Merge pull request #16 from ccp-p/master

feat(transcriber): 添加 Bcut 和 Kuaishou 转录器实现，优化转录服务提供器

backend/app/transcriber/bcut.py

@@ -0,0 +1,250 @@
+import json
+import logging
+import time
+from typing import Optional, List, Dict, Union
+
+import requests
+
+from app.decorators.timeit import timeit
+from app.models.transcriber_model import TranscriptSegment, TranscriptResult
+from app.transcriber.base import Transcriber
+from app.utils.logger import get_logger
+from events import transcription_finished
+
+__version__ = "0.0.3"
+
+API_BASE_URL = "https://member.bilibili.com/x/bcut/rubick-interface"
+
+# 申请上传
+API_REQ_UPLOAD = API_BASE_URL + "/resource/create"
+
+# 提交上传
+API_COMMIT_UPLOAD = API_BASE_URL + "/resource/create/complete"
+
+# 创建任务
+API_CREATE_TASK = API_BASE_URL + "/task"
+
+# 查询结果
+API_QUERY_RESULT = API_BASE_URL + "/task/result"
+
+logger = get_logger(__name__)
+
+class BcutTranscriber(Transcriber):
+    """必剪 语音识别接口"""
+    headers = {
+        'User-Agent': 'Bilibili/1.0.0 (https://www.bilibili.com)',
+        'Content-Type': 'application/json'
+    }
+
+    def __init__(self):
+        self.session = requests.Session()
+        self.task_id = None
+        self.__etags = []
+
+        self.__in_boss_key: Optional[str] = None
+        self.__resource_id: Optional[str] = None
+        self.__upload_id: Optional[str] = None
+        self.__upload_urls: List[str] = []
+        self.__per_size: Optional[int] = None
+        self.__clips: Optional[int] = None
+
+        self.__etags: List[str] = []
+        self.__download_url: Optional[str] = None
+        self.task_id: Optional[str] = None
+        
+    def _load_file(self, file_path: str) -> bytes:
+        """读取文件内容"""
+        with open(file_path, 'rb') as f:
+            return f.read()
+
+    def _upload(self, file_path: str) -> None:
+        """申请上传"""
+        file_binary = self._load_file(file_path)
+        if not file_binary:
+            raise ValueError("无法读取文件数据")
+            
+        payload = json.dumps({
+            "type": 2,
+            "name": "audio.mp3",
+            "size": len(file_binary),
+            "ResourceFileType": "mp3",
+            "model_id": "8",
+        })
+
+        resp = self.session.post(
+            API_REQ_UPLOAD,
+            data=payload,
+            headers=self.headers
+        )
+        resp.raise_for_status()
+        resp = resp.json()
+        resp_data = resp["data"]
+
+        self.__in_boss_key = resp_data["in_boss_key"]
+        self.__resource_id = resp_data["resource_id"]
+        self.__upload_id = resp_data["upload_id"]
+        self.__upload_urls = resp_data["upload_urls"]
+        self.__per_size = resp_data["per_size"]
+        self.__clips = len(resp_data["upload_urls"])
+
+        logger.info(
+            f"申请上传成功, 总计大小{resp_data['size'] // 1024}KB, {self.__clips}分片, 分片大小{resp_data['per_size'] // 1024}KB: {self.__in_boss_key}"
+        )
+        self.__upload_part(file_binary)
+        self.__commit_upload()
+
+    def __upload_part(self, file_binary: bytes) -> None:
+        """上传音频数据"""
+        for clip in range(self.__clips):
+            start_range = clip * self.__per_size
+            end_range = min((clip + 1) * self.__per_size, len(file_binary))
+            logger.info(f"开始上传分片{clip}: {start_range}-{end_range}")
+            resp = self.session.put(
+                self.__upload_urls[clip],
+                data=file_binary[start_range:end_range],
+                headers={'Content-Type': 'application/octet-stream'}
+            )
+            resp.raise_for_status()
+            etag = resp.headers.get("Etag", "").strip('"')
+            self.__etags.append(etag)
+            logger.info(f"分片{clip}上传成功: {etag}")
+
+    def __commit_upload(self) -> None:
+        """提交上传数据"""
+        data = json.dumps({
+            "InBossKey": self.__in_boss_key,
+            "ResourceId": self.__resource_id,
+            "Etags": ",".join(self.__etags),
+            "UploadId": self.__upload_id,
+            "model_id": "8",
+        })
+        resp = self.session.post(
+            API_COMMIT_UPLOAD,
+            data=data,
+            headers=self.headers
+        )
+        resp.raise_for_status()
+        resp = resp.json()
+        if resp.get("code") != 0:
