feat(memory): M4 记忆完善（三类作用域访问规则+项目索引分层+LLM异步提取+衰减溯源+向量接入，兼容既有57用例）
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package memory
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import (
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"context"
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"errors"
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"testing"
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"time"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/model"
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)
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// mockAdapter is a scriptable model.Adapter for tests. With no fn it returns an
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// empty candidate array, so a test that only needs a successful call can use it
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// directly.
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type mockAdapter struct {
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fn func(ctx context.Context, req model.Request, opts model.Options) (model.Response, error)
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}
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func (m *mockAdapter) Name() string { return "mock" }
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func (m *mockAdapter) Chat(ctx context.Context, req model.Request, opts model.Options) (model.Response, error) {
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if m.fn != nil {
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return m.fn(ctx, req, opts)
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}
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return model.Response{Content: "[]"}, nil
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}
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func (m *mockAdapter) ChatStream(ctx context.Context, req model.Request, onChunk func(delta string)) (model.Response, error) {
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return model.Response{}, model.ErrStream
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}
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func TestLLMExtractor_Extract_Parse_正常(t *testing.T) {
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t.Parallel()
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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return model.Response{Content: `[
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{"content":"用户喜欢冰美式","scope":"user","kind":"relationship","tags":["咖啡"],"confidence":0.9,"source_conversation":"conv.1"},
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{"content":"项目Alpha周三开会","scope":"project","project_id":"project.alpha","source_conversation":"conv.1"}
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]`}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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items, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "你好"),
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})
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if err != nil {
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t.Fatalf("Extract: %v", err)
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}
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if len(items) != 2 {
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t.Fatalf("got %d items, want 2", len(items))
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}
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if items[0].Content != "用户喜欢冰美式" || items[0].Scope != ScopeUser || items[0].Confidence != 0.9 {
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t.Errorf("items[0] = %+v, want parsed user item", items[0])
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}
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if items[0].SourceConversation != "conv.1" {
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t.Errorf("items[0].SourceConversation = %q, want conv.1", items[0].SourceConversation)
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}
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if items[1].ProjectID != "project.alpha" || items[1].Scope != ScopeProject {
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t.Errorf("items[1] = %+v, want project-scoped item", items[1])
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}
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if items[0].PersonaID != "persona.a" || items[0].RoleID != "role.1" {
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t.Errorf("items[0] author = %q/%q, want persona.a/role.1", items[0].PersonaID, items[0].RoleID)
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}
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}
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func TestLLMExtractor_Extract_InvalidScopeKind_Fallback_正常(t *testing.T) {
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t.Parallel()
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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return model.Response{Content: `[{"content":"一个事实","scope":"bogus","kind":"bogus"}]`}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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items, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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})
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if err != nil {
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t.Fatalf("Extract: %v", err)
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}
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if len(items) != 1 {
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t.Fatalf("got %d items, want 1", len(items))
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}
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// Bogus scope/kind fall back to the extractor's configured defaults.
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if items[0].Scope != ScopePersona || items[0].Kind != KindRelationship {
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t.Errorf("fallback scope/kind = %q/%q, want persona/relationship", items[0].Scope, items[0].Kind)
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}
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}
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func TestLLMExtractor_Extract_Dedup_正常(t *testing.T) {
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t.Parallel()
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// The model emits the same memory three times, differing only in case and
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// surrounding whitespace; they must collapse into one item.
