Update app.py

app.py

@@ -1,6 +1,8 @@
 import io
 import os
 
+import torch
+
 os.environ['VLLM_USE_V1'] = '0'
 os.environ['VLLM_WORKER_MULTIPROC_METHOD'] = 'spawn'
 from argparse import ArgumentParser
@@ -45,22 +47,33 @@ OSS_ACCESS_KEY_ID = os.environ['OSS_ACCESS_KEY_ID']
 OSS_ACCESS_KEY_SECRET = os.environ['OSS_ACCESS_KEY_SECRET']
 OSS_CONFIG_PATH = {}
 
+
 class OSSReader:
+
     def __init__(self):
         # 初始化OSS配置
         self.bucket2object = {
-            bucket_name: oss2.Bucket(oss2.Auth(OSS_ACCESS_KEY_ID, OSS_ACCESS_KEY_SECRET), endpoint, bucket_name),
+            bucket_name:
+            oss2.Bucket(oss2.Auth(OSS_ACCESS_KEY_ID, OSS_ACCESS_KEY_SECRET),
+                        endpoint, bucket_name),
         }
-        print(f"Loaded OSS config from: {OSS_CONFIG_PATH}\nSupported buckets: {list(self.bucket2object.keys())}")
-    
+        print(
+            f"Loaded OSS config from: {OSS_CONFIG_PATH}\nSupported buckets: {list(self.bucket2object.keys())}"
+        )
+
     def _parse_oss_path(self, oss_path):
         """解析oss路径，返回bucket名称和实际路径"""
         assert oss_path.startswith("oss://"), f"Invalid oss path {oss_path}"
         bucket_name, object_key = oss_path.split("oss://")[-1].split("/", 1)
         object_key = f"studio-temp/Qwen3-Omni-Demo/{object_key}"
         return bucket_name, object_key
-    
-    def _retry_operation(self, func, *args, retries=OSS_RETRY, delay=OSS_RETRY, **kwargs):
+
+    def _retry_operation(self,
+                         func,
+                         *args,
+                         retries=OSS_RETRY,
+                         delay=OSS_RETRY,
+                         **kwargs):
         """通用的重试机制"""
         for _ in range(retries):
             try:
@@ -70,23 +83,30 @@ class OSSReader:
                 if _ == retries - 1:
                     raise e
                 time.sleep(delay)
-    
+
     def get_public_url(self, oss_path):
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        url = self._retry_operation(self.bucket2object[bucket_name].sign_url, 'GET', object_key, 600,
-                                    slash_safe=True).replace('http://', 'https://')
+        url = self._retry_operation(self.bucket2object[bucket_name].sign_url,
+                                    'GET',
+                                    object_key,
+                                    600,
+                                    slash_safe=True).replace(
+                                        'http://', 'https://')
         return url.replace("-internal", '')
-    
+
     def file_exists(self, oss_path):
         """判断文件是否存在"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        return self._retry_operation(self.bucket2object[bucket_name].object_exists, object_key)
-    
+        return self._retry_operation(
+            self.bucket2object[bucket_name].object_exists, object_key)
+
     def download_file(self, oss_path, local_path):
         """下载OSS上的文件到本地"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        self._retry_operation(self.bucket2object[bucket_name].get_object_to_file, object_key, local_path)
-    
+        self._retry_operation(
+            self.bucket2object[bucket_name].get_object_to_file, object_key,
+            local_path)
+
     def upload_file(self, local_path, oss_path, overwrite=True):
         """上传本地文件到OSS"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
@@ -101,28 +121,30 @@ class OSSReader:
         try:
             self._retry_operation(
                 self.bucket2object[bucket_name].put_object_from_file,
-                object_key,
-                local_path
-            )
+                object_key, local_path)
             return True
         except Exception as e:
             print(f"Upload failed: {str(e)}")
             return False
-    
-    def upload_audio_from_array(self, data, sample_rate, oss_path, overwrite=True):
+
+    def upload_audio_from_array(self,
+                                data,
+                                sample_rate,
+                                oss_path,
+                                overwrite=True):
         """将音频数据保存为WAV格式并上传到OSS"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        
+
         # 检查目标文件是否存在（当overwrite=False时）
         if not overwrite and self.file_exists(oss_path):
             print(f"File {oss_path} already exists, skip upload")
             return False
-        
+
         try:
             # 使用 BytesIO 在内存中生成 WAV 格式数据
             import wave
             from io import BytesIO
-            
+
             byte_io = BytesIO()
             with wave.open(byte_io, 'wb') as wf:
                 wf.setnchannels(1)  # 单声道
@@ -132,49 +154,51 @@ class OSSReader:
                 data_int16 = np.clip(data, -1, 1) * 32767
                 data_int16 = data_int16.astype(np.int16)
                 wf.writeframes(data_int16.tobytes())
-            
+
             # 上传到 OSS
-            self._retry_operation(
-                self.bucket2object[bucket_name].put_object,
-                object_key,
-                byte_io.getvalue()
-            )
+            self._retry_operation(self.bucket2object[bucket_name].put_object,
+                                  object_key, byte_io.getvalue())
             return True
         except Exception as e:
             print(f"Upload failed: {str(e)}")
             return False
-    
+
     def get_object(self, oss_path):
         """读取OSS上的音频文件，返回音频数据和采样率"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        return self._retry_operation(self.bucket2object[bucket_name].get_object, object_key)
-    
+        return self._retry_operation(
+            self.bucket2object[bucket_name].get_object, object_key)
+
     def read_text_file(self, oss_path):
         """读取OSS上的文本文件"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        result = self._retry_operation(self.bucket2object[bucket_name].get_object, object_key)
+        result = self._retry_operation(
+            self.bucket2object[bucket_name].get_object, object_key)
         return result.read().decode('utf-8')
-    
+
     def read_audio_file(self, oss_path):
         """读取OSS上的音频文件，返回音频数据和采样率"""
         bucket_name, object_key = self._parse_oss_path(oss_path)
-        result = self._retry_operation(self.bucket2object[bucket_name].get_object, object_key)
