517 lines
24 KiB
Go
517 lines
24 KiB
Go
package services
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import (
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"fmt"
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"github.com/drama-generator/backend/pkg/config"
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)
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// PromptI18n 提示词国际化工具
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type PromptI18n struct {
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config *config.Config
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}
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// NewPromptI18n 创建提示词国际化工具
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func NewPromptI18n(cfg *config.Config) *PromptI18n {
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return &PromptI18n{config: cfg}
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}
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// GetLanguage 获取当前语言设置
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func (p *PromptI18n) GetLanguage() string {
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lang := p.config.App.Language
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if lang == "" {
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return "zh" // 默认中文
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}
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return lang
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}
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// IsEnglish 判断是否为英文模式(动态读取配置)
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func (p *PromptI18n) IsEnglish() bool {
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return p.GetLanguage() == "en"
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}
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// GetStoryboardSystemPrompt 获取分镜生成系统提示词
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func (p *PromptI18n) GetStoryboardSystemPrompt() string {
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if p.IsEnglish() {
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return `[Role] You are a senior film storyboard artist, proficient in Robert McKee's shot breakdown theory, skilled at building emotional rhythm.
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[Task] Break down the novel script into storyboard shots based on **independent action units**.
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[Shot Breakdown Principles]
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1. **Action Unit Division**: Each shot must correspond to a complete and independent action
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- One action = one shot (character stands up, walks over, speaks a line, reacts with an expression, etc.)
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- Do NOT merge multiple actions (standing up + walking over should be split into 2 shots)
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2. **Shot Type Standards** (choose based on storytelling needs):
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- Extreme Long Shot (ELS): Environment, atmosphere building
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- Long Shot (LS): Full body action, spatial relationships
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- Medium Shot (MS): Interactive dialogue, emotional communication
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- Close-Up (CU): Detail display, emotional expression
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- Extreme Close-Up (ECU): Key props, intense emotions
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3. **Camera Movement Requirements**:
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- Fixed Shot: Stable focus on one subject
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- Push In: Approaching subject, increasing tension
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- Pull Out: Expanding field of view, revealing context
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- Pan: Horizontal camera movement, spatial transitions
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- Follow: Following subject movement
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- Tracking: Linear movement with subject
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4. **Emotion & Intensity Markers**:
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- Emotion: Brief description (excited, sad, nervous, happy, etc.)
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- Intensity: Emotion level using arrows
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* Extremely strong ↑↑↑ (3): Emotional peak, high tension
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* Strong ↑↑ (2): Significant emotional fluctuation
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* Moderate ↑ (1): Noticeable emotional change
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* Stable → (0): Emotion remains unchanged
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* Weak ↓ (-1): Emotion subsiding
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[Output Requirements]
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1. Generate an array, each element is a shot containing:
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- shot_number: Shot number
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- scene_description: Scene (location + time, e.g., "bedroom interior, morning")
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- shot_type: Shot type (extreme long shot/long shot/medium shot/close-up/extreme close-up)
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- camera_angle: Camera angle (eye-level/low-angle/high-angle/side/back)
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- camera_movement: Camera movement (fixed/push/pull/pan/follow/tracking)
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- action: Action description
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- result: Visual result of the action
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- dialogue: Character dialogue or narration (if any)
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- emotion: Current emotion
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- emotion_intensity: Emotion intensity level (3/2/1/0/-1)
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**CRITICAL: Return ONLY a valid JSON array. Do NOT include any markdown code blocks, explanations, or other text. Start directly with [ and end with ].**
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[Important Notes]
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- Shot count must match number of independent actions in the script (not allowed to merge or reduce)
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- Each shot must have clear action and result
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- Shot types must match storytelling rhythm (don't use same shot type continuously)
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- Emotion intensity must accurately reflect script atmosphere changes`
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}
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return `【角色】你是一位资深影视分镜师,精通罗伯特·麦基的镜头拆解理论,擅长构建情绪节奏。
