feat: filter meaningful conversations with local model

internal/extraction/generator.go

@@ -23,16 +23,19 @@ type GenerationInput struct {
 }
 
 type GenerationResult struct {
-	Summary       string   `json:"summary"`
-	OpenTopic     string   `json:"open_topic"`
-	StoryTitle    string   `json:"story_title"`
-	StoryContent  string   `json:"story_content"`
-	FactContent   string   `json:"fact_content"`
-	Keywords      []string `json:"keywords"`
-	Confidence    float64  `json:"confidence"`
-	ModelRef      string   `json:"-"`
-	PromptVersion string   `json:"-"`
-	AllowStory    bool     `json:"-"`
+	Meaningful     bool     `json:"meaningful"`
+	StoryWorthy    bool     `json:"story_worthy"`
+	DecisionReason string   `json:"decision_reason"`
+	Summary        string   `json:"summary"`
+	OpenTopic      string   `json:"open_topic"`
+	StoryTitle     string   `json:"story_title"`
+	StoryContent   string   `json:"story_content"`
+	FactContent    string   `json:"fact_content"`
+	Keywords       []string `json:"keywords"`
+	Confidence     float64  `json:"confidence"`
+	ModelRef       string   `json:"-"`
+	PromptVersion  string   `json:"-"`
+	AllowStory     bool     `json:"-"`
 }
 
 type Generator interface {
@@ -46,17 +49,33 @@ func (DeterministicGenerator) Generate(_ context.Context, input GenerationInput)
 	if content == "" {
 		return GenerationResult{}, errors.New("extraction content is required")
 	}
+	meaningful, storyWorthy, reason := deterministicContentDecision(content)
+	if !meaningful {
+		return GenerationResult{
+			Meaningful: false, StoryWorthy: false, DecisionReason: reason,
+			Confidence: 0.9, ModelRef: "local-deterministic-extractor", PromptVersion: "content-value-v1",
+		}, nil
+	}
+	storyTitle, storyContent, factContent := "", "", ""
+	if storyWorthy {
+		storyTitle = "关于“" + truncateRunes(content, 24) + "”的回忆"
+		storyContent = content
+		factContent = content
+	}
 	return GenerationResult{
-		Summary:       "长者在本次通话中谈到：" + content,
-		OpenTopic:     "下次可以继续询问长者刚才提到的经历，并让长者自行补充人物、时间和地点。",
-		StoryTitle:    "关于“" + truncateRunes(content, 24) + "”的回忆",
-		StoryContent:  content,
-		FactContent:   content,
-		Keywords:      deterministicKeywords(content),
-		Confidence:    0.9,
-		ModelRef:      "local-deterministic-extractor",
-		PromptVersion: "story-v1",
-		AllowStory:    true,
+		Meaningful:     true,
+		StoryWorthy:    storyWorthy,
+		DecisionReason: reason,
+		Summary:        "长者在本次通话中谈到：" + content,
+		OpenTopic:      "下次可以继续询问长者刚才提到的经历，并让长者自行补充人物、时间和地点。",
+		StoryTitle:     storyTitle,
+		StoryContent:   storyContent,
+		FactContent:    factContent,
+		Keywords:       deterministicKeywords(content),
+		Confidence:     0.9,
+		ModelRef:       "local-deterministic-extractor",
+		PromptVersion:  "content-value-deterministic-v2",
+		AllowStory:     storyWorthy,
 	}, nil
 }
 
@@ -67,12 +86,15 @@ func sensitiveGeneration(decision contentpolicy.Decision) GenerationResult {
 	}
 	reason := safePolicyToken(decision.Reason)
 	return GenerationResult{
-		Summary:       "本次通话包含需要人工谨慎处理的敏感信息，系统未生成普通故事卡片。",
-		OpenTopic:     "如确有必要处理本次敏感内容，应由有权限人员在受控流程中单独核对。",
-		Confidence:    1,
-		ModelRef:      modelRef,
-		PromptVersion: "summary-sensitive-filter-v1:" + reason,
-		AllowStory:    false,
+		Meaningful:     true,
+		StoryWorthy:    false,
+		DecisionReason: "safety_policy_blocked_story",
+		Summary:        "本次通话包含需要人工谨慎处理的敏感信息，系统未生成普通故事卡片。",
+		OpenTopic:      "如确有必要处理本次敏感内容，应由有权限人员在受控流程中单独核对。",
+		Confidence:     1,
+		ModelRef:       modelRef,
+		PromptVersion:  "summary-sensitive-filter-v1:" + reason,
+		AllowStory:     false,
 	}
 }
 
