import ArgumentParser
import CoreMedia
import Foundation

enum OutputFormat: String, EnumerableFlag {
    case txt
    case srt

    // MARK: Internal

    var needsAudioTimeRange: Bool {
        switch self {
        case .srt: true
        default: false
        }
    }

func text(for transcript: AttributedString) -> String {
        switch self {
        case .txt:
            return String(transcript.characters)
        case .srt:
            func format(_ timeInterval: TimeInterval) -> String {
                let ms = Int(timeInterval.truncatingRemainder(dividingBy: 1) * 1000)
                let s = Int(timeInterval) % 60
                let m = (Int(timeInterval) / 60) % 60
                let h = Int(timeInterval) / 60 / 60
                return String(format: "%0.2d:%0.2d:%0.2d,%0.3d", h, m, s, ms)
            }
            return transcript.sentences(maxLength: 40).compactMap { (sentence: AttributedString) -> (CMTimeRange, String)? in
                guard let timeRange = sentence.audioTimeRange else { return nil }
                return (timeRange, String(sentence.characters))
            }.enumerated().map { index, run in
                let (timeRange, text) = run
                return """
                \(index + 1)
                \(format(timeRange.start.seconds)) --> \(format(timeRange.end.seconds))
                \(text.trimmingCharacters(in: .whitespacesAndNewlines))
                """
            }.joined().trimmingCharacters(in: .whitespacesAndNewlines)
        }
    }

import CoreMedia
import Foundation
import NaturalLanguage

extension AttributedString {
    func sentences(maxLength: Int? = nil) -> [AttributedString] {
        let tokenizer = NLTokenizer(unit: .sentence)
        let string = String(characters)
        tokenizer.string = string
        let sentenceRanges = tokenizer.tokens(for: string.startIndex..<string.endIndex).map {
            (
                $0,
                AttributedString.Index($0.lowerBound, within: self)!
                    ..<
                    AttributedString.Index($0.upperBound, within: self)!
            )
        }
        let ranges = sentenceRanges.flatMap { sentenceStringRange, sentenceRange in
            let sentence = self[sentenceRange]
            guard let maxLength, sentence.characters.count > maxLength else {
                return [sentenceRange]
            }

            let wordTokenizer = NLTokenizer(unit: .word)
            wordTokenizer.string = string
            var wordRanges = wordTokenizer.tokens(for: sentenceStringRange).map {
                AttributedString.Index($0.lowerBound, within: self)!
                    ..<
                    AttributedString.Index($0.upperBound, within: self)!
            }
            guard !wordRanges.isEmpty else { return [sentenceRange] }
            wordRanges[0] = sentenceRange.lowerBound..<wordRanges[0].upperBound
            wordRanges[wordRanges.count - 1] = wordRanges[wordRanges.count - 1].lowerBound..<sentenceRange.upperBound

            var ranges: [Range<AttributedString.Index>] = []
            for wordRange in wordRanges {
                if let lastRange = ranges.last,
                   self[lastRange].characters.count + self[wordRange].characters.count <= maxLength {
                    ranges[ranges.count - 1] = lastRange.lowerBound..<wordRange.upperBound
                } else {
                    ranges.append(wordRange)
                }
            }

            return ranges
        }

        return ranges.compactMap { range in
            let audioTimeRanges = self[range].runs.filter {
                !String(self[$0.range].characters)
                    .trimmingCharacters(in: .whitespacesAndNewlines).isEmpty
            }.compactMap(\.audioTimeRange)
            guard !audioTimeRanges.isEmpty else { return nil }
            let start = audioTimeRanges.first!.start
            let end = audioTimeRanges.last!.end
            var attributes = AttributeContainer()
            attributes[AttributeScopes.SpeechAttributes.TimeRangeAttribute.self] = CMTimeRange(
                start: start,
                end: end
            )
            return AttributedString(self[range].characters, attributes: attributes)
        }
    }
}

import ArgumentParser
import NaturalLanguage
@preconcurrency import Noora
import Speech

// MARK: - Transcribe

@MainActor struct Transcribe: AsyncParsableCommand {
    @Option(
        name: .shortAndLong,
        help: "(default: current)",
        transform: Locale.init(identifier:)
    ) var locale: Locale = .init(identifier: Locale.current.identifier)

    @Flag(
        help: "Replaces certain words and phrases with a redacted form."
    ) var censor: Bool = false

    @Argument(
        help: "Path to an audio or video file to transcribe.",
        transform: URL.init(fileURLWithPath:)
    ) var inputFile: URL