+        result = self._retry_operation(
+            self.bucket2object[bucket_name].get_object, object_key)
         # ffmpeg 命令：从标准输入读取音频并输出PCM浮点数据
         command = [
             'ffmpeg',
-            '-i', '-',  # 输入来自管道
-            '-ar', str(WAV_SAMPLE_RATE),  # 输出采样率
-            '-ac', '1',  # 单声道
-            '-f', 'f32le',  # 指定输出格式
+            '-i',
+            '-',  # 输入来自管道
+            '-ar',
+            str(WAV_SAMPLE_RATE),  # 输出采样率
+            '-ac',
+            '1',  # 单声道
+            '-f',
+            'f32le',  # 指定输出格式
             '-'  # 输出到管道
         ]
         # 启动ffmpeg子进程
-        process = subprocess.Popen(
-            command,
-            stdin=subprocess.PIPE,
-            stdout=subprocess.PIPE,
-            stderr=subprocess.PIPE
-        )
+        process = subprocess.Popen(command,
+                                   stdin=subprocess.PIPE,
+                                   stdout=subprocess.PIPE,
+                                   stderr=subprocess.PIPE)
         # 写入音频字节并获取输出
         stdout_data, stderr_data = process.communicate(input=result.read())
         if process.returncode != 0:
@@ -182,20 +206,27 @@ class OSSReader:
         # 将PCM数据转换为numpy数组
         wav_data = np.frombuffer(stdout_data, dtype=np.float32)
         return wav_data, WAV_SAMPLE_RATE
-    
+
     def get_wav_duration_from_bin(self, oss_path):
         oss_bin_path = oss_path + ".ar16k.bin"
         bucket_name, object_key = self._parse_oss_path(oss_bin_path)
-        metadata = self._retry_operation(self.bucket2object[bucket_name].get_object_meta, object_key)
+        metadata = self._retry_operation(
+            self.bucket2object[bucket_name].get_object_meta, object_key)
         duration = float(metadata.headers['Content-Length']) / (16000 * 2)
         return duration
-    
-    def read_wavdata_from_oss(self, oss_path, start=None, end=None, force_bin=False):
+
+    def read_wavdata_from_oss(self,
+                              oss_path,
+                              start=None,
+                              end=None,
+                              force_bin=False):
         bucket_name, object_key = self._parse_oss_path(oss_path)
         oss_bin_key = object_key + ".ar16k.bin"
         if start is None or end is None:
             if self.bucket2object[bucket_name].object_exists(oss_bin_key):
-                wav_data = self._retry_operation(self.bucket2object[bucket_name].get_object, oss_bin_key).read()
+                wav_data = self._retry_operation(
+                    self.bucket2object[bucket_name].get_object,
+                    oss_bin_key).read()
             elif not force_bin:
                 wav_data, _ = self.read_audio_file(oss_path)
             else:
@@ -208,49 +239,58 @@ class OSSReader:
             if not (end_offset - start_offset) % 2:
                 end_offset -= 1
             # 使用范围请求只获取指定字节范围的数据
-            wav_data = self._retry_operation(self.bucket2object[bucket_name].get_object,
-                                             oss_bin_key,
-                                             byte_range=(start_offset, end_offset),
-                                             headers={'x-oss-range-behavior': 'standard'}).read()
+            wav_data = self._retry_operation(
+                self.bucket2object[bucket_name].get_object,
+                oss_bin_key,
+                byte_range=(start_offset, end_offset),
+                headers={
+                    'x-oss-range-behavior': 'standard'
+                }).read()
         if not isinstance(wav_data, np.ndarray):
             wav_data = np.frombuffer(wav_data, np.int16).flatten() / 32768.0
         return wav_data.astype(np.float32)
-    
+
     def _list_files_by_suffix(self, oss_dir, suffix):
         """递归搜索以某个后缀结尾的所有文件，返回所有文件的OSS路径列表"""
         bucket_name, dir_key = self._parse_oss_path(oss_dir)
         file_list = []
-        
+
         def _recursive_list(prefix):
-            for obj in oss2.ObjectIterator(self.bucket2object[bucket_name], prefix=prefix, delimiter='/'):
+            for obj in oss2.ObjectIterator(self.bucket2object[bucket_name],
+                                           prefix=prefix,
+                                           delimiter='/'):
                 if obj.is_prefix():  # 如果是目录，递归搜索
                     _recursive_list(obj.key)
                 elif obj.key.endswith(suffix):
                     file_list.append(f"oss://{bucket_name}/{obj.key}")
-        
+
         _recursive_list(dir_key)
         return file_list
-    
+
     def list_files_by_suffix(self, oss_dir, suffix):
-        return self._retry_operation(self._list_files_by_suffix, oss_dir, suffix)
-    
+        return self._retry_operation(self._list_files_by_suffix, oss_dir,
+                                     suffix)
+
     def _list_files_by_prefix(self, oss_dir, file_prefix):
         """递归搜索以某个后缀结尾的所有文件，返回所有文件的OSS路径列表"""
         bucket_name, dir_key = self._parse_oss_path(oss_dir)
         file_list = []
-        
+
         def _recursive_list(prefix):
-            for obj in oss2.ObjectIterator(self.bucket2object[bucket_name], prefix=prefix, delimiter='/'):
+            for obj in oss2.ObjectIterator(self.bucket2object[bucket_name],
+                                           prefix=prefix,
+                                           delimiter='/'):
                 if obj.is_prefix():  # 如果是目录，递归搜索
                     _recursive_list(obj.key)
                 elif os.path.basename(obj.key).startswith(file_prefix):
                     file_list.append(f"oss://{bucket_name}/{obj.key}")
-        
+
         _recursive_list(dir_key)
         return file_list
-    
+
     def list_files_by_prefix(self, oss_dir, file_prefix):
-        return self._retry_operation(self._list_files_by_prefix, oss_dir, file_prefix)
+        return self._retry_operation(self._list_files_by_prefix, oss_dir,
+                                     file_prefix)
 
 
 def encode_base64(base64_path):
@@ -263,13 +303,13 @@ def _load_model_processor(args):
         device_map = 'cpu'
     else:
         device_map = 'auto'
-    
+
     model = OpenAI(
         # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：api_key="sk-xxx",
         api_key=API_KEY,