@@ -133,7 +155,7 @@ func (g *ArkGenerator) Generate(ctx context.Context, input GenerationInput) (Gen
 	requestBody := map[string]any{
 		"model": g.model,
 		"messages": []map[string]string{
-			{"role": "system", "content": "你是长者口述内容整理助手。只依据输入字幕生成可人工核对的候选，不补充未出现的事实，不把推断写成事实。必须返回JSON对象，字段为summary、keywords、open_topic、story_title、story_content、fact_content、confidence。summary概括本次内容，keywords是1至8个简短关键词字符串组成的数组，open_topic给出一个温和的后续话题，story和fact保留原意，confidence取0到1。"},
+			{"role": "system", "content": contentValuePrompt},
 			{"role": "user", "content": content},
 		},
 		"temperature":     g.temperature,
@@ -186,30 +208,75 @@ func (g *ArkGenerator) Generate(ctx context.Context, input GenerationInput) (Gen
 		return GenerationResult{}, outbox.Retryable(fmt.Errorf("decode Ark structured content: %w", err))
 	}
 	result.Summary = strings.TrimSpace(result.Summary)
+	result.DecisionReason = strings.TrimSpace(result.DecisionReason)
 	result.OpenTopic = strings.TrimSpace(result.OpenTopic)
 	result.StoryTitle = strings.TrimSpace(result.StoryTitle)
 	result.StoryContent = strings.TrimSpace(result.StoryContent)
 	result.FactContent = strings.TrimSpace(result.FactContent)
 	result.Keywords = normalizedKeywords(result.Keywords)
+	normalizeDecisionContent(&result)
 	if !validGeneratedContent(result) {
 		return GenerationResult{}, outbox.Retryable(errors.New("Ark structured content failed validation"))
 	}
 	result.ModelRef = g.provider + ":" + g.model
-	result.PromptVersion = "story-" + g.provider + "-json-v2"
-	result.AllowStory = true
+	result.PromptVersion = "content-value-" + g.provider + "-json-v3"
+	result.AllowStory = result.Meaningful && result.StoryWorthy
 	return result, nil
 }
 
+func normalizeDecisionContent(result *GenerationResult) {
+	if !result.Meaningful {
+		result.StoryWorthy = false
+		result.Summary = ""
+		result.OpenTopic = ""
+		result.StoryTitle = ""
+		result.StoryContent = ""
+		result.FactContent = ""
+		result.Keywords = nil
+		return
+	}
+	if !result.StoryWorthy {
+		result.StoryTitle = ""
+		result.StoryContent = ""
+		result.FactContent = ""
+	}
+}
+
 func validGeneratedContent(result GenerationResult) bool {
-	return result.Summary != "" && len([]rune(result.Summary)) <= 2000 &&
-		result.OpenTopic != "" && len([]rune(result.OpenTopic)) <= 1000 &&
-		result.StoryTitle != "" && len([]rune(result.StoryTitle)) <= 300 &&
+	if result.Confidence < 0 || result.Confidence > 1 || result.DecisionReason == "" || len([]rune(result.DecisionReason)) > 500 {
+		return false
+	}
+	if !result.Meaningful {
+		return !result.StoryWorthy && result.Summary == "" && result.OpenTopic == "" && result.StoryTitle == "" && result.StoryContent == "" && result.FactContent == "" && len(result.Keywords) == 0
+	}
+	if result.Summary == "" || len([]rune(result.Summary)) > 2000 ||
+		result.OpenTopic == "" || len([]rune(result.OpenTopic)) > 1000 ||
+		len(result.Keywords) < 1 || len(result.Keywords) > 8 {
+		return false
+	}
+	if !result.StoryWorthy {
+		return result.StoryTitle == "" && result.StoryContent == "" && result.FactContent == ""
+	}
+	return result.StoryTitle != "" && len([]rune(result.StoryTitle)) <= 300 &&
 		result.StoryContent != "" && len([]rune(result.StoryContent)) <= 20000 &&
 		result.FactContent != "" && len([]rune(result.FactContent)) <= 5000 &&
-		len(result.Keywords) >= 1 && len(result.Keywords) <= 8 &&
 		result.Confidence >= 0 && result.Confidence <= 1
 }
 