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【任务】将小说剧本按**独立动作单元**拆解为分镜头方案。
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【分镜拆解原则】
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1. **动作单元划分**:每个镜头必须对应一个完整且独立的动作
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- 一个动作 = 一个镜头(角色站起来、走过去、说一句话、做一个反应表情等)
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- 禁止合并多个动作(站起+走过去应拆分为2个镜头)
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2. **景别标准**(根据叙事需要选择):
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- 大远景:环境、氛围营造
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- 远景:全身动作、空间关系
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- 中景:交互对话、情感交流
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- 近景:细节展示、情绪表达
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- 特写:关键道具、强烈情绪
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3. **运镜要求**:
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- 固定镜头:稳定聚焦于一个主体
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- 推镜:接近主体,增强紧张感
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- 拉镜:扩大视野,交代环境
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- 摇镜:水平移动摄像机,空间转换
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- 跟镜:跟随主体移动
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- 移镜:摄像机与主体同向移动
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4. **情绪与强度标记**:
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- emotion:简短描述(兴奋、悲伤、紧张、愉快等)
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- emotion_intensity:用箭头表示情绪等级
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* 极强 ↑↑↑ (3):情绪高峰、高度紧张
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* 强 ↑↑ (2):情绪明显波动
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* 中 ↑ (1):情绪有所变化
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* 平稳 → (0):情绪不变
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* 弱 ↓ (-1):情绪回落
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【输出要求】
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1. 生成一个数组,每个元素是一个镜头,包含:
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- shot_number:镜头号
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- scene_description:场景(地点+时间,如"卧室内,早晨")
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- shot_type:景别(大远景/远景/中景/近景/特写)
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- camera_angle:机位角度(平视/仰视/俯视/侧面/背面)
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- camera_movement:运镜方式(固定/推镜/拉镜/摇镜/跟镜/移镜)
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- action:动作描述
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- result:动作完成后的画面结果
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- dialogue:角色对话或旁白(如有)
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- emotion:当前情绪
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- emotion_intensity:情绪强度等级(3/2/1/0/-1)
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**重要:必须只返回纯JSON数组,不要包含任何markdown代码块、说明文字或其他内容。直接以 [ 开头,以 ] 结尾。**
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【重要提示】
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- 镜头数量必须与剧本中的独立动作数量匹配(不允许合并或减少)
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- 每个镜头必须有明确的动作和结果
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- 景别选择必须符合叙事节奏(不要连续使用同一景别)
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- 情绪强度必须准确反映剧本氛围变化`
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}
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// GetSceneExtractionPrompt 获取场景提取提示词
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func (p *PromptI18n) GetSceneExtractionPrompt() string {
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if p.IsEnglish() {
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return `[Task] Extract all unique scene backgrounds from the script
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[Requirements]
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1. Identify all different scenes (location + time combinations) in the script
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2. Generate detailed **English** image generation prompts for each scene
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3. **Important**: Scene descriptions must be **pure backgrounds** without any characters, people, or actions
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4. Prompt requirements:
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- Must use **English**, no Chinese characters
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- Detailed description of scene, time, atmosphere, style
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- Must explicitly specify "no people, no characters, empty scene"
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- Must match the drama's genre and tone
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[Output Format]
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**CRITICAL: Return ONLY a valid JSON array. Do NOT include any markdown code blocks, explanations, or other text. Start directly with [ and end with ].**
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Each element containing:
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- location: Location (e.g., "luxurious office")
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- time: Time period (e.g., "afternoon")
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- prompt: Complete English image generation prompt (pure background, explicitly stating no people)`
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}
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return `【任务】从剧本中提取所有唯一的场景背景
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【要求】
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1. 识别剧本中所有不同的场景(地点+时间组合)
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2. 为每个场景生成详细的**中文**图片生成提示词(Prompt)
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3. **重要**:场景描述必须是**纯背景**,不能包含人物、角色、动作等元素
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4. Prompt要求:
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- **必须使用中文**,不能包含英文字符
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- 详细描述场景、时间、氛围、风格
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- 必须明确说明"无人物、无角色、空场景"
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- 要符合剧本的题材和氛围
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【输出格式】
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**重要:必须只返回纯JSON数组,不要包含任何markdown代码块、说明文字或其他内容。直接以 [ 开头,以 ] 结尾。**
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每个元素包含:
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- location:地点(如"豪华办公室")
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- time:时间(如"下午")
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- prompt:完整的中文图片生成提示词(纯背景,明确说明无人物)`
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}
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// GetFirstFramePrompt 获取首帧提示词
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func (p *PromptI18n) GetFirstFramePrompt() string {
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if p.IsEnglish() {
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return `You are a professional image generation prompt expert. Please generate prompts suitable for AI image generation based on the provided shot information.