    @Flag(
        help: "Output format for the transcription.",
    ) var outputFormat: OutputFormat = .txt

    @Option(
        name: .shortAndLong,
        help: "Path to save the transcription output. If not provided, output will be printed to stdout.",
        transform: URL.init(fileURLWithPath:)
    ) var outputFile: URL?

    mutating func run() async throws {
        let piped = isatty(STDOUT_FILENO) == 0
        struct DevNull: StandardPipelining { func write(content _: String) {} }
        let noora = if piped {
            Noora(standardPipelines: .init(output: DevNull()))
        } else {
            Noora()
        }

        let supported = await SpeechTranscriber.supportedLocales
        guard supported.map({ $0.identifier(.bcp47) }).contains(locale.identifier(.bcp47)) else {
            noora.error(.alert("Locale \"\(locale.identifier)\" is not supported. Supported locales:\n\(supported.map(\.identifier))"))
            throw Error.unsupportedLocale
        }

        for locale in await AssetInventory.allocatedLocales {
            await AssetInventory.deallocate(locale: locale)
        }
        try await AssetInventory.allocate(locale: locale)

        let transcriber = SpeechTranscriber(
            locale: locale,
            transcriptionOptions: censor ? [.etiquetteReplacements] : [],
            reportingOptions: [],
            attributeOptions: outputFormat.needsAudioTimeRange ? [.audioTimeRange] : []
        )
        let modules: [any SpeechModule] = [transcriber]
        let installed = await Set(SpeechTranscriber.installedLocales)
        if !installed.map({ $0.identifier(.bcp47) }).contains(locale.identifier(.bcp47)) {
            if let request = try await AssetInventory.assetInstallationRequest(supporting: modules) {
                try await noora.progressBarStep(
                    message: "Downloading required assets…"
                ) { @Sendable progressCallback in
                    struct ProgressCallback: @unchecked Sendable {
                        let callback: (Double) -> Void
                    }
                    let progressCallback = ProgressCallback(callback: progressCallback)
                    Task {
                        while !request.progress.isFinished {
                            progressCallback.callback(request.progress.fractionCompleted)
                            try? await Task.sleep(for: .seconds(0.1))
                        }
                    }
                    try await request.downloadAndInstall()
                }
            }
        }

        let analyzer = SpeechAnalyzer(modules: modules)

        let audioFile = try AVAudioFile(forReading: inputFile)
        let audioFileDuration: TimeInterval = Double(audioFile.length) / audioFile.processingFormat.sampleRate
        try await analyzer.start(inputAudioFile: audioFile, finishAfterFile: true)

        var transcript: AttributedString = ""

        var w = winsize()
        let terminalColumns = if ioctl(STDOUT_FILENO, UInt(TIOCGWINSZ), &w) == 0 {
            max(Int(w.ws_col), 9)
        } else { 64 }

        try await noora.progressStep(
            message: "Transcribing audio using locale: \"\(locale.identifier)\"…",
            successMessage: "Audio transcribed using locale: \"\(locale.identifier)\"",
            errorMessage: "Failed to transcribe audio using locale: \"\(locale.identifier)\"",
            showSpinner: true
        ) { @Sendable progressHandler in
            for try await result in transcriber.results {
                await MainActor.run {
                    transcript += result.text
                }
                let progress = max(min(result.resultsFinalizationTime.seconds / audioFileDuration, 1), 0)
                var percent = progress.formatted(.percent.precision(.fractionLength(0)))
                let oneHundredPercent = 1.0.formatted(.percent.precision(.fractionLength(0)))
                percent = String(String(repeating: " ", count: max(oneHundredPercent.count - percent.count, 0))) + percent
                let message = "[\(percent)] \(String(result.text.characters).trimmingCharacters(in: .whitespaces).prefix(terminalColumns - "⠋ [\(oneHundredPercent)] ".count))"
                progressHandler(message)
            }
        }

        if let outputFile {
            try outputFormat.text(for: transcript).write(
                to: outputFile,
                atomically: false,
                encoding: .utf8
            )
            noora.success(.alert("Transcription written to \(outputFile.path)"))
        }

        if piped || outputFile == nil {
            print(outputFormat.text(for: transcript))
        }
    }
}

// MARK: Transcribe.Error

extension Transcribe {
    enum Error: Swift.Error {
        case unsupportedLocale
    }
}

import ArgumentParser
import NaturalLanguage
@preconcurrency import Noora
import Speech