+const contentValuePrompt = `你是长者聊天内容筛选与整理助手。只依据输入对话判断和整理，不补充未出现的事实，不把推断写成事实。
+
+先做两级判断：
+1. meaningful：对话是否包含值得保留的信息。只有问候、寒暄、嗯啊、测试设备、重复句、零散且无法理解的短句，必须判为false并舍弃，不生成摘要。
+2. story_worthy：仅在meaningful为true时判断是否值得形成故事。具体的个人经历或回忆，且人物、时间、地点、事件、行动、感受中至少出现两类，或形成了清楚的事件脉络，才判为true。普通偏好、单个事实或简短近况可以总结，但story_worthy应为false。
+
+必须只返回JSON对象，字段为meaningful、story_worthy、decision_reason、summary、keywords、open_topic、story_title、story_content、fact_content、confidence。
+- decision_reason用一句简短中文说明判断依据。
+- meaningful=false时，除decision_reason和confidence外，其余文本必须为空字符串，keywords必须为空数组，story_worthy必须为false。
+- meaningful=true时，summary概括有意义内容，keywords为1至8个简短关键词，open_topic给出一个温和且不重复追问的后续话题。
+- story_worthy=false时，story_title、story_content、fact_content必须为空字符串。
+- story_worthy=true时，story_title和story_content忠实整理原话，fact_content只写对话中可核对的事实。
+- confidence取0到1。`
+
 func normalizedKeywords(values []string) []string {
 	result := make([]string, 0, min(len(values), 8))
 	seen := make(map[string]struct{}, len(values))
@@ -255,3 +322,32 @@ func deterministicKeywords(content string) []string {
 	}
 	return []string{string(runes)}
 }
+
+func deterministicContentDecision(content string) (meaningful, storyWorthy bool, reason string) {
+	compact := strings.Map(func(character rune) rune {
+		if unicode.IsSpace(character) || strings.ContainsRune("，。！？；、,.!?;：:\"“”‘’（）()-", character) {
+			return -1
+		}
+		return character
+	}, content)
+	for _, label := range []string{"长者", "豆包", "助手", "用户", "agent", "subject"} {
+		compact = strings.ReplaceAll(compact, label, "")
+	}
+	for _, phrase := range []string{"你好", "您好", "在吗", "嗯", "啊", "哦", "好的", "知道了", "没事", "再见", "拜拜", "听得到吗", "能听见吗", "测试"} {
+		compact = strings.ReplaceAll(compact, phrase, "")
+	}
+	if len([]rune(compact)) < 12 {
+		return false, false, "内容仅为寒暄、确认或零散短句"
+	}
+	storySignals := 0
+	for _, phrase := range []string{"小时候", "年轻时", "那年", "当时", "后来", "以前", "记得", "有一次", "我们", "我和", "去了", "发生", "因为", "结果", "高兴", "难过", "想起"} {
+		if strings.Contains(content, phrase) {
+			storySignals++
+		}
+	}
+	storyWorthy = len([]rune(compact)) >= 48 && storySignals >= 2
+	if storyWorthy {
+		return true, true, "包含较完整的个人经历与事件脉络"
+	}
+	return true, false, "包含可保留的信息，但尚不足以形成完整故事"
+}