+            error_msg = f"上传提交失败: {resp.get('message', '未知错误')}"
+            logger.error(error_msg)
+            raise Exception(error_msg)
+            
+        self.__download_url = resp["data"]["download_url"]
+        logger.info(f"提交成功，下载链接: {self.__download_url}")
+
+    def _create_task(self) -> str:
+        """开始创建转换任务"""
+        resp = self.session.post(
+            API_CREATE_TASK, json={"resource": self.__download_url, "model_id": "8"}, headers=self.headers
+        )
+        resp.raise_for_status()
+        resp = resp.json()
+        if resp.get("code") != 0:
+            error_msg = f"创建任务失败: {resp.get('message', '未知错误')}"
+            logger.error(error_msg)
+            raise Exception(error_msg)
+            
+        self.task_id = resp["data"]["task_id"]
+        logger.info(f"任务已创建: {self.task_id}")
+        return self.task_id
+
+    def _query_result(self) -> dict:
+        """查询转换结果"""
+        resp = self.session.get(
+            API_QUERY_RESULT, 
+            params={"model_id": 7, "task_id": self.task_id}, 
+            headers=self.headers
+        )
+        resp.raise_for_status()
+        resp = resp.json()
+        if resp.get("code") != 0:
+            error_msg = f"查询结果失败: {resp.get('message', '未知错误')}"
+            logger.error(error_msg)
+            raise Exception(error_msg)
+            
+        return resp["data"]
+
+    @timeit
+    def transcript(self, file_path: str) -> TranscriptResult:
+        """执行识别过程，符合 Transcriber 接口"""
+        try:
+            logger.info(f"开始处理文件: {file_path}")
+            
+            # 上传文件
+            logger.info("正在上传文件...")
+            self._upload(file_path)
+            
+            # 创建任务
+            logger.info("提交转录任务...")
+            self._create_task()
+            
+            # 轮询检查任务状态
+            logger.info("等待转录结果...")
+            task_resp = None
+            max_retries = 500
+            for i in range(max_retries):
+                task_resp = self._query_result()
+                
+                if task_resp["state"] == 4:  # 完成状态
+                    break
+                elif task_resp["state"] == 3:  # 失败状态
+                    error_msg = f"B站ASR任务失败，状态码: {task_resp['state']}"
+                    logger.error(error_msg)
+                    raise Exception(error_msg)
+                    
+                # 每隔一段时间打印进度
+                if i % 10 == 0:
+                    logger.info(f"转录进行中... {i}/{max_retries}")
+                    
+                time.sleep(1)
+                
+            if not task_resp or task_resp["state"] != 4:
+                error_msg = f"B站ASR任务未能完成，状态: {task_resp.get('state') if task_resp else 'Unknown'}"
+                logger.error(error_msg)
+                raise Exception(error_msg)
+                
+            # 解析结果
+            logger.info("转录成功，处理结果...")
+            result_json = json.loads(task_resp["result"])
+            
+            # 提取分段数据
+            segments = []
+            full_text = ""
+            
+            for u in result_json.get("utterances", []):
+                text = u.get("transcript", "").strip()
+                # B站ASR返回的时间戳是毫秒，需要转换为秒
+                start_time = float(u.get("start_time", 0)) / 1000.0
+                end_time = float(u.get("end_time", 0)) / 1000.0
+                
+                full_text += text + " "
+                segments.append(TranscriptSegment(
+                    start=start_time,
+                    end=end_time,
+                    text=text
+                ))
+            
+            # 创建结果对象
+            result = TranscriptResult(
+                language=result_json.get("language", "zh"),
+                full_text=full_text.strip(),
+                segments=segments,
+                raw=result_json
+            )
+            
+            # 触发完成事件
+            self.on_finish(file_path, result)
+            
+            return result
+            
+        except Exception as e:
+            logger.error(f"B站ASR处理失败: {str(e)}")
+            raise
+
+    def on_finish(self, video_path: str, result: TranscriptResult) -> None:
+        """转录完成的回调"""
+        logger.info(f"B站ASR转写完成: {video_path}")
+        transcription_finished.send({
+            "file_path": video_path,
+        })

