512 lines
17 KiB
Go
512 lines
17 KiB
Go
package services
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import (
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"encoding/json"
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"fmt"
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"strconv"
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"github.com/drama-generator/backend/domain/models"
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"github.com/drama-generator/backend/pkg/ai"
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"github.com/drama-generator/backend/pkg/logger"
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"github.com/drama-generator/backend/pkg/utils"
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"gorm.io/gorm"
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)
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type ScriptGenerationService struct {
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db *gorm.DB
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aiService *AIService
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log *logger.Logger
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}
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func NewScriptGenerationService(db *gorm.DB, log *logger.Logger) *ScriptGenerationService {
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return &ScriptGenerationService{
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db: db,
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aiService: NewAIService(db, log),
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log: log,
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}
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}
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type GenerateOutlineRequest struct {
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DramaID string `json:"drama_id" binding:"required"`
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Theme string `json:"theme" binding:"required,min=2,max=500"`
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Genre string `json:"genre"`
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Style string `json:"style"`
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Length int `json:"length"`
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Temperature float64 `json:"temperature"`
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}
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type GenerateCharactersRequest struct {
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DramaID string `json:"drama_id" binding:"required"`
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Outline string `json:"outline"`
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Count int `json:"count"`
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Temperature float64 `json:"temperature"`
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}
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type GenerateEpisodesRequest struct {
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DramaID string `json:"drama_id" binding:"required"`
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Outline string `json:"outline"`
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EpisodeCount int `json:"episode_count" binding:"required,min=1,max=100"`
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Temperature float64 `json:"temperature"`
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}
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type OutlineResult struct {
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Title string `json:"title"`
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Summary string `json:"summary"`
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Genre string `json:"genre"`
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Tags []string `json:"tags"`
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Characters []CharacterOutline `json:"characters"`
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Episodes []EpisodeOutline `json:"episodes"`
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KeyScenes []string `json:"key_scenes"`
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}
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type CharacterOutline struct {
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Name string `json:"name"`
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Role string `json:"role"`
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Description string `json:"description"`
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Personality string `json:"personality"`
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Appearance string `json:"appearance"`
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}
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type EpisodeOutline struct {
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EpisodeNumber int `json:"episode_number"`
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Title string `json:"title"`
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Summary string `json:"summary"`
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Scenes []string `json:"scenes"`
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Duration int `json:"duration"`
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}
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func (s *ScriptGenerationService) GenerateOutline(req *GenerateOutlineRequest) (*OutlineResult, error) {
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var drama models.Drama
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if err := s.db.Where("id = ?", req.DramaID).First(&drama).Error; err != nil {
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return nil, fmt.Errorf("drama not found")
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}
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systemPrompt := `你是专业短剧编剧。根据主题和剧集数量，创作完整的短剧大纲，规划好每一集的剧情走向。
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要求：
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1. 剧情紧凑，矛盾冲突强烈，节奏快
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2. 必须规划好每一集的核心剧情