         base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
     )
-    
+
     return model, None
 
 
@@ -279,90 +319,150 @@ oss_reader = OSSReader()
 def _launch_demo(args, model, processor):
     # Voice settings
     VOICE_OPTIONS = {
-        "芊悦 Cherry": "Cherry",
-        "晨煦 Ethan": "Ethan",
-        "詹妮弗 Jennifer": "Jennifer",
-        "甜茶 Ryan": "Ryan",
-        "卡捷琳娜 Katerina": "Katerina",
-        "不吃鱼 Nofish": "Nofish",
-        "墨讲师 Elias": "Elias",
-        "南京-老李 Li": "Li",
-        "陕西-秦川 Marcus": "Marcus",
-        "闽南-阿杰 Roy": "Roy",
-        "天津-李彼得 Peter": "Peter",
-        "四川-程川 Eric": "Eric",
-        "粤语-阿强 Rocky": "Rocky",
-        "粤语-阿清 Kiki": "Kiki",
-        "四川-晴儿 Sunny": "Sunny",
-        "上海-阿珍 Jada": "Jada",
-        "北京-晓东 Dylan": "Dylan",
+        "Cherry / 芊悦": "Cherry",
+        "Serena / 苏瑶": "Serena",
+        "Ethan / 晨煦": "Ethan",
+        "Chelsie / 千雪": "Chelsie",
+        "Momo / 茉兔": "Momo",
+        "Vivian / 十三": "Vivian",
+        "Moon / 月白": "Moon",
+        "Maia / 四月": "Maia",
+        "Kai / 凯": "Kai",
+        "Nofish / 不吃鱼": "Nofish",
+        "Bella / 萌宝": "Bella",
+        "Jennifer / 詹妮弗": "Jennifer",
+        "Ryan / 甜茶": "Ryan",
+        "Katerina / 卡捷琳娜": "Katerina",
+        "Aiden / 艾登": "Aiden",
+        "Bodega / 西班牙语-博德加": "Bodega",
+        "Alek / 俄语-阿列克": "Alek",
+        "Dolce / 意大利语-多尔切": "Dolce",
+        "Sohee / 韩语-素熙": "Sohee",
+        "Ono Anna / 日语-小野杏": "Ono Anna",
+        "Lenn / 德语-莱恩": "Lenn",
+        "Sonrisa / 西班牙语拉美-索尼莎": "Sonrisa",
+        "Emilien / 法语-埃米尔安": "Emilien",
+        "Andre / 葡萄牙语欧-安德雷": "Andre",
+        "Radio Gol / 葡萄牙语巴-拉���奥·戈尔": "Radio Gol",
+        "Eldric Sage / 精品百人-沧明子": "Eldric Sage",
+        "Mia / 精品百人-乖小妹": "Mia",
+        "Mochi / 精品百人-沙小弥": "Mochi",
+        "Bellona / 精品百人-燕铮莺": "Bellona",
+        "Vincent / 精品百人-田叔": "Vincent",
+        "Bunny / 精品百人-萌小姬": "Bunny",
+        "Neil / 精品百人-阿闻": "Neil",
+        "Elias / 墨讲师": "Elias",
+        "Arthur / 精品百人-徐大爷": "Arthur",
+        "Nini / 精品百人-邻家妹妹": "Nini",
+        "Ebona / 精品百人-诡婆婆": "Ebona",
+        "Seren / 精品百人-小婉": "Seren",
+        "Pip / 精品百人-调皮小新": "Pip",
+        "Stella / 精品百人-美少女阿月": "Stella",
+        "Li / 南京-老李": "Li",
+        "Marcus / 陕西-秦川": "Marcus",
+        "Roy / 闽南-阿杰": "Roy",
+        "Peter / 天津-李彼得": "Peter",
+        "Eric / 四川-程川": "Eric",
+        "Rocky / 粤语-阿强": "Rocky",
+        "Kiki / 粤语-阿清": "Kiki",
+        "Sunny / 四川-晴儿": "Sunny",
+        "Jada / 上海-阿珍": "Jada",
+        "Dylan / 北京-晓东": "Dylan",
     }
     DEFAULT_VOICE = '芊悦 Cherry'
-    
+
     default_system_prompt = ''
-    
+
     language = args.ui_language
-    
+
     def get_text(text: str, cn_text: str):
         if language == 'en':
             return text
         if language == 'zh':
             return cn_text
         return text
-    
+
     def to_mp4(path):
         import subprocess
         if path and path.endswith(".webm"):
             mp4_path = path.replace(".webm", ".mp4")
-            subprocess.run([
-                "ffmpeg", "-y",
-                "-i", path,
-                "-c:v", "libx264",  # 使用 H.264
-                "-preset", "ultrafast",  # 最快速度！
-                "-tune", "fastdecode",  # 优化快速解码（利于后续处理）
-                "-pix_fmt", "yuv420p",  # 兼容性像素格式
-                "-c:a", "aac",  # 音频编码
-                "-b:a", "128k",  # 可选：限制音频比特率加速
-                "-threads", "0",  # 使用所有线程
-                "-f", "mp4",
-                mp4_path
-            ], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+            subprocess.run(
+                [
+                    "ffmpeg",
+                    "-y",
+                    "-i",
+                    path,
+                    "-c:v",
+                    "libx264",  # 使用 H.264
+                    "-preset",
+                    "ultrafast",  # 最快速度！
+                    "-tune",
+                    "fastdecode",  # 优化快速解码（利于后续处理）
+                    "-pix_fmt",
+                    "yuv420p",  # 兼容性像素格式
+                    "-c:a",
+                    "aac",  # 音频编码
+                    "-b:a",
+                    "128k",  # 可选：限制音频比特率加速
+                    "-threads",
+                    "0",  # 使用所有线程
+                    "-f",
+                    "mp4",
+                    mp4_path
+                ],
+                check=True,
+                stdout=subprocess.DEVNULL,
+                stderr=subprocess.DEVNULL)
             return mp4_path
         return path  # 已经是 mp4 或 None
-    
+
     def format_history(history: list, system_prompt: str):
         print(history)
         messages = []
         if system_prompt != "":
-            messages.append({"role": "system", "content": [{"type": "text", "text": system_prompt}]})
-        
+            messages.append({
+                "role":
+                "system",
+                "content": [{
+                    "type": "text",
+                    "text": system_prompt
+                }]
+            })
+
         current_user_content = []
-        
+
         for item in history:
             role = item['role']
             content = item['content']
-            
+
             if role != "user":
                 if current_user_content:
-                    messages.append({"role": "user", "content": current_user_content})
+                    messages.append({
+                        "role": "user",
+                        "content": current_user_content
+                    })
                     current_user_content = []
-                
+
                 if isinstance(content, str):
                     messages.append({
-                        "role": role,
-                        "content": [{"type": "text", "text": content}]
+                        "role":
+                        role,
+                        "content": [{
+                            "type": "text",
+                            "text": content
+                        }]
                     })
                 else:
                     pass
                 continue
-            
+
             if isinstance(content, str):
                 current_user_content.append({"type": "text", "text": content})
             elif isinstance(content, (list, tuple)):
                 for file_path in content:
