334 lines
12 KiB
Kotlin
334 lines
12 KiB
Kotlin
package com.digitalperson.util
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import android.content.ContentUris
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import android.content.Context
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import android.provider.MediaStore
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import android.util.Log
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import com.digitalperson.config.AppConfig
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import java.io.File
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import java.io.FileOutputStream
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object FileHelper {
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private const val TAG = AppConfig.TAG
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fun assetExists(context: Context, path: String): Boolean {
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return try {
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context.assets.open(path).close()
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true
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} catch (_: Throwable) {
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false
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}
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}
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fun copyAssetsToInternal(context: Context, assetDir: String, targetDir: File, files: Array<String>): File {
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if (!targetDir.exists()) targetDir.mkdirs()
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for (name in files) {
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val assetPath = "$assetDir/$name"
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val outFile = File(targetDir, name)
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if (outFile.exists() && outFile.length() > 0) continue
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try {
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context.assets.open(assetPath).use { input ->
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FileOutputStream(outFile).use { output ->
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input.copyTo(output)
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}
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}
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} catch (e: Exception) {
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Log.e(TAG, "Failed to copy asset $assetPath: ${e.message}")
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}
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}
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return targetDir
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}
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fun copySenseVoiceAssets(context: Context): File {
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val outDir = File(context.filesDir, AppConfig.Asr.MODEL_DIR)
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val files = arrayOf(
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"am.mvn",
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"chn_jpn_yue_eng_ko_spectok.bpe.model",
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"embedding.npy",
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"sense-voice-encoder.rknn"
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)
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return copyAssetsToInternal(context, AppConfig.Asr.MODEL_DIR, outDir, files)
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}
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@JvmStatic
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fun copyRetinaFaceAssets(context: Context): File {
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val outDir = File(context.filesDir, AppConfig.Face.MODEL_DIR)
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val files = arrayOf(AppConfig.Face.MODEL_NAME)
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return copyAssetsToInternal(context, AppConfig.Face.MODEL_DIR, outDir, files)
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}
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@JvmStatic
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fun copyInsightFaceAssets(context: Context): File {
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val outDir = File(context.filesDir, AppConfig.FaceRecognition.MODEL_DIR)
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val files = arrayOf(AppConfig.FaceRecognition.MODEL_NAME)
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return copyAssetsToInternal(context, AppConfig.FaceRecognition.MODEL_DIR, outDir, files)
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}
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fun ensureDir(dir: File): File {
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if (!dir.exists()) {
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val created = dir.mkdirs()
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if (!created) {
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Log.e(TAG, "Failed to create directory: ${dir.absolutePath}")
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// 如果创建失败，使用应用内部存储
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return File("/data/data/${dir.parentFile?.parentFile?.name}/files/llm")
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}
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}
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return dir
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}
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fun getAsrAudioDir(context: Context): File {
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return ensureDir(File(context.filesDir, "asr_audio"))
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}
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// @JvmStatic
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// 当前使用的模型文件名
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private val MODEL_FILE_NAME = com.digitalperson.config.AppConfig.LLM.MODEL_FILE_NAME
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fun getLLMModelPath(context: Context): String {
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Log.d(TAG, "=== getLLMModelPath START ===")
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// 从应用内部存储目录加载模型
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val llmDir = ensureDir(File(context.filesDir, AppConfig.LLM.MODEL_DIR))
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Log.d(TAG, "Loading models from: ${llmDir.absolutePath}")
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// 检查文件是否存在
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val rkllmFile = File(llmDir, MODEL_FILE_NAME)
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if (!rkllmFile.exists()) {
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Log.e(TAG, "RKLLM model not found: ${rkllmFile.absolutePath}")
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} else {
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Log.i(TAG, "RKLLM model exists, size: ${rkllmFile.length() / (1024*1024)} MB")
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}
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val modelPath = rkllmFile.absolutePath
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Log.i(TAG, "Using RKLLM model path: $modelPath")
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Log.d(TAG, "=== getLLMModelPath END ===")
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return modelPath
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}
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/**
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* 异步下载模型文件，带进度回调
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* @param context 上下文