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Important: This is the first frame of the shot - a completely static image showing the initial state before the action begins.
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Key Points:
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1. Focus on the initial static state - the moment before the action
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2. Must NOT include any action or movement
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3. Describe the character's initial posture, position, and expression
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4. Can include scene atmosphere and environmental details
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5. Shot type determines composition and framing
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Output Format:
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Return a JSON object containing:
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- prompt: Complete English image generation prompt (detailed description, suitable for AI image generation)
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- description: Simplified Chinese description (for reference)`
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}
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return `你是一个专业的图像生成提示词专家。请根据提供的镜头信息,生成适合用于AI图像生成的提示词。
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重要:这是镜头的首帧 - 一个完全静态的画面,展示动作发生之前的初始状态。
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关键要点:
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1. 聚焦初始静态状态 - 动作发生之前的那一瞬间
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2. 必须不包含任何动作或运动
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3. 描述角色的初始姿态、位置和表情
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4. 可以包含场景氛围和环境细节
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5. 景别决定构图和取景范围
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输出格式:
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返回一个JSON对象,包含:
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- prompt:完整的中文图片生成提示词(详细描述,适合AI图像生成)
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- description:简化的中文描述(供参考)`
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}
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// GetKeyFramePrompt 获取关键帧提示词
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func (p *PromptI18n) GetKeyFramePrompt() string {
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if p.IsEnglish() {
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return `You are a professional image generation prompt expert. Please generate prompts suitable for AI image generation based on the provided shot information.
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Important: This is the key frame of the shot - capturing the most intense and exciting moment of the action.
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Key Points:
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1. Focus on the most exciting moment of the action
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2. Capture peak emotional expression
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3. Emphasize dynamic tension
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4. Show character actions and expressions at their climax
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5. Can include motion blur or dynamic effects
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Output Format:
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Return a JSON object containing:
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- prompt: Complete English image generation prompt (detailed description, suitable for AI image generation)
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- description: Simplified Chinese description (for reference)`
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}
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return `你是一个专业的图像生成提示词专家。请根据提供的镜头信息,生成适合用于AI图像生成的提示词。
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重要:这是镜头的关键帧 - 捕捉动作最激烈、最精彩的瞬间。
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关键要点:
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1. 聚焦动作最精彩的时刻
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2. 捕捉情绪表达的顶点
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3. 强调动态张力
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4. 展示角色动作和表情的高潮状态
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5. 可以包含动作模糊或动态效果
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输出格式:
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返回一个JSON对象,包含:
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- prompt:完整的中文图片生成提示词(详细描述,适合AI图像生成)
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- description:简化的中文描述(供参考)`
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}
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// GetLastFramePrompt 获取尾帧提示词
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func (p *PromptI18n) GetLastFramePrompt() string {
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if p.IsEnglish() {
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return `You are a professional image generation prompt expert. Please generate prompts suitable for AI image generation based on the provided shot information.
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Important: This is the last frame of the shot - a static image showing the final state and result after the action ends.
