feat(model,capacity,vision,io): per-persona 路由 + 本地三级(默认关) + L3 分类 + OCR 独立模型 + image-crop 工具（裁决 03.4.1/03.4.3/14.4.1/14.4.4/14.4.5）
- 03.4.1：per-persona 路由载体选 models.json（组内新增 personaModels/personaProviders + 校验 + PersonaRoute()）， Router/RuntimeLLM 快照绑定、loop 流式路径按该 turn 的 persona 路由；主步用路由结果、降级步钉自己的模型 - 03.4.3：本地第三级降级链（LLM_LOCAL_*，Configured() 含 Enabled ⇒ **默认关**），warn 标注来源 - 14.4.4：capacity 接入 L3（分类器接口 + TTL 缓存 + 严格 JSON 解析），CAPACITY_L3_ENABLED **默认 false** - 14.4.1：语义修正 —— group.multimodal 才是「主模型能否收图」（env 路径不再臆断），LLM_VISION_MODEL 只配视觉工具； vision/OCR 可各用不同模型；runtime 不再因有图抢路由（vision.Router 是唯一分层权威） - 14.4.5：新增 image-crop 工具（工具数 5→6，策略默认 owner-only），schema 支持按区域裁切 - 组合根：wire_runtime 读 group.Multimodal；capacity 装配拆出 wire_capacity.go（守 500 行） - 复核：`go build`/`go vet`/各包 `go test -count=1` 全绿；**6 条变异反证**先红后还原（含作者自查出的 2 条假阳性变异） - 未落：按 provider 的 thinking 开关（需 openai_encode.go/openai.go 文件面）、persona awakening（需 loader 文件面）
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@@ -0,0 +1,203 @@
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package capacity
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import (
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"context"
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"errors"
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"sync"
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"testing"
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"time"
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)
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// stubClassifier is a deterministic IntentClassifier: it records every text it
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// was asked about so a test can pin whether L3 ran at all (裁决 14.4.4 的
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// CAPACITY_L3_ENABLED 默认关).
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type stubClassifier struct {
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mu sync.Mutex
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seen []string
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verdict Judgment
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err error
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calls int
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}
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func (s *stubClassifier) Classify(_ context.Context, text string) (Judgment, error) {
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s.mu.Lock()
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defer s.mu.Unlock()
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s.calls++
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s.seen = append(s.seen, text)
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if s.err != nil {
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return Judgment{}, s.err
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}
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return s.verdict, nil
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}
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func (s *stubClassifier) callCount() int {
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s.mu.Lock()
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defer s.mu.Unlock()
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return s.calls
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}
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func l3Config(c IntentClassifier, ttl time.Duration) Config {
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cfg := activeConfig()
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cfg.L3Enabled = true
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cfg.L3Classifier = c
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cfg.L3CacheTTL = ttl
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return cfg
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}
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// TestDecide_L3Disabled_ClassifierNeverRuns pins the default-off red line: with
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// CAPACITY_L3_ENABLED false the classifier must never be consulted, even when one
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// is configured, so L1/L2/L4 behavior is unchanged.
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func TestDecide_L3Disabled_ClassifierNeverRuns(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, Confidence: 0.9}}
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cfg := activeConfig()
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cfg.L3Classifier = stub // configured but not enabled
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cfg.L3CacheTTL = time.Minute
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// A turn no heuristic can decide: L1 needs a task verb + object, L2 needs a
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// leaning window. "那件事后来如何" carries no signal at all.
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dec := New(cfg).Decide(context.Background(), in("那件事后来如何"))
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if stub.callCount() != 0 {
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t.Fatalf("classifier calls = %d, want 0 while L3 is disabled", stub.callCount())
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}
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if dec.State != StateQuiet {
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t.Fatalf("state = %s, want quiet (conservative default)", dec.State)
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}
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}
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// TestDecide_L3AwakensUndecidedTurn pins that an enabled L3 layer turns an
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// otherwise undecided turn into a wake with the classifier's own confidence, and
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// advertises the awake tool set.
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func TestDecide_L3AwakensUndecidedTurn(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, TaskKind: "query", Confidence: 0.82}}
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dec := New(l3Config(stub, time.Minute)).Decide(context.Background(), in("那件事后来如何"))
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if stub.callCount() != 1 {
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t.Fatalf("classifier calls = %d, want 1", stub.callCount())
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}
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if dec.State != StateAwake {
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t.Fatalf("state = %s, want awake (L3 verdict)", dec.State)
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}
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if dec.Confidence != 0.82 {
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t.Fatalf("confidence = %v, want the classifier's 0.82", dec.Confidence)
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}
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if dec.Judgment.IsTask != true {
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t.Errorf("judgment = %+v, want the classifier's isTask=true written back for L4", dec.Judgment)
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}
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if !contains(dec.AllowedTools, "web-search") {
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t.Errorf("allowed = %v, want the awake set including web-search", dec.AllowedTools)
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}
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}
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// TestDecide_L3ComplexKindWakesFull pins the quantified gate's upper branch: a
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// "complex" task kind maps to the full state rather than awake.
