Rocky
34be2e8dd1
Use redacted cursor neighborhood and pause-aware chunks for more natural polish, validate protected terms with retry/local fallback, and structure bilingual prompts for consistency and provider prefix caching.
64 lines
3.0 KiB
Swift
64 lines
3.0 KiB
Swift
// TranslationPrompt.swift
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// OSGKeyboard · Shared
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//
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// Builds the system prompt the LLM sees when the user has the
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// translation toggle on. Re-uses the same per-provider "primary
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// language" split as `PolishingService.buildPrompt` so Chinese-native
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// LLMs get a Chinese prompt and English-native LLMs get an English one.
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//
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// The "translate AND polish" blend is intentional: ASR transcripts are
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// noisy, so the prompt asks the model to clean the noise while translating.
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// Style follows the auto-detected `AppContext` (same as the polish path).
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import Foundation
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public enum TranslationPrompt {
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/// Build the translate-and-polish system prompt.
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public static func make(
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target: TranslationLanguage,
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providerId: String,
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appContext: AppContext = .unknown,
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sourceText: String = ""
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) -> String {
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let useChinese = PolishingService.shouldUseChineseGuidance(
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inputText: sourceText,
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providerId: providerId
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)
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let contextGuideline = appContext.polishGuideline
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return useChinese
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? chinesePrompt(target: target, contextGuideline: contextGuideline)
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: englishPrompt(target: target, contextGuideline: contextGuideline)
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}
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// MARK: - Chinese prompt (for DeepSeek / Qwen / GLM / Moonshot)
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private static func chinesePrompt(target: TranslationLanguage, contextGuideline: String) -> String {
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"""
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你是一位语音输入翻译与润色助手。用户用 ASR 转写了一段可能含噪声的口述:
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1) 先识别原话的主要语言(若不确定则按用户给定的方向处理);
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2) 将内容翻译为「\(target.promptLanguageName)」,保留原意,不增删事实、不臆测;
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3) 顺带修复 ASR 噪声(同音错字、漏字、断句错乱),让译文读起来自然;
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4) 简洁;不超过原文 1.5 倍;去掉无意义的口头禅(嗯、啊、那个);
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5) 只输出译文正文,不要解释、不要加引号、不要前缀"以下是翻译"。
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当前输入场景：\(contextGuideline)
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"""
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}
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// MARK: - English prompt (for OpenAI / OpenAI-compatible non-Chinese)
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private static func englishPrompt(target: TranslationLanguage, contextGuideline: String) -> String {
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"""
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You are a voice-input translation and polishing assistant. The user has spoken informally and the transcript may contain ASR noise:
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1) Identify the input language; if unclear, assume the user wants translation INTO \(target.promptLanguageName);
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2) Translate the content INTO \(target.promptLanguageName), preserving meaning; do not invent facts or omit content;
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3) Fix ASR noise (homophone errors, missing characters, broken segmentation) so the translation reads naturally;
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4) Stay concise; do not exceed 1.5x the spoken length; drop filler words (um, uh, like);
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5) Output ONLY the translation. No quotes, no preamble, no explanation.
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Current input context: \(contextGuideline)
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"""
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}
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}
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