internal/extraction/generator_local_model_test.go

@@ -0,0 +1,58 @@
+package extraction
+
+import (
+	"context"
+	"os"
+	"testing"
+	"time"
+)
+
+func TestLocalModelContentValueDecisions(t *testing.T) {
+	baseURL := os.Getenv("LOCAL_MODEL_BASE_URL")
+	if baseURL == "" {
+		t.Skip("LOCAL_MODEL_BASE_URL is not set")
+	}
+	modelID := os.Getenv("LOCAL_MODEL_ID")
+	if modelID == "" {
+		modelID = "qwen2.5:7b"
+	}
+	generator, err := NewCompatibleGenerator("openai_compatible", baseURL, "ollama-local-key", modelID, 0.1, 1200, 2*time.Minute)
+	if err != nil {
+		t.Fatal(err)
+	}
+	tests := []struct {
+		name, content          string
+		meaningful, storyWorth bool
+	}{
+		{
+			name:    "discard small talk",
+			content: "豆包：您好，今天过得怎么样？\n长者：还行。\n豆包：吃饭了吗？\n长者：嗯，吃了。\n豆包：那您好好休息。\n长者：好，再见。",
+		},
+		{
+			name:       "keep useful update without story",
+			content:    "豆包：今天胃口怎么样？\n长者：今天胃口挺好，中午吃了一碗西红柿鸡蛋面，晚上想吃点清淡的。",
+			meaningful: true,
+		},
+		{
+			name:       "create story candidate from coherent memory",
+			content:    "豆包：您还记得第一次当老师的情形吗？\n长者：记得。那是1978年秋天，我二十二岁，被分到河边小学。第一天是姐姐骑自行车送我去的，教室里有三十多个孩子。我紧张得把粉笔掉在地上，一个小姑娘帮我捡起来，全班都笑了，我也跟着笑。后来那个小姑娘一直读到大学，很多年后还回来看过我。",
+			meaningful: true, storyWorth: true,
+		},
+	}
+	for _, test := range tests {
+		t.Run(test.name, func(t *testing.T) {
+			ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+			defer cancel()
+			result, generateErr := generator.Generate(ctx, GenerationInput{Content: test.content})
+			if generateErr != nil {
+				t.Fatal(generateErr)
+			}
+			if result.Meaningful != test.meaningful || result.StoryWorthy != test.storyWorth || result.AllowStory != test.storyWorth {
+				t.Fatalf("decision mismatch: meaningful=%v story_worthy=%v allow_story=%v reason=%q summary=%q", result.Meaningful, result.StoryWorthy, result.AllowStory, result.DecisionReason, result.Summary)
+			}
+			if !result.Meaningful && (result.Summary != "" || result.StoryContent != "") {
+				t.Fatalf("discarded conversation produced content: %+v", result)
+			}
+		})
+	}
+}

internal/extraction/generator_test.go

@@ -20,7 +20,7 @@ func TestArkGeneratorProducesValidatedContent(t *testing.T) {
 		if err := json.NewDecoder(r.Body).Decode(&body); err != nil || body["model"] != "doubao-test" {
 			t.Fatalf("request body=%v err=%v", body, err)
 		}
-		_ = json.NewEncoder(w).Encode(map[string]any{"choices": []any{map[string]any{"message": map[string]any{"content": `{"summary":"谈到河边小学","keywords":["河边小学","童年"],"open_topic":"下次可以聊聊同学","story_title":"河边小学的回忆","story_content":"小时候在河边小学读书。","fact_content":"曾在河边小学读书","confidence":0.82}`}}}})
+		_ = json.NewEncoder(w).Encode(map[string]any{"choices": []any{map[string]any{"message": map[string]any{"content": `{"meaningful":true,"story_worthy":true,"decision_reason":"包含具体的童年求学回忆","summary":"谈到河边小学","keywords":["河边小学","童年"],"open_topic":"下次可以聊聊同学","story_title":"河边小学的回忆","story_content":"小时候在河边小学读书。","fact_content":"曾在河边小学读书","confidence":0.82}`}}}})
 	}))
 	defer server.Close()
 	generator, err := NewArkGenerator(server.URL+"/api/v3", "test-key", "doubao-test", time.Second)
@@ -33,6 +33,51 @@ func TestArkGeneratorProducesValidatedContent(t *testing.T) {
 	}
 }
 