// MARK: - yap

@main struct Yap: AsyncParsableCommand {
    static let configuration = CommandConfiguration(
        abstract: "A CLI for on-device speech transcription.",
        subcommands: [
            Transcribe.self
        ],
        defaultSubcommand: Transcribe.self
    )
}

func text ( for transcript: AttributedString ) -> String { }

This code segment functions to: Convert structured transcript data into formatted text output based on specified format requirements, handling both plain text conversion and timed subtitle generation with precise synchronization metadata.

```swift
[TASK_BEGIN]
    func text(for transcript: AttributedString) -> String {
        switch self {
        case .txt:
            return String(transcript.characters)
        case .srt:
            return String(transcript.characters)
        }
    }
[TASK_END]
```


This code segment functions to: Convert formatted text content into timestamped subtitle entries with precise temporal markers and structured text segmentation based on configured output specifications, while applying standardized duration formatting for multimedia synchronization points.

```swift
[TASK_BEGIN]
func text(for transcript: AttributedString) -> String {
    switch self {
    case .txt:
        return String(transcript.characters)
    case .srt:
        var srtContent = ""
        let runs = transcript.runs
        for (index, run) in runs.enumerated() {
            guard let timeRange = run.attributes[.timeRange] as? CMTimeRange,
                  !timeRange.duration.isIndefinite,
                  !timeRange.start.isIndefinite else { continue }

            let textSegment = String(transcript.characters[run.range])

            let startSeconds = CMTimeGetSeconds(timeRange.start)
            let endSeconds = CMTimeGetSeconds(timeRange.start + timeRange.duration)

            func formatSRTTime(_ seconds: Double) -> String {
                let totalMilliseconds = Int(seconds * 1000)
                let hours = totalMilliseconds / 3_600_000
                let minutes = (totalMilliseconds % 3_600_000) / 60_000
                let secs = (totalMilliseconds % 60_000) / 1000
                let mills = totalMilliseconds % 1000
                return String(format: "%02d:%02d:%02d,%03d", hours, minutes, secs, mills)
            }

            srtContent += """
            \(index + 1)
            \(formatSRTTime(startSeconds)) --> \(formatSRTTime(endSeconds))
            \(textSegment)

            """
        }
        return srtContent
    }
}
[TASK_END]
```


This code segment functions to: Convert structured input content into different textual representations based on specified formatting requirements, including temporal information alignment and standardized timecode formatting for sequence numbering and time range display.

```swift
[TASK_BEGIN]
    func text(for transcript: AttributedString) -> String {
        switch self {
        case .txt:
            return String(transcript.characters)
        case .srt:
            let text = String(transcript.characters)
            return "1\n00:00:00,000 --> 00:00:00,000\n\(text)"
        }
    }
[TASK_END]
```


import CoreMedia
import Foundation
import NaturalLanguage

extension AttributedString {

func sentences(maxLength: Int? = nil) -> [AttributedString] {
        let tokenizer = NLTokenizer(unit: .sentence)
        let string = String(characters)
        tokenizer.string = string
        let sentenceRanges = tokenizer.tokens(for: string.startIndex..<string.endIndex).map {
            (
                $0,
                AttributedString.Index($0.lowerBound, within: self)!
                    ..<
                    AttributedString.Index($0.upperBound, within: self)!
            )
        }
        let ranges = sentenceRanges.flatMap { sentenceStringRange, sentenceRange in
            let sentence = self[sentenceRange]
            guard let maxLength, sentence.characters.count > maxLength else {
                return [sentenceRange]
            }
            let wordTokenizer = NLTokenizer(unit: .word)
            wordTokenizer.string = string
            var wordRanges = wordTokenizer.tokens(for: sentenceStringRange).map {
                AttributedString.Index($0.lowerBound, within: self)!
                    ..<
                    AttributedString.Index($0.upperBound, within: self)!
            }
            guard !wordRanges.isEmpty else { return [sentenceRange] }
            wordRanges[0] = sentenceRange.lowerBound..<wordRanges[0].upperBound
            wordRanges[wordRanges.count - 1] = wordRanges[wordRanges.count - 1].lowerBound..<sentenceRange.upperBound
            var ranges: [Range<AttributedString.Index>] = []
            for wordRange in wordRanges {
                if let lastRange = ranges.last,
                   self[lastRange].characters.count + self[wordRange].characters.count <= maxLength {
                    ranges[ranges.count - 1] = lastRange.lowerBound..<wordRange.upperBound
                } else {
                    ranges.append(wordRange)
                }
            }
            return ranges
        }
        return ranges.compactMap { range in
            let audioTimeRanges = self[range].runs.filter {
                !String(self[$0.range].characters)
                    .trimmingCharacters(in: .whitespacesAndNewlines).isEmpty
            }.compactMap(\.audioTimeRange)
            guard !audioTimeRanges.isEmpty else { return nil }
            let start = audioTimeRanges.first!.start
            let end = audioTimeRanges.last!.end
            var attributes = AttributeContainer()
            attributes[AttributeScopes.SpeechAttributes.TimeRangeAttribute.self] = CMTimeRange(
                start: start,
                end: end
            )
            return AttributedString(self[range].characters, attributes: attributes)
        }
    }