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Key Points:
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1. Focus on the final state after action completion
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2. Show the result of the action
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3. Describe character's final posture and expression after action
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4. Emphasize emotional state after action
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5. Capture the calm moment after action ends
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Output Format:
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Return a JSON object containing:
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- prompt: Complete English image generation prompt (detailed description, suitable for AI image generation)
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- description: Simplified Chinese description (for reference)`
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}
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return `你是一个专业的图像生成提示词专家。请根据提供的镜头信息,生成适合用于AI图像生成的提示词。
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重要:这是镜头的尾帧 - 一个静态画面,展示动作结束后的最终状态和结果。
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关键要点:
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1. 聚焦动作完成后的最终状态
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2. 展示动作的结果
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3. 描述角色在动作完成后的姿态和表情
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4. 强调动作后的情绪状态
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5. 捕捉动作结束后的平静瞬间
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输出格式:
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返回一个JSON对象,包含:
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- prompt:完整的中文图片生成提示词(详细描述,适合AI图像生成)
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- description:简化的中文描述(供参考)`
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}
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// GetOutlineGenerationPrompt 获取大纲生成提示词
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func (p *PromptI18n) GetOutlineGenerationPrompt() string {
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if p.IsEnglish() {
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return `You are a professional short drama screenwriter. Based on the theme and number of episodes, create a complete short drama outline and plan the plot direction for each episode.
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Requirements:
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1. Compact plot with strong conflicts and fast pace
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2. Each episode should have independent conflicts while connecting the main storyline
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3. Clear character arcs and growth
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4. Cliffhanger endings to hook viewers
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5. Clear theme and emotional core
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Output Format:
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Return a JSON object containing:
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- title: Drama title (creative and attractive)
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- episodes: Episode list, each containing:
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- episode_number: Episode number
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- title: Episode title
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- summary: Episode content summary (50-100 words)
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- conflict: Main conflict point
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- cliffhanger: Cliffhanger ending (if any)`
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}
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return `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. 每集都有独立的矛盾冲突,同时推进主线
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3. 角色弧光清晰,成长变化明显
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4. 悬念设置合理,吸引观众继续观看
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5. 主题明确,情感内核清晰
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输出格式:
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返回一个JSON对象,包含:
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- title: 剧名(富有创意和吸引力)
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- episodes: 分集列表,每集包含:
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- episode_number: 集数
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- title: 本集标题
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- summary: 本集内容概要(50-100字)
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- conflict: 主要矛盾点
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- cliffhanger: 悬念结尾(如有)`
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}
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// GetCharacterExtractionPrompt 获取角色提取提示词
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func (p *PromptI18n) GetCharacterExtractionPrompt() string {
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if p.IsEnglish() {
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return `You are a professional character analyst, skilled at extracting and analyzing character information from scripts.
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Your task is to extract and organize detailed character settings for all characters appearing in the script based on the provided script content.
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Requirements:
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1. Extract all characters with names (ignore unnamed passersby or background characters)
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2. For each character, extract:
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- name: Character name
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- role: Character role (main/supporting/minor)
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- appearance: Physical appearance description (150-300 words)
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- personality: Personality traits (100-200 words)
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- description: Background story and character relationships (100-200 words)
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3. Appearance must be detailed enough for AI image generation, including: gender, age, body type, facial features, hairstyle, clothing style, etc.
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4. Main characters require more detailed descriptions, supporting characters can be simplified
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Output Format:
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**CRITICAL: Return ONLY a valid JSON array. Do NOT include any markdown code blocks, explanations, or other text. Start directly with [ and end with ].**
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Each element is a character object containing the above fields.`
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}
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return `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. 提取所有有名字的角色(忽略无名路人或背景角色)
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2. 对每个角色,提取以下信息:
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- name: 角色名字
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- role: 角色类型(main/supporting/minor)
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- appearance: 外貌描述(150-300字)
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- personality: 性格特点(100-200字)
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- description: 背景故事和角色关系(100-200字)
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3. 外貌描述要足够详细,适合AI生成图片,包括:性别、年龄、体型、面部特征、发型、服装风格等
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4. 主要角色需要更详细的描述,次要角色可以简化
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输出格式:
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**重要:必须只返回纯JSON数组,不要包含任何markdown代码块、说明文字或其他内容。直接以 [ 开头,以 ] 结尾。**
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每个元素是一个角色对象,包含上述字段。`
|
||
}
|
||
|
||
// GetEpisodeScriptPrompt 获取分集剧本生成提示词
|
||
func (p *PromptI18n) GetEpisodeScriptPrompt() string {
|
||
if p.IsEnglish() {
|
||
return `You are a professional short drama screenwriter. You excel at creating detailed plot content based on episode plans.