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* @param onProgress 进度回调 (currentFile, downloadedBytes, totalBytes, progressPercent)
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* @param onComplete 完成回调 (success, message)
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*/
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@JvmStatic
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fun downloadModelFilesWithProgress(
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context: Context,
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onProgress: (String, Long, Long, Int) -> Unit,
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onComplete: (Boolean, String) -> Unit
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) {
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Log.d(TAG, "=== downloadModelFilesWithProgress START ===")
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val llmDir = ensureDir(File(context.filesDir, AppConfig.LLM.MODEL_DIR))
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// 模型文件列表 - 使用 DeepSeek-R1-Distill-Qwen-1.5B 模型
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val modelFiles = listOf(
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MODEL_FILE_NAME
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)
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// 在后台线程下载
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Thread {
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try {
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var allSuccess = true
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var totalDownloaded: Long = 0
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var totalSize: Long = 0
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// 首先计算总大小
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val downloadUrl = AppConfig.LLM.DOWNLOAD_SERVER + AppConfig.LLM.DOWNLOAD_PATH
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Log.i(TAG, "Using download server: ${AppConfig.LLM.DOWNLOAD_SERVER}")
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for (fileName in modelFiles) {
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val modelFile = File(llmDir, fileName)
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if (!modelFile.exists() || modelFile.length() == 0L) {
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val size = getFileSizeFromServer("$downloadUrl/$fileName")
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if (size > 0) {
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totalSize += size
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} else {
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// 如果无法获取文件大小，使用估计值
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val estimatedSize = AppConfig.LLM.MODEL_SIZE_ESTIMATE
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totalSize += estimatedSize
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Log.i(TAG, "Using estimated size for $fileName: ${estimatedSize / (1024*1024)} MB")
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}
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}
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}
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for (fileName in modelFiles) {
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val modelFile = File(llmDir, fileName)
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if (!modelFile.exists() || modelFile.length() == 0L) {
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Log.i(TAG, "Downloading model file: $fileName")
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try {
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downloadFileWithProgress(
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"$downloadUrl/$fileName",
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modelFile
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) { downloaded, total ->
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val progress = if (totalSize > 0) {
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((totalDownloaded + downloaded) * 100 / totalSize).toInt()
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} else 0
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onProgress(fileName, downloaded, total, progress)
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}
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totalDownloaded += modelFile.length()
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Log.i(TAG, "Downloaded model file: $fileName, size: ${modelFile.length() / (1024*1024)} MB")
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} catch (e: Exception) {
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Log.e(TAG, "Failed to download model file $fileName: ${e.message}")
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allSuccess = false
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}
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} else {
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totalDownloaded += modelFile.length()
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Log.i(TAG, "Model file exists: $fileName, size: ${modelFile.length() / (1024*1024)} MB")
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}
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}
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Log.d(TAG, "=== downloadModelFilesWithProgress END ===")
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if (allSuccess) {
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onComplete(true, "模型下载完成")
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} else {
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onComplete(false, "部分模型下载失败")
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}
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} catch (e: Exception) {
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Log.e(TAG, "Download failed: ${e.message}")
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onComplete(false, "下载失败: ${e.message}")
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}
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}.start()
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}
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/**
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* 从服务器获取文件大小
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*/
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private fun getFileSizeFromServer(url: String): Long {
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return try {
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val connection = java.net.URL(url).openConnection() as java.net.HttpURLConnection
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connection.requestMethod = "HEAD"
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connection.connectTimeout = AppConfig.LLM.DOWNLOAD_CONNECT_TIMEOUT
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connection.readTimeout = AppConfig.LLM.DOWNLOAD_READ_TIMEOUT
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// 从响应头获取 Content-Length，避免 int 溢出
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val contentLengthStr = connection.getHeaderField("Content-Length")
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var size = 0L
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if (contentLengthStr != null) {
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try {
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size = contentLengthStr.toLong()
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if (size < 0) {
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Log.w(TAG, "Invalid Content-Length value: $size")
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size = 0
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}
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} catch (e: NumberFormatException) {
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Log.w(TAG, "Invalid Content-Length format: $contentLengthStr")
