OSGKeyboard/OSGKeyboardShared/Services/PolishingService.swift

// PolishingService.swift
// OSGKeyboard · Shared
//
// v0.3.0 rewrite: one-step "intelligent" polish that combines ASR
// error correction, filler removal, and tone adaptation in a single
// LLM call. The previous design was two separate steps (correction
// then polish) which doubled latency and token cost; Typeless,
// Wispr Flow, and the "intelligent" rewrite literature all confirm
// the merged prompt performs just as well for everyday Chinese /
// English dictation while halving the network round-trip.
//
// Engine matrix:
//   - `engineMode == "cloud"`  → always polish
//   - `engineMode == "local"`,
//     `localModeCloudPolishEnabled == false` → ASR-only, return raw
//   - `engineMode == "local"`,
//     `localModeCloudPolishEnabled == true`  → polish via user's LLM
//   - `polishIntensity == .off`               → ASR-only, return raw,
//     regardless of engine mode
//   - Missing API key                          → return raw + throw
//     `.missingAPIKey` so the caller can show the "fill in your key"
//     hint inline
//
// Caller-supplied `PolishContext` carries the per-call signals:
//   - `appContext`     code / email / chat / document / unknown
//   - `intensity`      off / light / medium / heavy (per-call
//     override; default is the user-configured value)
//   - `precedingText`  optional tail of the cursor's preceding text
//     for reference resolution
//
// The prompt is intentionally a single message; multi-message
// conversation history would let earlier hallucinations pollute
// later calls (see MIT 2026 "Do LLMs Benefit From Their Own Words?")
// and the user expectation is that each take is independent.

import Foundation

public actor PolishingService {

    public enum PolishError: Error, Equatable {
        case noTranscript
        case timeout
        /// v0.2.0: local engine + cloud-polish-on, but the user hasn't
        /// saved an API key in the Keychain. Caller surfaces an Alert
        /// telling them to fill it in; we deliver the raw transcript
        /// so no data is lost.
        case missingAPIKey
    }

    private let store: AppGroupStore
    private let timeout: TimeInterval
    /// Optional injected client (mostly for testing). When nil we build
    /// one from `store.makeClient()` per call.
    private let injectedClient: LLMClient?

    /// Default `timeout` is `LLMClient.requestTimeout + 1` second so the
    /// safety-net `withThrowingTaskGroup` never wins the race against
    /// the URL request itself; if the request times out cleanly the
    /// network error reaches us first. The +1 is the single point of
    /// slack between the two clocks — keep it here, not in `LLMClient`.
    public init(
        store: AppGroupStore = AppGroupStore(),
        client: LLMClient? = nil,
        timeout: TimeInterval? = nil
    ) {
        self.store = store
        self.injectedClient = client
        self.timeout = timeout ?? (LLMClientFactory.defaultRequestTimeout + 1)
    }

    public func polish(_ raw: String, context: PolishContext? = nil) async throws -> String {
        let trimmed = raw.trimmingCharacters(in: .whitespacesAndNewlines)
        guard !trimmed.isEmpty else { throw PolishError.noTranscript }

        // Resolve per-call context: per-call override wins over the
        // user-configured App Group value.
        let resolvedContext = resolveContext(override: context)

        // "off" intensity never calls the LLM, regardless of engine.
        // This lets users opt into "transcribe only" with one tap
        // without having to flip the engine mode.
        if resolvedContext.intensity == .off {
            return trimmed
        }

        // Local engine + cloud-polish-off: pure ASR, no LLM.
        if store.engineMode == "local", !store.localModeCloudPolishEnabled {
            return trimmed
        }

        // Cloud engine or local+cloud-polish-on needs an API key.
        guard !store.apiKey.isEmpty else {
            throw PolishError.missingAPIKey
        }

        return try await polishRemote(trimmed, context: resolvedContext)
    }

    /// Build the final `PolishContext` for this call. Per-call
    /// overrides take precedence; otherwise we read the user-configured
    /// values out of the App Group (so the keyboard extension's
    /// `PolishingService` instance does not need to know about
    /// `ProviderConfig`).
    private func resolveContext(override: PolishContext?) -> PolishContext {
        guard let override else {
            return PolishContext(
                appContext: store.detectedAppContext?.context ?? .unknown,
                intensity: store.polishIntensity
            )
        }
        // If the override leaves a field at its default-when-nil
        // value, fall back to the App Group value. Today every
        // `PolishContext` field is non-optional so this branch
        // simply forwards; kept for future-proofing.
        return override
    }

    private func polishRemote(_ trimmed: String, context: PolishContext) async throws -> String {
        let client = injectedClient ?? store.makeClient()
        let prompt = buildPrompt(for: trimmed, context: context)
        let budget = effectiveTimeout(for: trimmed)

        return try await withThrowingTaskGroup(of: String.self) { group in
            group.addTask {
                try await client.polish(trimmed, systemPrompt: prompt)
            }
            group.addTask {
                try await Task.sleep(nanoseconds: UInt64(budget * 1_000_000_000))
                throw PolishError.timeout
            }
            let result = try await group.next()!
            group.cancelAll()
            return result
        }
    }