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3. 每集有明确冲突和转折点，集与集之间有连贯性和悬念
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**重要：必须输出完整有效的JSON，确保所有字段完整，特别是episodes数组必须完整闭合！**
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JSON格式（紧凑，summary和episodes字段必须完整）：
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{"title":"剧名","summary":"200-250字剧情概述，包含故事背景、主要矛盾、核心冲突、完整走向","genre":"类型","tags":["标签1","标签2","标签3"],"episodes":[{"episode_number":1,"title":"标题","summary":"80字剧情概要"},{"episode_number":2,"title":"标题","summary":"80字剧情概要"}],"key_scenes":["场景1","场景2","场景3"]}
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关键要求：
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- summary控制在200-250字，简洁清晰
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- episodes必须生成用户要求的完整集数
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- 每集summary控制在80字左右
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- 确保JSON完整闭合，不要截断
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- 不要添加任何JSON外的文字说明`
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userPrompt := fmt.Sprintf(`请为以下主题创作短剧大纲：
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主题：%s`, req.Theme)
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if req.Genre != "" {
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userPrompt += fmt.Sprintf("\n类型偏好：%s", req.Genre)
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}
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if req.Style != "" {
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userPrompt += fmt.Sprintf("\n风格要求：%s", req.Style)
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}
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length := req.Length
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if length == 0 {
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length = 5
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}
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userPrompt += fmt.Sprintf("\n剧集数量：%d集", length)
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userPrompt += fmt.Sprintf("\n\n**重要：必须在episodes数组中规划完整的%d集剧情，每集都要有明确的故事内容！**", length)
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temperature := req.Temperature
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if temperature == 0 {
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temperature = 0.8
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}
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// 调整token限制：基础2000 + 每集约150 tokens（包含80-100字概要）
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maxTokens := 2000 + (length * 150)
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if maxTokens > 8000 {
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maxTokens = 8000
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}
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s.log.Infow("Generating outline with episodes",
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"episode_count", length,
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"max_tokens", maxTokens)
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text, err := s.aiService.GenerateText(
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userPrompt,
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systemPrompt,
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ai.WithTemperature(temperature),
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ai.WithMaxTokens(maxTokens),
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)
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if err != nil {
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s.log.Errorw("Failed to generate outline", "error", err)
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return nil, fmt.Errorf("生成失败: %w", err)
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}
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s.log.Infow("AI response received", "length", len(text), "preview", text[:minInt(200, len(text))])
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var result OutlineResult
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if err := utils.SafeParseAIJSON(text, &result); err != nil {
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s.log.Errorw("Failed to parse outline JSON", "error", err, "raw_response", text[:minInt(500, len(text))])
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return nil, fmt.Errorf("解析 AI 返回结果失败: %w", err)
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}
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// 将Tags转换为JSON格式存储
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tagsJSON, err := json.Marshal(result.Tags)
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if err != nil {
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s.log.Errorw("Failed to marshal tags", "error", err)
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tagsJSON = []byte("[]")
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}
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if err := s.db.Model(&drama).Updates(map[string]interface{}{
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"title": result.Title,
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"description": result.Summary,
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"genre": result.Genre,
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"tags": tagsJSON,
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}).Error; err != nil {
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s.log.Errorw("Failed to update drama", "error", err)
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}
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s.log.Infow("Outline generated", "drama_id", req.DramaID)
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return &result, nil
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}
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func (s *ScriptGenerationService) GenerateCharacters(req *GenerateCharactersRequest) ([]models.Character, error) {
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var drama models.Drama
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if err := s.db.Where("id = ? ", req.DramaID).First(&drama).Error; err != nil {