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size = 0
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}
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} else {
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val contentLength = connection.contentLength
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if (contentLength > 0) {
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size = contentLength.toLong()
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} else {
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Log.w(TAG, "Content-Length not available or invalid: $contentLength")
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size = 0
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}
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}
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connection.disconnect()
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Log.i(TAG, "File size for $url: $size bytes")
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size
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} catch (e: Exception) {
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Log.w(TAG, "Failed to get file size: ${e.message}")
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0
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}
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}
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/**
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* 从网络下载文件，带进度回调
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*/
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private fun downloadFileWithProgress(
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url: String,
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destination: File,
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onProgress: (Long, Long) -> Unit
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) {
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val connection = java.net.URL(url).openConnection() as java.net.HttpURLConnection
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connection.connectTimeout = AppConfig.LLM.DOWNLOAD_CONNECT_TIMEOUT
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connection.readTimeout = AppConfig.LLM.DOWNLOAD_READ_TIMEOUT
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// 从响应头获取 Content-Length，避免 int 溢出
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val contentLengthStr = connection.getHeaderField("Content-Length")
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val totalSize = if (contentLengthStr != null) {
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try {
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contentLengthStr.toLong()
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} catch (e: NumberFormatException) {
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Log.w(TAG, "Invalid Content-Length format: $contentLengthStr")
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0
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}
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} else {
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connection.contentLength.toLong()
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}
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Log.i(TAG, "Downloading file $url, size: $totalSize bytes")
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try {
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connection.inputStream.use { input ->
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FileOutputStream(destination).use { output ->
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val buffer = ByteArray(8192)
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var downloaded: Long = 0
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var bytesRead: Int
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while (input.read(buffer).also { bytesRead = it } != -1) {
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output.write(buffer, 0, bytesRead)
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downloaded += bytesRead
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onProgress(downloaded, totalSize)
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}
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}
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}
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} finally {
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connection.disconnect()
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}
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}
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/**
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* 检查本地 LLM 模型是否可用
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*/
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@JvmStatic
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fun isLocalLLMAvailable(context: Context): Boolean {
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val llmDir = File(context.filesDir, AppConfig.LLM.MODEL_DIR)
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val rkllmFile = File(llmDir, MODEL_FILE_NAME)
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val rkllmExists = rkllmFile.exists() && rkllmFile.length() > 0
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Log.i(TAG, "LLM model check: rkllm=$rkllmExists")
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Log.i(TAG, "RKLLM file: ${rkllmFile.absolutePath}, size: ${if (rkllmFile.exists()) rkllmFile.length() / (1024*1024) else 0} MB")
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return rkllmExists
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}
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/**
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* 从网络下载文件
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*/
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private fun downloadFile(url: String, destination: File) {
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val connection = java.net.URL(url).openConnection() as java.net.HttpURLConnection
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connection.connectTimeout = 30000 // 30秒超时
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connection.readTimeout = 60000 // 60秒读取超时
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try {
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connection.inputStream.use { input ->
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FileOutputStream(destination).use { output ->
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input.copyTo(output)
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}
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}
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} finally {
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connection.disconnect()
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}
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}
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/**
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* 下载测试图片
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*/
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fun downloadTestImage(url: String, destination: File): Boolean {
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return try {
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downloadFile(url, destination)
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true
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} catch (e: Exception) {
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Log.e(TAG, "Failed to download test image: ${e.message}", e)
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false
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}
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}
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}
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