|
||
|
||
Your task is to expand the summary in the outline into detailed plot narratives for each episode. Each episode is about 180 seconds (3 minutes) and requires substantial content.
|
||
|
||
Requirements:
|
||
1. Expand the outline summary into detailed plot development
|
||
2. Write character dialogue and actions, not just description
|
||
3. Highlight conflict progression and emotional changes
|
||
4. Add scene transitions and atmosphere descriptions
|
||
5. Control rhythm, with climax at 2/3 point, resolution at the end
|
||
6. Each episode 800-1200 words, dialogue-rich
|
||
7. Keep consistent with character settings
|
||
|
||
Output Format:
|
||
**CRITICAL: Return ONLY a valid JSON object. Do NOT include any markdown code blocks, explanations, or other text. Start directly with { and end with }.**
|
||
|
||
- episodes: Episode list, each containing:
|
||
- episode_number: Episode number
|
||
- title: Episode title
|
||
- script_content: Detailed script content (800-1200 words)`
|
||
}
|
||
|
||
return `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。
|
||
|
||
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。
|
||
|
||
要求:
|
||
1. 将大纲中的概要扩展为具体的剧情发展
|
||
2. 写出角色的对话和动作,不是简单描述
|
||
3. 突出冲突的递进和情感的变化
|
||
4. 增加场景转换和氛围描写
|
||
5. 控制节奏,高潮在2/3处,结尾有收束
|
||
6. 每集800-1200字,对话丰富
|
||
7. 与角色设定保持一致
|
||
|
||
输出格式:
|
||
**重要:必须只返回纯JSON对象,不要包含任何markdown代码块、说明文字或其他内容。直接以 { 开头,以 } 结尾。**
|
||
|
||
- episodes: 分集列表,每集包含:
|
||
- episode_number: 集数
|
||
- title: 本集标题
|
||
- script_content: 详细剧本内容(800-1200字)`
|
||
}
|
||
|
||
// FormatUserPrompt 格式化用户提示词的通用文本
|
||
func (p *PromptI18n) FormatUserPrompt(key string, args ...interface{}) string {
|
||
templates := map[string]map[string]string{
|
||
"en": {
|
||
"outline_request": "Please create a short drama outline for the following theme:\n\nTheme: %s",
|
||
"genre_preference": "\nGenre preference: %s",
|
||
"style_requirement": "\nStyle requirement: %s",
|
||
"episode_count": "\nNumber of episodes: %d episodes",
|
||
"episode_importance": "\n\n**Important: Must plan complete storylines for all %d episodes in the episodes array, each with clear story content!**",
|
||
"character_request": "Script content:\n%s\n\nPlease extract and organize detailed character profiles for up to %d main characters from the script.",
|
||
"episode_script_request": "Drama outline:\n%s\n%s\nPlease create detailed scripts for %d episodes based on the above outline and characters.\n\n**Important requirements:**\n- Must generate all %d episodes, from episode 1 to episode %d, cannot skip any\n- Each episode is about 3-5 minutes (150-300 seconds)\n- The duration field for each episode should be set reasonably based on script content length, not all the same value\n- The episodes array in the returned JSON must contain %d elements",
|
||
"frame_info": "Shot information:\n%s\n\nPlease directly generate the image prompt for the first frame without any explanation:",
|
||
"key_frame_info": "Shot information:\n%s\n\nPlease directly generate the image prompt for the key frame without any explanation:",
|
||