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return nil, fmt.Errorf("drama not found")
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}
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count := req.Count
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if count == 0 {
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count = 5
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}
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systemPrompt := `你是一个专业的角色分析师，擅长从剧本中提取和分析角色信息。
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你的任务是根据提供的剧本内容，提取并整理剧中出现的所有角色的详细设定。
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要求：
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1. 仔细阅读剧本，识别所有出现的角色
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2. 根据剧本中的对话、行为和描述，总结角色的性格特点
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3. 提取角色在剧本中的关键信息：背景、动机、目标、关系等
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4. 角色之间的关系必须基于剧本中的实际描述
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5. 外貌描述必须极其详细，如果剧本中有描述则使用，如果没有则根据角色设定合理推断，便于AI绘画生成角色形象
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6. 优先提取主要角色和重要配角，次要角色可以简略
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请严格按照以下 JSON 格式输出，不要添加任何其他文字：
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{
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"characters": [
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{
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"name": "角色名",
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"role": "主角/重要配角/配角",
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"description": "角色背景和简介（200-300字，包括：出身背景、成长经历、核心动机、与其他角色的关系、在故事中的作用）",
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"personality": "性格特点（详细描述，100-150字，包括：主要性格特征、行为习惯、价值观、优点缺点、情绪表达方式、对待他人的态度等）",
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"appearance": "外貌描述（极其详细，150-200字，必须包括：确切年龄、精确身高、体型身材、肤色质感、发型发色发长、眼睛颜色形状、面部特征（如眉毛、鼻子、嘴唇）、着装风格、服装颜色材质、配饰细节、标志性特征、整体气质风格等，描述要具体到可以直接用于AI绘画）",
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"voice_style": "说话风格和语气特点（详细描述，50-80字，包括：语速语调、用词习惯、口头禅、说话时的情绪特征等）"
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}
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]
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}
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注意：
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- 必须基于剧本内容提取角色，不要凭空创作
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- 优先提取主要角色和重要配角，数量根据剧本实际情况确定
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- description、personality、appearance、voice_style都必须详细描述，字数要充足
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- appearance外貌描述是重中之重，必须极其详细具体，要能让AI准确生成角色形象
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- 如果剧本中角色信息不完整，可以根据角色设定合理补充，但要符合剧本整体风格`
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outlineText := req.Outline
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if outlineText == "" {
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outlineText = fmt.Sprintf("剧名：%s\n简介：%s\n类型：%s", drama.Title, drama.Description, drama.Genre)
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}
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userPrompt := fmt.Sprintf(`剧本内容：
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%s
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请从剧本中提取并整理最多 %d 个主要角色的详细设定。`, outlineText, count)
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temperature := req.Temperature
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if temperature == 0 {
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temperature = 0.7
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}
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text, err := s.aiService.GenerateText(
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userPrompt,
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systemPrompt,
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ai.WithTemperature(temperature),
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ai.WithMaxTokens(3000),
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)
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if err != nil {
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s.log.Errorw("Failed to generate characters", "error", err)
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return nil, fmt.Errorf("生成失败: %w", err)
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}
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s.log.Infow("AI response received", "length", len(text), "preview", text[:minInt(200, len(text))])
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var result struct {
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Characters []struct {
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Name string `json:"name"`
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Role string `json:"role"`
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Description string `json:"description"`
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Personality string `json:"personality"`
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Appearance string `json:"appearance"`
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VoiceStyle string `json:"voice_style"`
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} `json:"characters"`
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}
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if err := utils.SafeParseAIJSON(text, &result); err != nil {
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s.log.Errorw("Failed to parse characters JSON", "error", err, "raw_response", text[:minInt(500, len(text))])
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return nil, fmt.Errorf("解析 AI 返回结果失败: %w", err)
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}
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var characters []models.Character
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for _, char := range result.Characters {
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// 检查角色是否已存在
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var existingChar models.Character
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err := s.db.Where("drama_id = ? AND name = ?", req.DramaID, char.Name).First(&existingChar).Error