backend/app/transcriber/kuaishou.py

@@ -0,0 +1,115 @@
+import requests
+import logging
+import os
+from typing import Union, List, Dict, Optional
+
+from app.decorators.timeit import timeit
+from app.models.transcriber_model import TranscriptSegment, TranscriptResult
+from app.transcriber.base import Transcriber
+from app.utils.logger import get_logger
+from events import transcription_finished
+
+logger = get_logger(__name__)
+
+class KuaishouTranscriber(Transcriber):
+    """快手语音识别实现"""
+    
+    API_URL = "https://ai.kuaishou.com/api/effects/subtitle_generate"
+    
+    def __init__(self):
+        pass
+
+    def _load_file(self, file_path: str) -> bytes:
+        """读取文件内容"""
+        with open(file_path, 'rb') as f:
+            return f.read()
+
+    def _submit(self, file_path: str) -> dict:
+        """提交识别请求"""
+        try:
+            file_binary = self._load_file(file_path)
+            
+            payload = {
+                "typeId": "1"
+            }
+            
+            # 使用文件名作为上传文件名
+            file_name = os.path.basename(file_path)
+            files = [('file', (file_name, file_binary, 'audio/mpeg'))]
+            
+            logger.info(f"开始向快手API提交请求，文件: {file_name}")
+            response = requests.post(self.API_URL, data=payload, files=files, timeout=300)
+            response.raise_for_status()  # 检查HTTP错误
+            
+            result = response.json()
+            
+            # 检查快手API返回是否包含错误
+            if "data" not in result or result.get("code", 0) != 0:
+                error_msg = f"快手API返回错误: {result.get('message', '未知错误')}"
+                logger.error(error_msg)
+                raise Exception(error_msg)
+                
+            return result
+            
+        except requests.exceptions.RequestException as e:
+            error_msg = f"快手ASR请求网络错误: {str(e)}"
+            logger.error(error_msg)
+            raise
+        except Exception as e:
+            error_msg = f"快手ASR请求处理错误: {str(e)}"
+            logger.error(error_msg)
+            raise
+
+    @timeit
+    def transcript(self, file_path: str) -> TranscriptResult:
+        """执行转录过程，符合 Transcriber 接口"""
+        try:
+            logger.info(f"开始处理文件: {file_path}")
+            
+            # 提交请求并获取结果
+            logger.info("向快手API提交识别请求...")
+            result_data = self._submit(file_path)
+            
+            logger.info("请求成功，处理结果...")
+            
+            # 提取分段数据
+            segments = []
+            full_text = ""
+            
+            # 解析快手API返回的文本段
+            texts = result_data.get('data', {}).get('text', [])
+            for u in texts:
+                text = u.get('text', '').strip()
+                start_time = float(u.get('start_time', 0))
+                end_time = float(u.get('end_time', 0))
+                
+                full_text += text + " "
+                segments.append(TranscriptSegment(
+                    start=start_time,
+                    end=end_time,
+                    text=text
+                ))
+            
+            # 创建结果对象
+            result = TranscriptResult(
+                language="zh",  # 快手API可能不返回语言信息，默认为中文
+                full_text=full_text.strip(),
+                segments=segments,
+                raw=result_data
+            )
+            
+            # 触发完成事件
+            self.on_finish(file_path, result)
+            
+            return result
+            
+        except Exception as e:
+            logger.error(f"快手ASR处理失败: {str(e)}")
+            raise
+
+    def on_finish(self, video_path: str, result: TranscriptResult) -> None:
+        """转录完成的回调"""
+        logger.info(f"快手ASR转写完成: {video_path}")
+        transcription_finished.send({
+            "file_path": video_path,
+        })

