feat(engine): 添加GLM-ASR语音识别引擎支持

- 新增GLM-ASR云端语音识别引擎实现
- 扩展配置界面添加GLM相关参数设置
- Ollama支持自定义域名和Apikey以支持云端和其他LLM
- 修改音频处理逻辑以支持新引擎
- 更新依赖项和构建配置
- 修复Ollama翻译功能相关问题

engine/audio2text/__init__.py

@@ -1,3 +1,4 @@
 from .gummy import GummyRecognizer
 from .vosk import VoskRecognizer
-from .sosv import SosvRecognizer
+from .sosv import SosvRecognizer
+from .glm import GlmRecognizer

engine/audio2text/glm.py

@@ -0,0 +1,163 @@
+import threading
+import io
+import wave
+import struct
+import math
+import audioop
+import requests
+from datetime import datetime
+
+from utils import shared_data
+from utils import stdout_cmd, stdout_obj, google_translate, ollama_translate
+
+class GlmRecognizer:
+    """
+    使用 GLM-ASR 引擎处理音频数据，并在标准输出中输出 Auto Caption 软件可读取的 JSON 字符串数据
+
+    初始化参数：
+        url: GLM-ASR API URL
+        model: GLM-ASR 模型名称
+        api_key: GLM-ASR API Key
+        source: 源语言
+        target: 目标语言
+        trans_model: 翻译模型名称
+        ollama_name: Ollama 模型名称
+    """
+    def __init__(self, url: str, model: str, api_key: str, source: str, target: str | None, trans_model: str, ollama_name: str, ollama_url: str = '', ollama_api_key: str = ''):
+        self.url = url
+        self.model = model
+        self.api_key = api_key
+        self.source = source
+        self.target = target
+        if trans_model == 'google':
+            self.trans_func = google_translate
+        else:
+            self.trans_func = ollama_translate
+        self.ollama_name = ollama_name
+        self.ollama_url = ollama_url
+        self.ollama_api_key = ollama_api_key
+        
+        self.audio_buffer = []
+        self.is_speech = False
+        self.silence_frames = 0
+        self.speech_start_time = None
+        self.time_str = ''
+        self.cur_id = 0
+        
+        # VAD settings (假设 16k 16bit, chunk size 1024 or similar)
+        # 16bit = 2 bytes per sample.
+        # RMS threshold needs tuning. 500 is a conservative guess for silence.
+        self.threshold = 500 
+        self.silence_limit = 15 # frames (approx 0.5-1s depending on chunk size)
+        self.min_speech_frames = 10 # frames
+
+    def start(self):
+        """启动 GLM 引擎"""
+        stdout_cmd('info', 'GLM-ASR recognizer started.')
+
+    def stop(self):
+        """停止 GLM 引擎"""
+        stdout_cmd('info', 'GLM-ASR recognizer stopped.')
+
+    def process_audio(self, chunk):
+        # chunk is bytes (int16)
+        rms = audioop.rms(chunk, 2)
+        
+        if rms > self.threshold:
+            if not self.is_speech:
+                self.is_speech = True
+                self.time_str = datetime.now().strftime('%H:%M:%S.%f')[:-3]
+                self.audio_buffer = []
+            self.audio_buffer.append(chunk)
+            self.silence_frames = 0
+        else:
+            if self.is_speech:
+                self.audio_buffer.append(chunk)
+                self.silence_frames += 1
+                if self.silence_frames > self.silence_limit:
+                    # Speech ended
+                    if len(self.audio_buffer) > self.min_speech_frames:
+                        self.recognize(self.audio_buffer, self.time_str)
+                    self.is_speech = False
+                    self.audio_buffer = []
+                    self.silence_frames = 0
+    
+    def recognize(self, audio_frames, time_s):
+        audio_bytes = b''.join(audio_frames)
+        
+        wav_io = io.BytesIO()
+        with wave.open(wav_io, 'wb') as wav_file:
+            wav_file.setnchannels(1)
+            wav_file.setsampwidth(2)
+            wav_file.setframerate(16000)
+            wav_file.writeframes(audio_bytes)
+        wav_io.seek(0)
+        
+        threading.Thread(
+            target=self._do_request, 
+            args=(wav_io.read(), time_s, self.cur_id)
+        ).start()
+        self.cur_id += 1
+
+    def _do_request(self, audio_content, time_s, index):
+        try:
+            files = {
+                'file': ('audio.wav', audio_content, 'audio/wav')
+            }
+            data = {
+                'model': self.model,
+                'stream': 'false'
+            }
+            headers = {
+                'Authorization': f'Bearer {self.api_key}'
+            }
+            
+            response = requests.post(self.url, headers=headers, data=data, files=files, timeout=15)
+            
+            if response.status_code == 200:
+                res_json = response.json()
+                text = res_json.get('text', '')
+                if text:
+                    self.output_caption(text, time_s, index)
+            else:
+                try:
+                    err_msg = response.json()
+                    stdout_cmd('error', f"GLM API Error: {err_msg}")
+                except:
+                    stdout_cmd('error', f"GLM API Error: {response.text}")
+                
+        except Exception as e:
+            stdout_cmd('error', f"GLM Request Failed: {str(e)}")
+
+    def output_caption(self, text, time_s, index):
+        caption = {
+            'command': 'caption',
+            'index': index,
+            'time_s': time_s,
+            'time_t': datetime.now().strftime('%H:%M:%S.%f')[:-3],
+            'text': text,
+            'translation': ''
+        }
+        
+        if self.target:
+             if self.trans_func == ollama_translate:
+                 th = threading.Thread(
+                    target=self.trans_func,
+                    args=(self.ollama_name, self.target, caption['text'], time_s, self.ollama_url, self.ollama_api_key),
+                    daemon=True
+                )
+             else:
+                 th = threading.Thread(
+                    target=self.trans_func,
+                    args=(self.ollama_name, self.target, caption['text'], time_s),
+                    daemon=True
+                )
+             th.start()
+        
+        stdout_obj(caption)
+
+    def translate(self):
+        global shared_data
+        while shared_data.status == 'running':
+            chunk = shared_data.chunk_queue.get()
+            self.process_audio(chunk)