                     mime_type = client_utils.get_mimetype(file_path)
                     media_type = None
-                    
+
                     if mime_type.startswith("image"):
                         media_type = "image_url"
                     elif mime_type.startswith("video"):
@@ -370,7 +470,7 @@ def _launch_demo(args, model, processor):
                         file_path = to_mp4(file_path)
                     elif mime_type.startswith("audio"):
                         media_type = "input_audio"
-                    
+
                     if media_type:
                         # base64_media = encode_base64(file_path)
                         import uuid
@@ -405,36 +505,47 @@ def _launch_demo(args, model, processor):
                             "type": "text",
                             "text": file_path
                         })
-        
+
         if current_user_content:
             media_items = []
             text_items = []
-            
+
             for item in current_user_content:
                 if item["type"] == "text":
                     text_items.append(item)
                 else:
                     media_items.append(item)
-            
+
             messages.append({
                 "role": "user",
                 "content": media_items + text_items
             })
-        
+
         return messages
-    
-    def predict(messages, voice_choice=DEFAULT_VOICE, temperature=0.7, top_p=0.8, top_k=20, return_audio=False,
+
+    def predict(messages,
+                voice_choice=DEFAULT_VOICE,
+                temperature=0.7,
+                top_p=0.8,
+                top_k=20,
+                return_audio=False,
                 enable_thinking=False):
         # print('predict history: ', messages)
         if enable_thinking:
-            return_audio=False
+            return_audio = False
         if return_audio:
             completion = model.chat.completions.create(
-                model="qwen3-omni-flash",
+                model="qwen3-omni-flash-2025-12-01",
                 messages=messages,
                 modalities=["text", "audio"],
-                audio={"voice": VOICE_OPTIONS[voice_choice], "format": "wav"},
-                extra_body={'enable_thinking': False, "top_k": top_k},
+                audio={
+                    "voice": VOICE_OPTIONS[voice_choice],
+                    "format": "wav"
+                },
+                extra_body={
+                    'enable_thinking': False,
+                    "top_k": top_k
+                },
                 stream_options={"include_usage": True},
                 stream=True,
                 temperature=temperature,
@@ -442,10 +553,13 @@ def _launch_demo(args, model, processor):
             )
         else:
             completion = model.chat.completions.create(
-                model="qwen3-omni-flash",
+                model="qwen3-omni-flash-2025-12-01",
                 messages=messages,
                 modalities=["text"],
-                extra_body={'enable_thinking': enable_thinking, "top_k": top_k},
+                extra_body={
+                    'enable_thinking': enable_thinking,
+                    "top_k": top_k
+                },
                 stream_options={"include_usage": True},
                 stream=True,
                 temperature=temperature,
@@ -463,14 +577,18 @@ def _launch_demo(args, model, processor):
                     try:
                         audio_string += chunk.choices[0].delta.audio["data"]
                     except Exception as e:
-                        output_text += chunk.choices[0].delta.audio["transcript"]
+                        output_text += chunk.choices[0].delta.audio[
+                            "transcript"]
                         yield {"type": "text", "data": output_text}
                 else:
                     delta = chunk.choices[0].delta
                     if enable_thinking:
-                        if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None:
+                        if hasattr(delta, "reasoning_content"
+                                   ) and delta.reasoning_content is not None:
                             if not is_answering:
-                                print(delta.reasoning_content, end="", flush=True)
+                                print(delta.reasoning_content,
+                                      end="",
+                                      flush=True)
                             reasoning_content += delta.reasoning_content
                             yield {"type": "text", "data": reasoning_content}
                         if hasattr(delta, "content") and delta.content:
@@ -478,17 +596,20 @@ def _launch_demo(args, model, processor):
                                 reasoning_content += "\n\n</think>\n\n"
                                 is_answering = True
                             answer_content += delta.content
-                            yield {"type": "text", "data": reasoning_content + answer_content}
+                            yield {
+                                "type": "text",
+                                "data": reasoning_content + answer_content
+                            }
                     else:
                         if hasattr(delta, "content") and delta.content:
                             output_text += chunk.choices[0].delta.content
                             yield {"type": "text", "data": output_text}
             else:
                 print(chunk.usage)
-        
+
         wav_bytes = base64.b64decode(audio_string)
         audio_np = np.frombuffer(wav_bytes, dtype=np.int16)
-        
+
         if audio_string != "":
             wav_io = io.BytesIO()
             sf.write(wav_io, audio_np, samplerate=24000, format="WAV")
@@ -497,8 +618,16 @@ def _launch_demo(args, model, processor):
             audio_path = processing_utils.save_bytes_to_cache(
                 wav_bytes, "audio.wav", cache_dir=demo.GRADIO_CACHE)
             yield {"type": "audio", "data": audio_path}
-    
-    def media_predict(audio, video, history, system_prompt, voice_choice, temperature, top_p, top_k, return_audio=False,
+
+    def media_predict(audio,
+                      video,
+                      history,