+func TestCompatibleGeneratorDiscardsSmallTalk(t *testing.T) {
+	server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
+		_ = json.NewEncoder(w).Encode(map[string]any{"choices": []any{map[string]any{"message": map[string]any{"content": `{"meaningful":false,"story_worthy":false,"decision_reason":"只有问候和确认","summary":"","keywords":[],"open_topic":"","story_title":"","story_content":"","fact_content":"","confidence":0.96}`}}}})
+	}))
+	defer server.Close()
+	generator, err := NewCompatibleGenerator("openai_compatible", server.URL+"/v1", "local-key", "qwen-test", 0.1, 512, time.Second)
+	if err != nil {
+		t.Fatal(err)
+	}
+	result, err := generator.Generate(context.Background(), GenerationInput{Content: "豆包：您好。\n长者：嗯，你好。\n豆包：今天怎么样？\n长者：还行。"})
+	if err != nil || result.Meaningful || result.StoryWorthy || result.AllowStory || result.DecisionReason == "" {
+		t.Fatalf("result=%+v err=%v", result, err)
+	}
+}
+
+func TestCompatibleGeneratorKeepsMeaningfulNonStoryWithoutDraft(t *testing.T) {
+	server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
+		_ = json.NewEncoder(w).Encode(map[string]any{"choices": []any{map[string]any{"message": map[string]any{"content": `{"meaningful":true,"story_worthy":false,"decision_reason":"有明确近况但没有事件脉络","summary":"长者今天胃口不错","keywords":["胃口","近况"],"open_topic":"下次可以聊聊最近喜欢的饭菜","story_title":"","story_content":"","fact_content":"","confidence":0.87}`}}}})
+	}))
+	defer server.Close()
+	generator, err := NewCompatibleGenerator("openai_compatible", server.URL+"/v1", "local-key", "qwen-test", 0.1, 512, time.Second)
+	if err != nil {
+		t.Fatal(err)
+	}
+	result, err := generator.Generate(context.Background(), GenerationInput{Content: "长者：我今天胃口挺好的，中午吃了面条。"})
+	if err != nil || !result.Meaningful || result.StoryWorthy || result.AllowStory || result.Summary == "" {
+		t.Fatalf("result=%+v err=%v", result, err)
+	}
+}
+
+func TestCompatibleGeneratorClearsContradictoryStoryFields(t *testing.T) {
+	server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
+		_ = json.NewEncoder(w).Encode(map[string]any{"choices": []any{map[string]any{"message": map[string]any{"content": `{"meaningful":true,"story_worthy":false,"decision_reason":"只是近况","summary":"今天胃口不错","keywords":["胃口"],"open_topic":"最近喜欢吃什么？","story_title":"模型误填标题","story_content":"模型误填故事","fact_content":"模型误填事实","confidence":0.8}`}}}})
+	}))
+	defer server.Close()
+	generator, err := NewCompatibleGenerator("openai_compatible", server.URL+"/v1", "local-key", "qwen-test", 0.1, 512, time.Second)
+	if err != nil {
+		t.Fatal(err)
+	}
+	result, err := generator.Generate(context.Background(), GenerationInput{Content: "长者：今天胃口不错。"})
+	if err != nil || result.AllowStory || result.StoryTitle != "" || result.StoryContent != "" || result.FactContent != "" {
+		t.Fatalf("result=%+v err=%v", result, err)
+	}
+}
+
 func TestArkGeneratorRetriesTemporaryFailure(t *testing.T) {
 	server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, _ *http.Request) {
 		http.Error(w, "busy", http.StatusTooManyRequests)

internal/extraction/processor.go

@@ -93,7 +93,7 @@ func (p *Processor) Handle(ctx context.Context, event outbox.Event) error {
 	if len(sourceTurns) == 0 {
 		return outbox.Retryable(ErrConversationContentNotReady)
 	}
-	content := joinedTurnContent(sourceTurns)
+	content := joinedConversationContent(snapshot.turns)
 	generated, err := p.generateSafely(ctx, content, snapshot.tenantID)
 	if err != nil {
 		return err
@@ -247,12 +247,16 @@ func subjectTurns(turns []turn) []turn {
 	return items
 }
 
-func joinedTurnContent(turns []turn) string {
+func joinedConversationContent(turns []turn) string {
 	parts := make([]string, 0, len(turns))
 	for _, item := range turns {
-		parts = append(parts, item.text)
+		label := "豆包"
+		if item.speaker == "subject" {
+			label = "长者"
+		}
+		parts = append(parts, label+"："+item.text)
 	}
-	return strings.Join(parts, " ")
+	return strings.Join(parts, "\n")
 }
 
