault_clearing"}
+
+// BuildProposerInput parses a narrative, runs the pattern engine, keeps the
+// narrative-relevant patterns, and returns the hazards, mitigations and fired
+// patterns. NOTE: it does not apply the CE cyber-category skip, so the proposer
+// view may include cyber/AI hazards that the CE log excludes — harmless for the
+// GT recall screen (they match no CE ground-truth entry).
+func BuildProposerInput(narrative, machineType string, extraMachineTypes []string) ([]Hazard, []Mitigation, []PatternMatch) {
+	res := ParseNarrative(narrative, machineType)
+
+	var compIDs, compNames, energyIDs []string
+	for _, c := range res.Components {
+		if c.Negated {
+			continue
+		}
+		compIDs = append(compIDs, c.LibraryID)
+		compNames = append(compNames, c.NameDE)
+	}
+	for _, e := range res.EnergySources {
+		energyIDs = append(energyIDs, e.SourceID)
+	}
+
+	machineTypes := append([]string{}, extraMachineTypes...)
+	if machineType != "" {
+		machineTypes = append(machineTypes, machineType)
+	}
+	lifecycles := append(append([]string{}, res.LifecyclePhases...), universalLifecyclePhases...)
+
+	out := NewPatternEngine().Match(MatchInput{
+		ComponentLibraryIDs: compIDs,
+		EnergySourceIDs:     energyIDs,
+		LifecyclePhases:     lifecycles,
+		CustomTags:          res.CustomTags,
+		OperationalStates:   res.OperationalStates,
+		StateTransitions:    res.StateTransitions,
+		HumanRoles:          res.Roles,
+		MachineTypes:        machineTypes,
+	})
+
+	kept := make([]PatternMatch, 0, len(out.MatchedPatterns))
+	for _, pm := range out.MatchedPatterns {
+		if IsPatternRelevant(pm, narrative, compNames) {
+			kept = append(kept, pm)
+		}
+	}
+	filtered := *out
+	filtered.MatchedPatterns = kept
+	hazards, mits := patternsToHazardsAndMitigations(&filtered)
+	return hazards, mits, kept
+}
+
+// patternsToHazardsAndMitigations converts engine output into the hazard/mitigation
+// entities the benchmark + proposer compare on. Simplified vs InitializeProject
+// (no risk estimation, no norm refs) — it only needs category/zone/scenario/measures.
+func patternsToHazardsAndMitigations(out *MatchOutput) ([]Hazard, []Mitigation) {
+	hazards := make([]Hazard, 0, len(out.MatchedPatterns))
+	patternToHazard := make(map[string]uuid.UUID, len(out.MatchedPatterns))
+
+	for _, pm := range out.MatchedPatterns {
+		cat := ""
+		if len(pm.HazardCats) > 0 {
+			cat = pm.HazardCats[0]
+		}
+		lifecycle := ""
+		if len(pm.ApplicableLifecycles) > 0 {
+			lifecycle = pm.ApplicableLifecycles[0]
+		}
+		h := Hazard{
+			ID:             uuid.New(),
+			Name:           pm.ScenarioDE,
+			Category:       cat,
+			Description:    pm.ScenarioDE,
+			Scenario:       pm.ScenarioDE,
+			TriggerEvent:   pm.TriggerDE,
+			PossibleHarm:   pm.HarmDE,
+			AffectedPerson: pm.AffectedDE,
+			HazardousZone:  pm.ZoneDE,
+			LifecyclePhase: lifecycle,
+		}
+		if h.Name == "" {
+			h.Name = pm.PatternName
+		}
+		hazards = append(hazards, h)
+		patternToHazard[pm.PatternID] = h.ID
+	}
+
+	measureNames := make(map[string]string)
+	for _, m := range GetProtectiveMeasureLibrary() {
+		measureNames[m.ID] = m.Name
+	}
+
+	var mitigations []Mitigation
+	for _, sm := range out.SuggestedMeasures {
+		name := measureNames[sm.MeasureID]
+		if name == "" {
+			name = sm.MeasureID
+		}
+		for _, srcPattern := range sm.SourcePatterns {
+			hid, ok := patternToHazard[srcPattern]
+			if !ok {
+				continue
+			}
+			mitigations = append(mitigations, Mitigation{
+				ID:       uuid.New(),
+				HazardID: hid,
+				Name:     name,
+			})
+		}
+	}
+	return hazards, mitigations
+}

ai-compliance-sdk/internal/iace/proposer_input_test.go

@@ -0,0 +1,25 @@
+package iace
+
+import "testing"
+
+func TestBuildProposerInput_WarewashingFires(t *testing.T) {
+	hazards, _, fired := BuildProposerInput(
+		warewashingNarrative,
+		"Gewerbliche Untertisch-Geschirrspuelmaschine (vernetzt)",
+		[]string{"food_processing"},
+	)
+	if len(fired) == 0 || len(hazards) == 0 {
+		t.Fatalf("want fired patterns + hazards, got %d patterns / %d hazards", len(fired), len(hazards))
+	}
+	has := func(id string) bool {
+		for _, pm := range fired {
+			if pm.PatternID == id {
+				return true
+			}
+		}
+		return false
+	}
+	if !has("HP2201") {
+		t.Errorf("warewashing-specific HP2201 must fire via BuildProposerInput")
+	}
+}