backend/app/transcriber/transcriber_provider.py

@@ -1,19 +1,74 @@
 from app.transcriber.whisper import WhisperTranscriber
+from app.transcriber.bcut import BcutTranscriber
+from app.transcriber.kuaishou import KuaishouTranscriber
 from app.utils.logger import get_logger
 logger = get_logger(__name__)
 
-logger.info('实例化transcriber')
-# TODO:后面需要加入逻辑选择
-_transcriber = None
+logger.info('初始化转录服务提供器')
 
-def get_transcriber(model_size="base", device="cuda"):
-    global _transcriber
+# 维护各种转录器的单例实例
+_transcribers = {
+    'whisper': None,
+    'bcut': None,
+    'kuaishou': None
+}
 
-    if _transcriber is None:
-        logger.info('不存在 transcriber ，开始实例化transcriber。')
+def get_whisper_transcriber(model_size="base", device="cuda"):
+    """获取 Whisper 转录器实例"""
+    if _transcribers['whisper'] is None:
+        logger.info(f'创建 Whisper 转录器实例，参数：{model_size}, {device}')
         try:
-            _transcriber = WhisperTranscriber(model_size=model_size, device=device)
-            logger.info(f'实例化transcriber成功。参数：{model_size}, {device} ')
+            _transcribers['whisper'] = WhisperTranscriber(model_size=model_size, device=device)
+            logger.info('Whisper 转录器创建成功')
         except Exception as e:
-            logger.error(f"实例化transcriber失败，请检查是否安装whisper。{e}")
-    return _transcriber
+            logger.error(f"Whisper 转录器创建失败: {e}")
+            raise
+    return _transcribers['whisper']
+
+def get_bcut_transcriber():
+    """获取 Bcut 转录器实例"""
+    if _transcribers['bcut'] is None:
+        logger.info('创建 Bcut 转录器实例')
+        try:
+            _transcribers['bcut'] = BcutTranscriber()
+            logger.info('Bcut 转录器创建成功')
+        except Exception as e:
+            logger.error(f"Bcut 转录器创建失败: {e}")
+            raise
+    return _transcribers['bcut']
+
+def get_kuaishou_transcriber():
+    """获取快手转录器实例"""
+    if _transcribers['kuaishou'] is None:
+        logger.info('创建快手转录器实例')
+        try:
+            _transcribers['kuaishou'] = KuaishouTranscriber()
+            logger.info('快手转录器创建成功')
+        except Exception as e:
+            logger.error(f"快手转录器创建失败: {e}")
+            raise
+    return _transcribers['kuaishou']
+
+def get_transcriber(transcriber_type="whisper", model_size="base", device="cuda"):
+    """
+    获取指定类型的转录器实例
+    
+    参数:
+        transcriber_type: 转录器类型，支持 "whisper", "bcut", "kuaishou"
+        model_size: 模型大小，whisper 特有参数
+        device: 设备类型，whisper 特有参数
+    
+    返回:
+        对应类型的转录器实例
+    """
+    logger.info(f'获取转录器，类型: {transcriber_type}')
+    
+    if transcriber_type == "whisper":
+        return get_whisper_transcriber(model_size, device)
+    elif transcriber_type == "bcut":
+        return get_bcut_transcriber()
+    elif transcriber_type == "kuaishou":
+        return get_kuaishou_transcriber()
+    else:
+        logger.warning(f'未知转录器类型 "{transcriber_type}"，使用默认 whisper')
+        return get_whisper_transcriber(model_size, device)