+                      system_prompt,
+                      voice_choice,
+                      temperature,
+                      top_p,
+                      top_k,
+                      return_audio=False,
                       enable_thinking=False):
         # First yield
         yield (
@@ -508,13 +637,13 @@ def _launch_demo(args, model, processor):
             gr.update(visible=False),  # submit_btn
             gr.update(visible=True),  # stop_btn
         )
-        
+
         files = [audio, video]
-        
+
         for f in files:
             if f:
-                history.append({"role": "user", "content": (f,)})
-        
+                history.append({"role": "user", "content": (f, )})
+
         yield (
             None,  # microphone
             None,  # webcam
@@ -522,13 +651,16 @@ def _launch_demo(args, model, processor):
             gr.update(visible=True),  # submit_btn
             gr.update(visible=False),  # stop_btn
         )
-        
-        formatted_history = format_history(history=history,
-                                           system_prompt=system_prompt, )
-        
+
+        formatted_history = format_history(
+            history=history,
+            system_prompt=system_prompt,
+        )
+
         history.append({"role": "assistant", "content": ""})
-        
-        for chunk in predict(formatted_history, voice_choice, temperature, top_p, top_k, return_audio, enable_thinking):
+
+        for chunk in predict(formatted_history, voice_choice, temperature,
+                             top_p, top_k, return_audio, enable_thinking):
             print('chunk', chunk)
             if chunk["type"] == "text":
                 history[-1]["content"] = chunk["data"]
@@ -544,7 +676,7 @@ def _launch_demo(args, model, processor):
                     "role": "assistant",
                     "content": gr.Audio(chunk["data"])
                 })
-        
+
         # Final yield
         yield (
             None,  # microphone
@@ -553,170 +685,259 @@ def _launch_demo(args, model, processor):
             gr.update(visible=True),  # submit_btn
             gr.update(visible=False),  # stop_btn
         )
-    
-    def chat_predict(text, audio, image, video, history, system_prompt, voice_choice, temperature, top_p, top_k,
-                     return_audio=False, enable_thinking=False):
-        
+
+    def chat_predict(text,
+                     audio,
+                     image,
+                     video,
+                     history,
+                     system_prompt,
+                     voice_choice,
+                     temperature,
+                     top_p,
+                     top_k,
+                     return_audio=False,
+                     enable_thinking=False):
+
         # Process audio input
         if audio:
-            history.append({"role": "user", "content": (audio,)})
-        
+            history.append({"role": "user", "content": (audio, )})
+
         # Process text input
         if text:
             history.append({"role": "user", "content": text})
-        
+
         # Process image input
         if image:
-            history.append({"role": "user", "content": (image,)})
-        
+            history.append({"role": "user", "content": (image, )})
+
         # Process video input
         if video:
-            history.append({"role": "user", "content": (video,)})
-        
+            history.append({"role": "user", "content": (video, )})
+
         formatted_history = format_history(history=history,
                                            system_prompt=system_prompt)
-        
+
         yield None, None, None, None, history
-        
+
         history.append({"role": "assistant", "content": ""})
-        for chunk in predict(formatted_history, voice_choice, temperature, top_p, top_k, return_audio, enable_thinking):
+        for chunk in predict(formatted_history, voice_choice, temperature,
+                             top_p, top_k, return_audio, enable_thinking):
             print('chat_predict chunk', chunk)
-            
+
             if chunk["type"] == "text":
                 history[-1]["content"] = chunk["data"]
-                yield gr.skip(), gr.skip(), gr.skip(), gr.skip(
-                ), history
+                yield gr.skip(), gr.skip(), gr.skip(), gr.skip(), history
             if chunk["type"] == "audio":
                 history.append({
                     "role": "assistant",
                     "content": gr.Audio(chunk["data"])
                 })
         yield gr.skip(), gr.skip(), gr.skip(), gr.skip(), history
-    
+
     # --- CORRECTED UI LAYOUT ---
-    with gr.Blocks(theme=gr.themes.Soft(font=[gr.themes.GoogleFont("Source Sans Pro"), "Arial", "sans-serif"]),
-                   css=".gradio-container {max-width: none !important;}") as demo:
+    with gr.Blocks(
+            theme=gr.themes.Soft(font=[
+                gr.themes.GoogleFont("Source Sans Pro"), "Arial", "sans-serif"
+            ]),
+            css=".gradio-container {max-width: none !important;}") as demo:
         gr.Markdown("# Qwen3-Omni Demo")
         gr.Markdown(
-            "**Instructions**: Interact with the model through text, audio, images, or video. Use the tabs to switch between Online and Offline chat modes.")
+            "**Instructions**: Interact with the model through text, audio, images, or video. Use the tabs to switch between Online and Offline chat modes."
+        )
         gr.Markdown(
             "**使用说明**：1️⃣ 点击音频录制按钮，或摄像头-录制按钮 2️⃣ 输入音频或者视频 3️⃣ 点击提交并等待模型的回答")
-        
+
         with gr.Row(equal_height=False):
             with gr.Column(scale=1):
                 gr.Markdown("### ⚙️ Parameters (参数)")
-                system_prompt_textbox = gr.Textbox(label="System Prompt", value=default_system_prompt, lines=4,
+                system_prompt_textbox = gr.Textbox(label="System Prompt",
+                                                   value=default_system_prompt,
+                                                   lines=4,
                                                    max_lines=8)
-                voice_choice = gr.Dropdown(label="Voice Choice", choices=VOICE_OPTIONS, value=DEFAULT_VOICE,
+                voice_choice = gr.Dropdown(label="Voice Choice",