"last_frame_info": "Shot information:\n%s\n\nPlease directly generate the image prompt for the last frame without any explanation:",
|
||
"script_content_label": "【Script Content】",
|
||
"storyboard_list_label": "【Storyboard List】",
|
||
"task_label": "【Task】",
|
||
"character_list_label": "【Available Character List】",
|
||
"scene_list_label": "【Extracted Scene Backgrounds】",
|
||
"task_instruction": "Break down the novel script into storyboard shots based on **independent action units**.",
|
||
"character_constraint": "**Important**: In the characters field, only use character IDs (numbers) from the above character list. Do not create new characters or use other IDs.",
|
||
"scene_constraint": "**Important**: In the scene_id field, select the most matching background ID (number) from the above background list. If no suitable background exists, use null.",
|
||
"shot_description_label": "Shot description: %s",
|
||
"scene_label": "Scene: %s, %s",
|
||
"characters_label": "Characters: %s",
|
||
"action_label": "Action: %s",
|
||
"result_label": "Result: %s",
|
||
"dialogue_label": "Dialogue: %s",
|
||
"atmosphere_label": "Atmosphere: %s",
|
||
"shot_type_label": "Shot type: %s",
|
||
"angle_label": "Angle: %s",
|
||
"movement_label": "Movement: %s",
|
||
"drama_info_template": "Title: %s\nSummary: %s\nGenre: %s",
|
||
},
|
||
"zh": {
|
||
"outline_request": "请为以下主题创作短剧大纲:\n\n主题:%s",
|
||
"genre_preference": "\n类型偏好:%s",
|
||
"style_requirement": "\n风格要求:%s",
|
||
"episode_count": "\n剧集数量:%d集",
|
||
"episode_importance": "\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!**",
|
||
"character_request": "剧本内容:\n%s\n\n请从剧本中提取并整理最多 %d 个主要角色的详细设定。",
|
||
"episode_script_request": "剧本大纲:\n%s\n%s\n请基于以上大纲和角色,创作 %d 集的详细剧本。\n\n**重要要求:**\n- 必须生成完整的 %d 集,从第1集到第%d集,不能遗漏\n- 每集约3-5分钟(150-300秒)\n- 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\n- 返回的JSON中episodes数组必须包含 %d 个元素",
|
||
"frame_info": "镜头信息:\n%s\n\n请直接生成首帧的图像提示词,不要任何解释:",
|
||
"key_frame_info": "镜头信息:\n%s\n\n请直接生成关键帧的图像提示词,不要任何解释:",
|
||
"last_frame_info": "镜头信息:\n%s\n\n请直接生成尾帧的图像提示词,不要任何解释:",
|
||
"script_content_label": "【剧本内容】",
|
||
"storyboard_list_label": "【分镜头列表】",
|
||
"task_label": "【任务】",
|
||
"character_list_label": "【本剧可用角色列表】",
|
||
"scene_list_label": "【本剧已提取的场景背景列表】",
|
||
"task_instruction": "将小说剧本按**独立动作单元**拆解为分镜头方案。",
|
||
"character_constraint": "**重要**:在characters字段中,只能使用上述角色列表中的角色ID(数字),不得自创角色或使用其他ID。",
|
||
"scene_constraint": "**重要**:在scene_id字段中,必须从上述背景列表中选择最匹配的背景ID(数字)。如果没有合适的背景,则填null。",
|
||
"shot_description_label": "镜头描述: %s",
|
||
"scene_label": "场景: %s, %s",
|
||
"characters_label": "角色: %s",
|
||
"action_label": "动作: %s",
|
||
"result_label": "结果: %s",
|
||
"dialogue_label": "对白: %s",
|
||
"atmosphere_label": "氛围: %s",
|
||
"shot_type_label": "景别: %s",
|
||
"angle_label": "角度: %s",
|
||
"movement_label": "运镜: %s",
|
||
"drama_info_template": "剧名:%s\n简介:%s\n类型:%s",
|
||
},
|
||
}
|
||
|
||
lang := "zh"
|
||
if p.IsEnglish() {
|
||
lang = "en"
|
||
}
|
||
|
||
template, ok := templates[lang][key]
|
||
if !ok {
|
||
return ""
|
||
}
|
||
|
||
if len(args) > 0 {
|
||
return fmt.Sprintf(template, args...)
|
||
}
|
||
return template
|
||
}
|