    /// Build the one-step "intelligent" prompt. The structure is:
    ///   1. Role
    ///   2. Three numbered tasks (correction, polish, style)
    ///   3. Hard rules (do-not-modify list, length cap, short-circuit)
    ///   4. User dictionary block (if any)
    ///   5. Context + intensity guidelines
    ///   6. Optional preceding text
    ///   7. The transcript to process
    ///   8. Output contract
    ///
    /// The Chinese / English split mirrors the existing per-provider
    /// default system prompt in `AppGroupStore.defaultSystemPrompt(for:)`
    /// so the polish step stays in the user's chosen output language.
    internal func buildPrompt(for text: String, context: PolishContext) -> String {
        let dictionary = store.personalDictionary
        let dictionaryBlock = dictionary.promptFragment()
        let contextGuideline = context.appContext.polishGuideline
        let intensityGuideline = context.intensity.promptGuideline
        let precedingBlock = context.precedingForPrompt
            .map { "上文（仅供参考，**不要**改写）：\n\($0)\n" } ?? ""
        let useChinese = shouldUseChineseGuidance(providerId: store.providerId)

        if useChinese {
            return """
            你是智能语音输入法的后处理引擎。一次完成三件事：

            ## 任务 1：纠错
            - 修正明显的语音识别错误（同音字、近音字、漏字、错字）
            - 修正专有名词、英文术语（参考下面的用户词典）
            - **绝不**修改数字、人名、地名（除非明显错得离谱）

            ## 任务 2：润色
            - 删除冗余的语气词（嗯、呃、那个、就是、然后、对、ok）
            - 删除重复说错的字句
            - 必要时调整语序让表达更通顺
            - 加合适的标点

            ## 任务 3：风格适配
            当前输入场景：\(context.appContext.rawValue)
            风格要求：\(contextGuideline)
            润色档位：\(intensityGuideline)

            ## 重要规则
            1. **最小改动原则**：原文已经能听懂的部分不要重写
            2. 保留说话人的口吻和意图
            3. 不添加原文中没有的信息
            4. 短句（≤ 8 个中文字符 或 ≤ 15 个英文字符）直接原样返回，不要润色
            5. 输出语言必须与原文一致

            \(dictionaryBlock.isEmpty ? "" : "## 用户词典（必须原样保留，禁止改写）\n\(dictionaryBlock)\n")
            \(precedingBlock)
            ## 原文
            \(text)

            请直接输出处理后的文本，**不要任何解释**。
            """
        } else {
            return """
            You are the post-processing engine of a voice-input keyboard. Complete three tasks in one pass:

            ## Task 1: Correction
            - Fix obvious speech-recognition errors (homophones, near-misses, missing/extra characters).
            - Correct proper nouns, English terms, and technical identifiers (see the user dictionary below).
            - **Never** alter numbers, person names, or place names unless clearly wrong.

            ## Task 2: Polish
            - Remove redundant filler words (um, uh, like, you know, basically).
            - Remove duplicated fragments the speaker self-corrected.
            - Adjust obviously broken word order.
            - Add appropriate punctuation and capitalization.

            ## Task 3: Style adaptation
            Current input context: \(context.appContext.rawValue)
            Style guideline: \(contextGuideline)
            Polish intensity: \(intensityGuideline)

            ## Hard rules
            1. Minimum-change principle: do not rewrite parts the user already said clearly.
            2. Preserve the speaker's voice and intent.
            3. Never add information that is not in the original.
            4. Short inputs (≤ 15 English words or ≤ 8 CJK characters) must be returned verbatim.
            5. Output language must match the input language.

            \(dictionaryBlock.isEmpty ? "" : "## User dictionary (must be preserved verbatim)\n\(dictionaryBlock)\n")
            \(precedingBlock)
            ## Original transcript
            \(text)

            Output the processed text directly. **No explanation, no quotes, no preamble.**
            """
        }
    }

    /// Mirror `AppGroupStore.defaultSystemPrompt(for:)` — Chinese LLM
    /// providers get a Chinese prompt, English ones get English.
    /// Keeping these aligned avoids the "model answers in the wrong
    /// language" failure mode that LLM benchmarks consistently flag.
    private func shouldUseChineseGuidance(providerId: String) -> Bool {
        switch providerId {
        case "zhipu", "moonshot", "qwen", "deepseek":
            return true
        default:
            return false
        }
    }

    /// Scale polish budget with transcript length (3-minute Flow utterances).
    private func effectiveTimeout(for text: String) -> TimeInterval {
        let scaled = timeout + (Double(text.count) / 200.0) * 2.0
        return min(max(scaled, timeout), 120)
    }
}