+                                           choices=VOICE_OPTIONS,
+                                           value=DEFAULT_VOICE,
                                            visible=True)
-                return_audio = gr.Checkbox(
-                    label="Return Audio （返回语音）",
-                    value=True,
-                    interactive=True,
-                    elem_classes="checkbox-large"
-                )
-                enable_thinking = gr.Checkbox(
-                    label="Enable Thinking （启用思维链）",
-                    value=False,
-                    interactive=True,
-                    elem_classes="checkbox-large"
-                )
-                temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=2.0, value=0.6, step=0.1)
-                top_p = gr.Slider(label="Top P", minimum=0.05, maximum=1.0, value=0.95, step=0.05)
-                top_k = gr.Slider(label="Top K", minimum=1, maximum=100, value=20, step=1)
-            
+                return_audio = gr.Checkbox(label="Return Audio （返回语音）",
+                                           value=True,
+                                           interactive=True,
+                                           elem_classes="checkbox-large")
+                enable_thinking = gr.Checkbox(label="Enable Thinking （启用思维链）",
+                                              value=False,
+                                              interactive=True,
+                                              elem_classes="checkbox-large")
+                temperature = gr.Slider(label="Temperature",
+                                        minimum=0.1,
+                                        maximum=2.0,
+                                        value=0.6,
+                                        step=0.1)
+                top_p = gr.Slider(label="Top P",
+                                  minimum=0.05,
+                                  maximum=1.0,
+                                  value=0.95,
+                                  step=0.05)
+                top_k = gr.Slider(label="Top K",
+                                  minimum=1,
+                                  maximum=100,
+                                  value=20,
+                                  step=1)
+
             with gr.Column(scale=3):
                 with gr.Tabs():
                     with gr.TabItem("Online"):
                         with gr.Row():
                             with gr.Column(scale=1):
                                 gr.Markdown("### Audio-Video Input (音视频输入)")
-                                microphone = gr.Audio(sources=['microphone'], type="filepath",
-                                                      label="Record Audio (录制音频)")
-                                webcam = gr.Video(sources=['webcam', "upload"],
-                                                  label="Record/Upload Video (录制/上传视频)",
-                                                  elem_classes="media-upload")
+                                microphone = gr.Audio(
+                                    sources=['microphone'],
+                                    type="filepath",
+                                    label="Record Audio (录制音频)")
+                                webcam = gr.Video(
+                                    sources=['webcam', "upload"],
+                                    label="Record/Upload Video (录制/上传视频)",
+                                    elem_classes="media-upload")
                                 with gr.Row():
-                                    submit_btn_online = gr.Button("Submit (提交)", variant="primary", scale=2)
-                                    stop_btn_online = gr.Button("Stop (停止)", visible=False, scale=1)
-                                clear_btn_online = gr.Button("Clear History (清除历史)")
+                                    submit_btn_online = gr.Button(
+                                        "Submit (提交)",
+                                        variant="primary",
+                                        scale=2)
+                                    stop_btn_online = gr.Button("Stop (停止)",
+                                                                visible=False,
+                                                                scale=1)
+                                clear_btn_online = gr.Button(
+                                    "Clear History (清除历史)")
                             with gr.Column(scale=2):
                                 # FIX: Re-added type="messages"
-                                media_chatbot = gr.Chatbot(label="Chat History (对话历史)", type="messages", height=650,
-                                                           layout="panel", bubble_full_width=False,
-                                                           allow_tags=["think"], render=False)
+                                media_chatbot = gr.Chatbot(
+                                    label="Chat History (对话历史)",
+                                    type="messages",
+                                    height=650,
+                                    layout="panel",
+                                    bubble_full_width=False,
+                                    allow_tags=["think"],
+                                    render=False)
                                 media_chatbot.render()
-                        
+
                         def clear_history_online():
                             return [], None, None
-                        
+
                         submit_event_online = submit_btn_online.click(
                             fn=media_predict,
-                            inputs=[microphone, webcam, media_chatbot, system_prompt_textbox, voice_choice, temperature,
-                                    top_p, top_k, return_audio, enable_thinking],
-                            outputs=[microphone, webcam, media_chatbot, submit_btn_online, stop_btn_online]
-                        )
-                        stop_btn_online.click(fn=lambda: (gr.update(visible=True), gr.update(visible=False)),
-                                              outputs=[submit_btn_online, stop_btn_online],
-                                              cancels=[submit_event_online], queue=False)