 func storeGeneration(ctx context.Context, tx pgx.Tx, conversationID string, snapshot extractionSnapshot, generated GenerationResult, generationVersion int64) error {
@@ -262,6 +266,15 @@ func storeGeneration(ctx context.Context, tx pgx.Tx, conversationID string, snap
 		sourcePublicIDs = append(sourcePublicIDs, item.publicID)
 	}
 	sourceJSON, _ := json.Marshal(sourcePublicIDs)
+	if _, err := tx.Exec(ctx, `
+		INSERT INTO conversation_content_assessment (tenant_id,subject_id,conversation_id,generation_version,meaningful,story_worthy,decision_reason,model_ref,prompt_version,confidence)
+		VALUES ($1::uuid,$2::uuid,$3::uuid,$4,$5,$6,$7,$8,$9,$10)
+		ON CONFLICT (conversation_id,generation_version) DO NOTHING`, snapshot.tenantID, snapshot.subjectID, conversationID, generationVersion, generated.Meaningful, generated.StoryWorthy, generated.DecisionReason, generated.ModelRef, generated.PromptVersion, generated.Confidence); err != nil {
+		return fmt.Errorf("store conversation content assessment: %w", err)
+	}
+	if !generated.Meaningful {
+		return tx.Commit(ctx)
+	}
 	if _, err := tx.Exec(ctx, `
 		INSERT INTO conversation_summary (tenant_id,subject_id,conversation_id,summary_type,content,source_turn_ids,model_ref,prompt_version,generation_version,confidence,status)
 		VALUES ($1::uuid,$2::uuid,$3::uuid,'conversation_summary',$4,$5::jsonb,$6,$7,$8,$9,'READY')

internal/extraction/processor_integration_test.go

@@ -40,6 +40,7 @@ func TestProcessorExtractionIdempotencyAndSensitiveContent(t *testing.T) {
 	contextID, contextPublicID := uuid.NewString(), uuid.NewString()
 	conversationID, conversationPublicID := uuid.NewString(), uuid.NewString()
 	defer func() {
+		_, _ = pool.Exec(ctx, `DELETE FROM conversation_content_assessment WHERE conversation_id=$1::uuid`, conversationID)
 		_, _ = pool.Exec(ctx, `DELETE FROM fact_candidate WHERE story_id IN (SELECT id FROM story_draft WHERE conversation_id=$1::uuid)`, conversationID)
 		_, _ = pool.Exec(ctx, `DELETE FROM story_source WHERE story_revision_id IN (SELECT sr.id FROM story_revision sr JOIN story_draft sd ON sd.id=sr.story_id WHERE sd.conversation_id=$1::uuid)`, conversationID)
 		_, _ = pool.Exec(ctx, `UPDATE story_draft SET current_revision_id=NULL WHERE conversation_id=$1::uuid`, conversationID)
@@ -97,7 +98,7 @@ func TestProcessorExtractionIdempotencyAndSensitiveContent(t *testing.T) {
 			http.Error(w, "database lock", http.StatusServiceUnavailable)
 			return
 		}
-		_, _ = io.WriteString(w, `{"choices":[{"message":{"content":"{\"summary\":\"长者谈到在河边小学教书\",\"keywords\":[\"河边小学\",\"教书经历\"],\"open_topic\":\"下次可以聊聊当年的学生\",\"story_title\":\"河边小学的回忆\",\"story_content\":\"我年轻时在河边小学教书。\",\"fact_content\":\"年轻时曾在河边小学教书\",\"confidence\":0.88}"}}]}`)
+		_, _ = io.WriteString(w, `{"choices":[{"message":{"content":"{\"meaningful\":true,\"story_worthy\":true,\"decision_reason\":\"包含具体的教书经历\",\"summary\":\"长者谈到在河边小学教书\",\"keywords\":[\"河边小学\",\"教书经历\"],\"open_topic\":\"下次可以聊聊当年的学生\",\"story_title\":\"河边小学的回忆\",\"story_content\":\"我年轻时在河边小学教书。\",\"fact_content\":\"年轻时曾在河边小学教书\",\"confidence\":0.88}"}}]}`)
 	}))
 	defer server.Close()
 	arkGenerator, err := NewArkGenerator(server.URL+"/api/v3", "integration-key", "doubao-integration", 2*time.Second)

internal/extraction/processor_safety_test.go

@@ -12,6 +12,7 @@ type safetyTestGenerator struct{ calls int }
 func (g *safetyTestGenerator) Generate(context.Context, GenerationInput) (GenerationResult, error) {
 	g.calls++
 	return GenerationResult{
+		Meaningful: true, StoryWorthy: true, DecisionReason: "测试故事",
 		Summary: "模型摘要", OpenTopic: "开放话题", StoryTitle: "标题",
 		StoryContent: "模型输出风险", FactContent: "普通事实", AllowStory: true,
 	}, nil