engine/audio2text/sosv.py

@@ -29,7 +29,7 @@ class SosvRecognizer:
         trans_model: 翻译模型名称
         ollama_name: Ollama 模型名称
     """
-    def __init__(self, model_path: str, source: str, target: str | None, trans_model: str, ollama_name: str):
+    def __init__(self, model_path: str, source: str, target: str | None, trans_model: str, ollama_name: str, ollama_url: str = '', ollama_api_key: str = ''):
         if model_path.startswith('"'):
             model_path = model_path[1:]
         if model_path.endswith('"'):
@@ -45,6 +45,8 @@ class SosvRecognizer:
         else:
             self.trans_func = ollama_translate
         self.ollama_name = ollama_name
+        self.ollama_url = ollama_url
+        self.ollama_api_key = ollama_api_key
         self.time_str = ''
         self.cur_id = 0
         self.prev_content = ''
@@ -152,7 +154,7 @@ class SosvRecognizer:
                 if self.target:
                     th = threading.Thread(
                         target=self.trans_func,
-                        args=(self.ollama_name, self.target, caption['text'], self.time_str),
+                        args=(self.ollama_name, self.target, caption['text'], self.time_str, self.ollama_url, self.ollama_api_key),
                         daemon=True
                     )
                     th.start()    

engine/audio2text/vosk.py

@@ -18,7 +18,7 @@ class VoskRecognizer:
         trans_model: 翻译模型名称
         ollama_name: Ollama 模型名称
     """
-    def __init__(self, model_path: str, target: str | None, trans_model: str, ollama_name: str):
+    def __init__(self, model_path: str, target: str | None, trans_model: str, ollama_name: str, ollama_url: str = '', ollama_api_key: str = ''):
         SetLogLevel(-1)
         if model_path.startswith('"'):
             model_path = model_path[1:]
@@ -31,6 +31,8 @@ class VoskRecognizer:
         else:
             self.trans_func = ollama_translate
         self.ollama_name = ollama_name
+        self.ollama_url = ollama_url
+        self.ollama_api_key = ollama_api_key
         self.time_str = ''
         self.cur_id = 0
         self.prev_content = ''
@@ -66,7 +68,7 @@ class VoskRecognizer:
             if self.target:
                 th = threading.Thread(
                     target=self.trans_func,
-                    args=(self.ollama_name, self.target, caption['text'], self.time_str),
+                    args=(self.ollama_name, self.target, caption['text'], self.time_str, self.ollama_url, self.ollama_api_key),
                     daemon=True
                 )
                 th.start()