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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return model.Response{Content: `[
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{"content":"记得喝咖啡"},
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{"content":" 记得喝咖啡 "},
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{"content":"记得喝咖啡"}
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]`}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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items, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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})
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if err != nil {
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t.Fatalf("Extract: %v", err)
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}
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if len(items) != 1 {
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t.Fatalf("got %d items, want 1 after dedup", len(items))
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}
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}
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func TestLLMExtractor_Extract_Empty_正常(t *testing.T) {
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t.Parallel()
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ex := NewLLMExtractor(&mockAdapter{}, "persona.a", "role.1")
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items, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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})
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if err != nil {
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t.Fatalf("Extract: %v", err)
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}
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if len(items) != 0 {
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t.Fatalf("got %d items, want 0 for empty candidate response", len(items))
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}
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}
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func TestLLMExtractor_Extract_InvalidJSON_异常(t *testing.T) {
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t.Parallel()
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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return model.Response{Content: "{not-json}"}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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if _, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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}); err == nil {
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t.Fatal("Extract on malformed JSON: expected error, got nil")
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}
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}
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func TestLLMExtractor_Extract_NilAdapter_异常(t *testing.T) {
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t.Parallel()
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ex := NewLLMExtractor(nil, "persona.a", "role.1")
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if _, err := ex.Extract(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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}); !errors.Is(err, ErrNilAdapter) {
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t.Fatalf("Extract with nil adapter err = %v, want ErrNilAdapter", err)
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}
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}
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func TestLLMExtractor_Extract_Canceled_异常(t *testing.T) {
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t.Parallel()
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adapter := &mockAdapter{fn: func(ctx context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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<-ctx.Done()
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return model.Response{}, ctx.Err()
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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ctx, cancel := context.WithCancel(context.Background())
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cancel()
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if _, err := ex.Extract(ctx, []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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}); !errors.Is(err, context.Canceled) {
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t.Fatalf("Extract with canceled ctx err = %v, want context.Canceled", err)
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}
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}
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func TestLLMExtractor_ExtractAsync_异步_正常(t *testing.T) {
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t.Parallel()
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started := make(chan struct{})
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release := make(chan struct{})
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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close(started)
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<-release
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return model.Response{Content: `[{"content":"异步提取的记忆"}]`}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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ch, err := ex.ExtractAsync(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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})
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if err != nil {
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t.Fatalf("ExtractAsync: %v", err)
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}
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// ExtractAsync returned while the adapter is still blocked on release,
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// proving the extraction runs on a background goroutine.
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select {
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case <-started:
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case <-time.After(2 * time.Second):
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t.Fatal("extraction goroutine did not start in time")
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}
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close(release)
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res := <-ch
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if res.Err != nil {
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t.Fatalf("async result err = %v", res.Err)
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}
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if len(res.Items) != 1 || res.Items[0].Content != "异步提取的记忆" {
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t.Fatalf("async items = %+v, want one extracted item", res.Items)
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}
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}
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func TestLLMExtractor_ExtractAsync_Idempotent_正常(t *testing.T) {
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t.Parallel()
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adapter := &mockAdapter{fn: func(_ context.Context, _ model.Request, _ model.Options) (model.Response, error) {
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return model.Response{Content: `[{"content":"习惯：早起"}]`}, nil
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}}
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ex := NewLLMExtractor(adapter, "persona.a", "role.1")
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conv := []model.Message{model.TextMessage(model.RoleUser, "hi")}
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first, err := ex.ExtractAsync(context.Background(), conv)
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if err != nil {
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t.Fatalf("ExtractAsync first: %v", err)
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}
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if res := <-first; res.Err != nil || len(res.Items) != 1 {
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t.Fatalf("first async result = %+v, want 1 item", res)
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}
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// A second async extraction of the same memory deduplicates to zero.
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second, err := ex.ExtractAsync(context.Background(), conv)
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if err != nil {
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t.Fatalf("ExtractAsync second: %v", err)
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}
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if res := <-second; res.Err != nil || len(res.Items) != 0 {
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t.Fatalf("second async result = %+v, want 0 items (idempotent)", res)
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}
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}
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func TestLLMExtractor_ExtractAsync_NilAdapter_异常(t *testing.T) {
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t.Parallel()
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ex := NewLLMExtractor(nil, "persona.a", "role.1")
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if _, err := ex.ExtractAsync(context.Background(), []model.Message{
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model.TextMessage(model.RoleUser, "hi"),
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}); !errors.Is(err, ErrNilAdapter) {
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t.Fatalf("ExtractAsync with nil adapter err = %v, want ErrNilAdapter", err)
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}
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}
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