-                        clear_btn_online.click(fn=clear_history_online, outputs=[media_chatbot, microphone, webcam])
-                    
+                            inputs=[
+                                microphone, webcam, media_chatbot,
+                                system_prompt_textbox, voice_choice,
+                                temperature, top_p, top_k, return_audio,
+                                enable_thinking
+                            ],
+                            outputs=[
+                                microphone, webcam, media_chatbot,
+                                submit_btn_online, stop_btn_online
+                            ])
+                        stop_btn_online.click(
+                            fn=lambda: (gr.update(visible=True),
+                                        gr.update(visible=False)),
+                            outputs=[submit_btn_online, stop_btn_online],
+                            cancels=[submit_event_online],
+                            queue=False)
+                        clear_btn_online.click(
+                            fn=clear_history_online,
+                            outputs=[media_chatbot, microphone, webcam])
+
                     with gr.TabItem("Offline"):
                         # FIX: Re-added type="messages"
-                        chatbot = gr.Chatbot(label="Chat History (对话历史)", type="messages", height=550,
-                                             layout="panel", bubble_full_width=False, allow_tags=["think"],
+                        chatbot = gr.Chatbot(label="Chat History (对话历史)",
+                                             type="messages",
+                                             height=550,
+                                             layout="panel",
+                                             bubble_full_width=False,
+                                             allow_tags=["think"],
                                              render=False)
                         chatbot.render()
-                        
-                        with gr.Accordion("📎 Click to upload multimodal files (点击上传多模态文件)", open=False):
+
+                        with gr.Accordion(
+                                "📎 Click to upload multimodal files (点击上传多模态文件)",
+                                open=False):
                             with gr.Row():
-                                audio_input = gr.Audio(sources=["upload", 'microphone'], type="filepath", label="Audio",
-                                                       elem_classes="media-upload")
-                                image_input = gr.Image(sources=["upload", 'webcam'], type="filepath", label="Image",
-                                                       elem_classes="media-upload")
-                                video_input = gr.Video(sources=["upload", 'webcam'], label="Video",
-                                                       elem_classes="media-upload")
-                        
+                                audio_input = gr.Audio(
+                                    sources=["upload", 'microphone'],
+                                    type="filepath",
+                                    label="Audio",
+                                    elem_classes="media-upload")
+                                image_input = gr.Image(
+                                    sources=["upload", 'webcam'],
+                                    type="filepath",
+                                    label="Image",
+                                    elem_classes="media-upload")
+                                video_input = gr.Video(
+                                    sources=["upload", 'webcam'],
+                                    label="Video",
+                                    elem_classes="media-upload")
+
                         with gr.Row():
-                            text_input = gr.Textbox(show_label=False,
-                                                    placeholder="Enter text or upload files and press Submit... (输入文本或者上传文件并点击提交)",
-                                                    scale=7)
-                            submit_btn_offline = gr.Button("Submit (提交)", variant="primary", scale=1)
-                            stop_btn_offline = gr.Button("Stop (停止)", visible=False, scale=1)
-                            clear_btn_offline = gr.Button("Clear (清空) ", scale=1)
-                        
+                            text_input = gr.Textbox(
+                                show_label=False,
+                                placeholder=
+                                "Enter text or upload files and press Submit... (输入文本或者上传文件并点击提交)",
+                                scale=7)
+                            submit_btn_offline = gr.Button("Submit (提交)",
+                                                           variant="primary",
+                                                           scale=1)
+                            stop_btn_offline = gr.Button("Stop (停止)",
+                                                         visible=False,
+                                                         scale=1)
+                            clear_btn_offline = gr.Button("Clear (清空) ",
+                                                          scale=1)
+
                         def clear_history_offline():
                             return [], None, None, None, None
-                        
+
                         submit_event_offline = gr.on(
-                            triggers=[submit_btn_offline.click, text_input.submit],
+                            triggers=[
+                                submit_btn_offline.click, text_input.submit
+                            ],
                             fn=chat_predict,
-                            inputs=[text_input, audio_input, image_input, video_input, chatbot, system_prompt_textbox,
-                                    voice_choice, temperature, top_p, top_k, return_audio, enable_thinking],
-                            outputs=[text_input, audio_input, image_input, video_input, chatbot]
-                        )
-                        stop_btn_offline.click(fn=lambda: (gr.update(visible=True), gr.update(visible=False)),
-                                               outputs=[submit_btn_offline, stop_btn_offline],