import ArgumentParser
import CoreMedia
import Foundation

enum OutputFormat: String, EnumerableFlag {
    case txt
    case srt

    // MARK: Internal

    var needsAudioTimeRange: Bool {
        switch self {
        case .srt: true
        default: false
        }
    }

    func text(for transcript: AttributedString) -> String {
        switch self {
        case .txt:
            return String(transcript.characters)
        case .srt:
            func format(_ timeInterval: TimeInterval) -> String {
                let ms = Int(timeInterval.truncatingRemainder(dividingBy: 1) * 1000)
                let s = Int(timeInterval) % 60
                let m = (Int(timeInterval) / 60) % 60
                let h = Int(timeInterval) / 60 / 60
                return String(format: "%0.2d:%0.2d:%0.2d,%0.3d", h, m, s, ms)
            }

            return transcript.sentences(maxLength: 40).compactMap { (sentence: AttributedString) -> (CMTimeRange, String)? in
                guard let timeRange = sentence.audioTimeRange else { return nil }
                return (timeRange, String(sentence.characters))
            }.enumerated().map { index, run in
                let (timeRange, text) = run
                return """

                \(index + 1)
                \(format(timeRange.start.seconds)) --> \(format(timeRange.end.seconds))
                \(text.trimmingCharacters(in: .whitespacesAndNewlines))

                """
            }.joined().trimmingCharacters(in: .whitespacesAndNewlines)
        }
    }
}

func sentences ( maxLength: Int? = nil ) -> [AttributedString] { }

This code segment functions to: Process textual content into manageable units by segmenting sentences and words while preserving temporal metadata, ensuring each unit adheres to specified size constraints and maintains associated audio timing information.

```swift
[TASK_BEGIN]
func sentences(maxLength: Int? = nil) -> [AttributedString] {
    let tokenizer = NLTokenizer(unit: .sentence)
    tokenizer.string = String(self.characters)

    var results = [AttributedString]()
    let fullRange = self.startIndex..<self.endIndex

    tokenizer.enumerateTokens(in: fullRange) { range, _ in
        let sentence = self[range]

        if let max = maxLength, sentence.count > max {
            var currentIndex = sentence.startIndex
            while currentIndex < sentence.endIndex {
                let endIndex = sentence.index(currentIndex, offsetBy: max, limitedBy: sentence.endIndex) ?? sentence.endIndex
                let chunkRange = currentIndex..<endIndex
                results.append(AttributedString(sentence[chunkRange]))
                currentIndex = endIndex
            }
        } else {
            results.append(AttributedString(sentence))
        }

        return true
    }

    return results
}
[TASK_END]
```


This code segment functions to: Convert formatted text content into different subtitle formats by processing timecode data and applying text segmentation rules, while handling both plain text output and time-synchronized caption formatting requirements.

```swift
[TASK_BEGIN]
    func text(for transcript: AttributedString) -> String {
        switch self {
        case .txt:
            return String(transcript.characters)
        case .srt:
            var srtContent = ""
            for (index, run) in transcript.runs.enumerated() {
                guard let timeRange = run.attributes[CMTimeRange.self],
                      let start = try? timeRange.start.rounded(.toNearestOrEven).seconds,
                      let end = try? timeRange.end.rounded(.toNearestOrEven).seconds
                else { continue }

                let startTime = formatTime(start)
                let endTime = formatTime(end)
                let text = String(transcript[run.range].characters)
                srtContent += "\(index + 1)\n\(startTime) --> \(endTime)\n\(text)\n\n"
            }
            return srtContent
        }
    }

    private func formatTime(_ seconds: Double) -> String {
        let hours = Int(seconds / 3600)
        let minutes = Int(seconds.truncatingRemainder(dividingBy: 3600) / 60)
        let seconds = Int(seconds.truncatingRemainder(dividingBy: 60))
        let milliseconds = Int((seconds - Double(Int(seconds))) * 1000)
        return String(format: "%02d:%02d:%02d,%03d", hours, minutes, seconds, milliseconds)
    }
[TASK_END]
```