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func TestDecide_L3ComplexKindWakesFull(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, TaskKind: taskKindComplex, Confidence: 0.9}}
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dec := New(l3Config(stub, time.Minute)).Decide(context.Background(), in("那件事后来如何"))
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if dec.State != StateFull {
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t.Fatalf("state = %s, want full for a complex task kind", dec.State)
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}
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}
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// TestDecide_L3LowConfidenceIsUndecided pins the conservative gate: a verdict the
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// model is unsure about must not wake anything, and must not be written back as a
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// task either (the L4 write-back feeds the learning loop, so a hesitant verdict
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// recorded as a task would teach the wrong habit).
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func TestDecide_L3LowConfidenceIsUndecided(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, Confidence: 0.3}}
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dec := New(l3Config(stub, time.Minute)).Decide(context.Background(), in("那件事后来如何"))
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if stub.callCount() != 1 {
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t.Fatalf("classifier calls = %d, want 1", stub.callCount())
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}
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if dec.State != StateQuiet {
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t.Fatalf("state = %s, want quiet (below-threshold verdict is undecided)", dec.State)
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}
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if dec.Judgment.IsTask {
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t.Fatalf("judgment = %+v, want isTask=false (a below-threshold verdict is not a task)", dec.Judgment)
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}
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}
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// TestDecide_L3ClassifierErrorKeepsConservativeDefault pins that a model failure
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// is reported as "no verdict" rather than crashing or waking tools.
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func TestDecide_L3ClassifierErrorKeepsConservativeDefault(t *testing.T) {
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stub := &stubClassifier{err: errors.New("upstream down")}
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dec := New(l3Config(stub, time.Minute)).Decide(context.Background(), in("那件事后来如何"))
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if dec.State != StateQuiet {
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t.Fatalf("state = %s, want quiet after a classifier error", dec.State)
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}
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}
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// TestDecide_L3CacheReusesVerdict pins the L3 output cache (裁决 14.4.4): the same
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// turn text costs one model call inside the TTL, and a different turn still costs
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// its own call.
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func TestDecide_L3CacheReusesVerdict(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, Confidence: 0.9}}
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d := New(l3Config(stub, time.Minute))
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ctx := context.Background()
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for i := 0; i < 3; i++ {
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if dec := d.Decide(ctx, in("那件事后来如何")); dec.State != StateAwake {
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t.Fatalf("call %d state = %s, want awake", i, dec.State)
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}
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}
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if got := stub.callCount(); got != 1 {
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t.Fatalf("classifier calls = %d, want 1 (cached verdict reused)", got)
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}
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d.Decide(ctx, in("那件事后来如何？"))
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if got := stub.callCount(); got != 2 {
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t.Fatalf("classifier calls = %d, want 2 (different text is not cached)", got)
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}
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}
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// TestL3Cache_ExpiredEntryIsReclassified pins the TTL bound itself.
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func TestL3Cache_ExpiredEntryIsReclassified(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, Confidence: 0.9}}
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c := newL3Cache(stub, time.Minute)
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ctx := context.Background()
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if _, err := c.classify(ctx, "那件事后来如何"); err != nil {
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t.Fatalf("classify: %v", err)
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}
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// Backdate the stored entry past the TTL.
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c.mu.Lock()
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for k, e := range c.entries {
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e.at = time.Now().Add(-2 * time.Minute)
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c.entries[k] = e
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}
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c.mu.Unlock()
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if _, err := c.classify(ctx, "那件事后来如何"); err != nil {
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t.Fatalf("classify: %v", err)
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}
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if got := stub.callCount(); got != 2 {
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t.Fatalf("classifier calls = %d, want 2 (expired entry reclassified)", got)
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}
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}
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// TestL3Cache_EmptyTextIsNotClassified pins that an empty turn is a sentinel
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// error rather than a model call.
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func TestL3Cache_EmptyTextIsNotClassified(t *testing.T) {
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stub := &stubClassifier{verdict: Judgment{IsTask: true, Confidence: 0.9}}
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c := newL3Cache(stub, time.Minute)
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if _, err := c.classify(context.Background(), " "); !errors.Is(err, ErrEmptyTurn) {
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t.Fatalf("err = %v, want ErrEmptyTurn", err)
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}
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if stub.callCount() != 0 {
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t.Fatalf("classifier calls = %d, want 0", stub.callCount())
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}
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}
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// TestParseL3Judgment pins the wire parsing: a fenced JSON reply is accepted, a
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// prose reply is an error, and a hallucinated confidence is clamped.
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func TestParseL3Judgment(t *testing.T) {
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ok, err := parseL3Judgment("```json\n{\"isTask\":true,\"taskKind\":\"query\",\"confidence\":0.7}\n```")
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if err != nil {
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t.Fatalf("parseL3Judgment: %v", err)
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}
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if !ok.IsTask || ok.TaskKind != "query" || ok.Confidence != 0.7 {
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t.Fatalf("parsed = %+v, want isTask=true taskKind=query confidence=0.7", ok)
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}
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if _, err := parseL3Judgment("我觉得这是一个任务"); err == nil {
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t.Fatal("prose reply parsed without error, want failure")
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}
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if got := clampUnit(7.5); got != 1 {
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t.Errorf("clampUnit(7.5) = %v, want 1", got)
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}
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}
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