-                                               cancels=[submit_event_offline], queue=False)
+                            inputs=[
+                                text_input, audio_input, image_input,
+                                video_input, chatbot, system_prompt_textbox,
+                                voice_choice, temperature, top_p, top_k,
+                                return_audio, enable_thinking
+                            ],
+                            outputs=[
+                                text_input, audio_input, image_input,
+                                video_input, chatbot
+                            ])
+                        stop_btn_offline.click(
+                            fn=lambda: (gr.update(visible=True),
+                                        gr.update(visible=False)),
+                            outputs=[submit_btn_offline, stop_btn_offline],
+                            cancels=[submit_event_offline],
+                            queue=False)
                         clear_btn_offline.click(fn=clear_history_offline,
-                                                outputs=[chatbot, text_input, audio_input, image_input, video_input])
-        
+                                                outputs=[
+                                                    chatbot, text_input,
+                                                    audio_input, image_input,
+                                                    video_input
+                                                ])
+
         gr.HTML("""
             <style>
                 .media-upload { min-height: 160px; border: 2px dashed #ccc; border-radius: 8px; display: flex; align-items: center; justify-content: center; }
                 .media-upload:hover { border-color: #666; }
             </style>
         """)
-    
-    demo.queue(default_concurrency_limit=100, max_size=100).launch(max_threads=100,
-                                                                   ssr_mode=False,
-                                                                   share=args.share,
-                                                                   inbrowser=args.inbrowser,
-                                                                   # ssl_certfile="examples/offline_inference/qwen3_omni_moe/cert.pem",
-                                                                   # ssl_keyfile="examples/offline_inference/qwen3_omni_moe/key.pem",
-                                                                   # ssl_verify=False,
-                                                                   server_port=args.server_port,
-                                                                   server_name=args.server_name, )
+
+    demo.queue(default_concurrency_limit=100, max_size=100).launch(
+        max_threads=100,
+        ssr_mode=False,
+        share=args.share,
+        inbrowser=args.inbrowser,
+        # ssl_certfile="examples/offline_inference/qwen3_omni_moe/cert.pem",
+        # ssl_keyfile="examples/offline_inference/qwen3_omni_moe/key.pem",
+        # ssl_verify=False,
+        server_port=args.server_port,
+        server_name=args.server_name,
+    )
 
 
 DEFAULT_CKPT_PATH = "Qwen/Qwen3-Omni-30B-A3B-Instruct"
@@ -724,35 +945,51 @@ DEFAULT_CKPT_PATH = "Qwen/Qwen3-Omni-30B-A3B-Instruct"
 
 def _get_args():
     parser = ArgumentParser()
-    
+
     parser.add_argument('-c',
                         '--checkpoint-path',
                         type=str,
                         default=DEFAULT_CKPT_PATH,
                         help='Checkpoint name or path, default to %(default)r')
-    parser.add_argument('--cpu-only', action='store_true', help='Run demo with CPU only')
-    
-    parser.add_argument('--flash-attn2',
+    parser.add_argument('--cpu-only',
                         action='store_true',
-                        default=False,
-                        help='Enable flash_attention_2 when loading the model.')
+                        help='Run demo with CPU only')
+
+    parser.add_argument(
+        '--flash-attn2',
+        action='store_true',
+        default=False,
+        help='Enable flash_attention_2 when loading the model.')
     parser.add_argument('--use-transformers',
                         action='store_true',
                         default=False,
                         help='Use transformers for inference.')
-    parser.add_argument('--share',
-                        action='store_true',
-                        default=False,
-                        help='Create a publicly shareable link for the interface.')
-    parser.add_argument('--inbrowser',
-                        action='store_true',
-                        default=False,
-                        help='Automatically launch the interface in a new tab on the default browser.')
-    parser.add_argument('--server-port', type=int, default=7860, help='Demo server port.')
-    parser.add_argument('--server-name', type=str, default='0.0.0.0', help='Demo server name.')
-    parser.add_argument('--ui-language', type=str, choices=['en', 'zh'], default='zh',
+    parser.add_argument(
+        '--share',
+        action='store_true',
+        default=False,
+        help='Create a publicly shareable link for the interface.')
+    parser.add_argument(
+        '--inbrowser',
+        action='store_true',
+        default=False,
+        help=
+        'Automatically launch the interface in a new tab on the default browser.'
+    )
+    parser.add_argument('--server-port',
+                        type=int,
+                        default=8905,
+                        help='Demo server port.')
+    parser.add_argument('--server-name',
+                        type=str,
+                        default='0.0.0.0',
+                        help='Demo server name.')
+    parser.add_argument('--ui-language',
+                        type=str,
+                        choices=['en', 'zh'],
+                        default='zh',
                         help='Display language for the UI.')
-    
+
     args = parser.parse_args()
     return args
 
@@ -761,5 +998,3 @@ if __name__ == "__main__":
     args = _get_args()
     model, processor = _load_model_processor(args)
     _launch_demo(args, model, processor)
-
-