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if err == nil {
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// 角色已存在，直接使用已存在的角色，不覆盖
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s.log.Infow("Character already exists, skipping", "drama_id", req.DramaID, "name", char.Name)
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characters = append(characters, existingChar)
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continue
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}
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// 角色不存在，创建新角色
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dramaID, _ := strconv.ParseUint(req.DramaID, 10, 32)
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character := models.Character{
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DramaID: uint(dramaID),
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Name: char.Name,
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Role: &char.Role,
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Description: &char.Description,
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Personality: &char.Personality,
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Appearance: &char.Appearance,
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VoiceStyle: &char.VoiceStyle,
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}
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if err := s.db.Create(&character).Error; err != nil {
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s.log.Errorw("Failed to create character", "error", err)
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continue
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}
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characters = append(characters, character)
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}
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s.log.Infow("Characters generated", "drama_id", req.DramaID, "total_count", len(characters), "new_count", len(characters))
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return characters, nil
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}
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func (s *ScriptGenerationService) GenerateEpisodes(req *GenerateEpisodesRequest) ([]models.Episode, error) {
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var drama models.Drama
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if err := s.db.Where("id = ? ", req.DramaID).First(&drama).Error; err != nil {
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return nil, fmt.Errorf("drama not found")
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}
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// 获取角色信息
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var characters []models.Character
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s.db.Where("drama_id = ?", req.DramaID).Find(&characters)
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var characterList string
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if len(characters) > 0 {
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characterList = "\n角色设定：\n"
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for _, char := range characters {
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characterList += fmt.Sprintf("- %s", char.Name)
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if char.Role != nil {
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characterList += fmt.Sprintf("（%s）", *char.Role)
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}
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if char.Description != nil {
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characterList += fmt.Sprintf("：%s", *char.Description)
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}
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if char.Personality != nil {
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characterList += fmt.Sprintf(" | 性格：%s", *char.Personality)
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}
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characterList += "\n"
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}
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} else {
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characterList = "\n（注意：尚未设定角色，请根据大纲创作合理的角色出场）\n"
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}
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systemPrompt := `你是一个专业的短剧编剧。你擅长根据分集规划创作详细的剧情内容。
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你的任务是根据大纲中的分集规划，将每一集的概要扩展为详细的剧情叙述。每集约180秒（3分钟），需要充实的内容。
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工作流程：
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1. 大纲中已提供每集的剧情规划（80-100字概要）
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2. 你需要将每集概要扩展为400-500字的详细剧情叙述
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3. 严格按照分集规划的数量和走向展开，不能遗漏任何一集
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详细要求：
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1. script_content用400-500字详细叙述，包括：
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- 具体场景和环境描写
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- 角色的行动、对话要点、情绪变化
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- 冲突的产生过程和激化细节
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- 关键情节点和转折
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- 为下一集埋下的伏笔
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2. 每集有明确的冲突和转折点
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3. 集与集之间有连贯性和悬念
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4. 充分展现角色性格和关系演变
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5. 内容详实，足以支撑180秒时长
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JSON格式（紧凑）：
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{"episodes":[{"episode_number":1,"title":"标题","description":"简短梗概","script_content":"400-500字详细剧情叙述","duration":210}]}
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格式说明：
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1. script_content为叙述文，不是场景对话格式
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2. 每集包含开场铺垫、冲突发展、高潮转折、结局悬念
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3. duration根据剧情复杂度设置在150-300秒
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关键要求：
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- 大纲规划了几集就必须生成几集
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- 严格按照分集规划的故事线展开
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- 每一集都要有完整的400-500字详细内容
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- 绝对不能遗漏任何一集`
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outlineText := req.Outline
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if outlineText == "" {
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outlineText = fmt.Sprintf("剧名：%s\n简介：%s\n类型：%s", drama.Title, drama.Description, drama.Genre)
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}
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userPrompt := fmt.Sprintf(`剧本大纲：
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%s
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%s
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请基于以上大纲和角色，创作 %d 集的详细剧本。
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**重要要求：**
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- 必须生成完整的 %d 集，从第1集到第%d集，不能遗漏
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- 每集约3-5分钟（150-300秒）
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- 每集的duration字段要根据剧本内容长度合理设置，不要都设置为同一个值
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- 返回的JSON中episodes数组必须包含 %d 个元素`, outlineText, characterList, req.EpisodeCount, req.EpisodeCount, req.EpisodeCount, req.EpisodeCount)
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temperature := req.Temperature
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if temperature == 0 {
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temperature = 0.7
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}
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// 根据剧集数量调整token限制
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// 模型支持128k上下文，每集400-500字约需800-1000 tokens（包含JSON结构）
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baseTokens := 3000 // 基础（系统提示+角色列表+大纲）
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perEpisodeTokens := 900 // 每集约900 tokens（支持400-500字详细内容）
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maxTokens := baseTokens + (req.EpisodeCount * perEpisodeTokens)
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// 128k上下文，可以设置较大的token限制
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// 10集约12000 tokens，20集约21000 tokens，都在安全范围内
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if maxTokens > 32000 {
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maxTokens = 32000 // 保守限制在32k，留足够空间
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}
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s.log.Infow("Generating episodes with token limit",
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"episode_count", req.EpisodeCount,
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"max_tokens", maxTokens,
|
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"estimated_per_episode", perEpisodeTokens)
|
||
|
||
text, err := s.aiService.GenerateText(
|
||
userPrompt,
|
||
systemPrompt,
|
||
ai.WithTemperature(0.8),
|
||
ai.WithMaxTokens(maxTokens),
|
||
)
|
||
|
||
if err != nil {
|
||
s.log.Errorw("Failed to generate episodes", "error", err)
|
||
return nil, fmt.Errorf("生成失败: %w", err)
|
||
}
|
||
|
||
s.log.Infow("AI response received", "length", len(text), "preview", text[:minInt(200, len(text))])
|
||
|
||
var result struct {
|
||
Episodes []struct {
|
||
EpisodeNumber int `json:"episode_number"`
|
||
Title string `json:"title"`
|
||
Description string `json:"description"`
|
||
ScriptContent string `json:"script_content"`
|
||
Duration int `json:"duration"`
|
||
} `json:"episodes"`
|
||
}
|
||
|
||
if err := utils.SafeParseAIJSON(text, &result); err != nil {
|
||
s.log.Errorw("Failed to parse episodes JSON", "error", err, "raw_response", text[:minInt(500, len(text))])
|
||
return nil, fmt.Errorf("解析 AI 返回结果失败: %w", err)
|
||
}
|
||
|
||
// 检查生成的集数是否符合要求
|
||
if len(result.Episodes) < req.EpisodeCount {
|
||
s.log.Warnw("AI generated fewer episodes than requested",
|
||
"requested", req.EpisodeCount,
|
||
"generated", len(result.Episodes))
|
||
}
|
||
|
||
// 记录每集的详细信息
|
||
for i, ep := range result.Episodes {
|
||
s.log.Infow("Episode parsed from AI",
|
||
"index", i,
|
||
"episode_number", ep.EpisodeNumber,
|
||
"title", ep.Title,
|
||
"description_length", len(ep.Description),
|
||
"script_content_length", len(ep.ScriptContent),
|
||
"duration", ep.Duration)
|
||
}
|
||
|
||
var episodes []models.Episode
|
||
for _, ep := range result.Episodes {
|
||
duration := ep.Duration
|
||
if duration == 0 {
|
||
// AI未返回时长时使用默认值
|
||
duration = 180
|
||
s.log.Warnw("Episode duration not provided by AI, using default",
|
||
"episode_number", ep.EpisodeNumber,
|
||
"default_duration", 180)
|
||
} else {
|
||
s.log.Infow("Episode duration from AI",
|
||
"episode_number", ep.EpisodeNumber,
|
||
"duration", duration)
|
||
}
|
||
|
||
// 记录即将保存的数据
|
||
s.log.Infow("Creating episode in database",
|
||
"episode_number", ep.EpisodeNumber,
|
||
"title", ep.Title,
|
||
"script_content_length", len(ep.ScriptContent),
|
||
"script_content_empty", ep.ScriptContent == "")
|
||
|
||
dramaID, err := strconv.ParseUint(req.DramaID, 10, 32)
|
||
if err != nil {
|
||
return nil, fmt.Errorf("invalid drama ID")
|
||
}
|
||
|
||
episode := models.Episode{
|
||
DramaID: uint(dramaID),
|
||
EpisodeNum: ep.EpisodeNumber,
|
||
Title: ep.Title,
|
||
Description: &ep.Description,
|
||
ScriptContent: &ep.ScriptContent,
|
||
Duration: duration,
|
||
Status: "draft",
|
||
}
|
||
|
||
if err := s.db.Create(&episode).Error; err != nil {
|
||
s.log.Errorw("Failed to create episode", "error", err)
|
||
continue
|
||
}
|
||
|
||
episodes = append(episodes, episode)
|
||
}
|
||
|
||
s.log.Infow("Episodes generated", "drama_id", req.DramaID, "count", len(episodes))
|
||
return episodes, nil
|
||
}
|
||
|
||
// GenerateScenesForEpisode 已废弃，使用 StoryboardService.GenerateStoryboard 替代
|
||
// ParseScript 已废弃，使用 GenerateCharacters 替代
|
||
|
||
// minInt 返回两个整数中较小的一个
|
||
func minInt(a, b int) int {
|
||
if a < b {
|
||
return a
|
||
}
|
||
return b
|
||
}
|