feat(litellm): add native Beijing Bailian ASR and personal vocabulary

servers/bwh-hk-cmi/litellm/.gitignore

@@ -0,0 +1 @@
+__pycache__/

servers/bwh-hk-cmi/litellm/bailian_transcription.py

@@ -0,0 +1,119 @@
+"""Bridge OpenAI file uploads to Beijing Bailian's native ASR API."""
+import base64
+import io
+import json
+from pathlib import Path
+from urllib.parse import urlsplit
+import wave
+
+from litellm.llms.base_llm.audio_transcription.transformation import AudioTranscriptionRequestData
+from litellm.llms.openai.transcriptions.whisper_transformation import OpenAIWhisperAudioTranscriptionConfig
+from litellm.litellm_core_utils.audio_utils.utils import process_audio_file
+from litellm.types.utils import TranscriptionResponse, TranscriptionUsageDurationObject
+
+MODEL = 'qwen-audio-3.1-asr-flash'
+FORMATS = {'audio/wav':'wav','audio/x-wav':'wav','audio/wave':'wav',
+    'audio/mpeg':'mp3','audio/mp3':'mp3','audio/flac':'flac','audio/x-flac':'flac',
+    'audio/mp4':'m4a','audio/m4a':'m4a','audio/x-m4a':'m4a',
+    'audio/ogg':'ogg','audio/webm':'webm','video/webm':'webm','audio/aac':'aac'}
+VOCABULARY_PATHS = frozenset({'/etc/litellm/personal-vocabulary.json',
+                              '/credentials/personal-vocabulary.json'})
+
+
+def vocabulary(path):
+    if path not in VOCABULARY_PATHS:
+        raise ValueError('Unexpected personal vocabulary path')
+    words = json.loads(Path(path).read_text())
+    if not isinstance(words,list) or not 1 <= len(words) <= 100:
+        raise ValueError('Personal vocabulary must contain 1-100 terms')
+    if any(not isinstance(w,str) or not w.strip() or len(w)>100 for w in words):
+        raise ValueError('Invalid personal vocabulary term')
+    return {w.strip():3 for w in words}
+
+
+class BailianTranscriptionConfig(OpenAIWhisperAudioTranscriptionConfig):
+    @property
+    def has_native_transcription_endpoint(self):
+        return True
+
+    def get_supported_openai_params(self,model):
+        return ['language','response_format','prompt']
+
+    def map_openai_params(self,non_default_params,optional_params,model,drop_params):
+        result=super().map_openai_params(non_default_params,optional_params,model,drop_params)
+        if result.get('response_format') not in (None,'json','text'):
+            raise ValueError('Bailian dictation supports json/text without timestamps')
+        return result
+
+    def validate_environment(self,headers,model,messages,optional_params,litellm_params,
+                             api_key=None,api_base=None):
+        if not api_key:raise ValueError('Beijing Bailian API key required')
+        return {**headers,'Authorization':'Bearer '+api_key,'Content-Type':'application/json',
+                'X-DashScope-SSE':'disable'}
+
+    def get_complete_url(self,api_base,api_key,model,optional_params,litellm_params,stream=None):
+        parsed=urlsplit(api_base or '')
+        if (model != MODEL or parsed.scheme != 'https' or
+            not (parsed.hostname or '').endswith('.cn-beijing.maas.aliyuncs.com') or
+            parsed.path.rstrip('/') != '/api/v1' or parsed.port not in (None,443) or
+            parsed.username or parsed.password or parsed.query or parsed.fragment):
+            raise ValueError('Bailian ASR restricted to Beijing workspace native endpoints')
+        if stream:raise ValueError('Streaming not enabled on this dictation route')
+        return api_base.rstrip('/')+'/services/aigc/multimodal-generation/generation'
+
+    def transform_audio_transcription_request(self,model,audio_file,optional_params,litellm_params):
+        if model != MODEL or optional_params.get('timestamp_granularities'):
+            raise ValueError('Unsupported Bailian dictation model or timestamps')
+        audio=process_audio_file(audio_file)
+        mime=audio.content_type.split(';',1)[0].lower()
+        if mime not in FORMATS:raise ValueError('Unsupported Bailian audio MIME type')
+        if len(audio.file_content)>10_000_000:raise ValueError('Bailian inline audio exceeds 10 MB')
+        parameters={'format':FORMATS[mime]}
+        if parameters['format']=='wav':
+            with wave.open(io.BytesIO(audio.file_content),'rb') as wav:
+                parameters['sample_rate']=str(wav.getframerate())
+        language=optional_params.get('language')
+        if language:parameters['language_hints']=[language]
+        # LiteLLM classifies DashScope as OpenAI-compatible and nests custom kwargs.
+        extra=optional_params.get('extra_body') or {}
+        path=optional_params.get('bailian_vocabulary_path') or extra.get('bailian_vocabulary_path')
+        if path:parameters['vocabulary']=vocabulary(path)
+        prompt=optional_params.get('prompt')
+        messages=[]
+        if prompt:
+            if not isinstance(prompt,str) or len(prompt)>400:
+                raise ValueError('Bailian context prompt must be at most 400 characters')
+            messages.append({'role':'user','content':[{'type':'input_text','text':prompt}]})
+        # Always preserve the original bytes; only WAV metadata supplies sample rate.
+        uri_mime='audio/mp3' if parameters['format']=='mp3' else mime
+        data_uri='data:'+uri_mime+';base64,'+base64.b64encode(audio.file_content).decode()
+        if len(data_uri)>10_000_000:
+            raise ValueError('Bailian inline audio exceeds 10 MB after Base64 encoding')
+        messages.append({'role':'user','content':[{'type':'input_audio','input_audio':{
+            'data':data_uri}}]})
+        return AudioTranscriptionRequestData(data={'model':MODEL,'input':{'messages':messages},
+                                                  'parameters':parameters})
+
+    def transform_audio_transcription_response(self,raw_response):
+        body=raw_response.json()
+        text=body.get('output',{}).get('text',body.get('text'))
+        if not isinstance(text,str):raise ValueError('Bailian returned no transcript')
+        result=TranscriptionResponse(text=text)
+        duration=(body.get('usage') or {}).get('duration')
+        if duration is not None:
+            result.usage=TranscriptionUsageDurationObject(type='duration',seconds=duration)
+            result['duration']=duration
+        return result
+
+
+def install():
+    import litellm
+    from litellm.utils import ProviderConfigManager
+    original=ProviderConfigManager.get_provider_audio_transcription_config
+    if getattr(original,'_bailian_asr_adapter',False):return
+    def select(model,provider):
+        if provider==litellm.LlmProviders.DASHSCOPE and model==MODEL:
+            return BailianTranscriptionConfig()
+        return original(model,provider)
+    select._bailian_asr_adapter=True
+    ProviderConfigManager.get_provider_audio_transcription_config=staticmethod(select)

servers/bwh-hk-cmi/litellm/compose.yaml

@@ -35,12 +35,15 @@ services:
       ZENMUX_SUBSCRIPTION_API_KEY: ${ZENMUX_SUBSCRIPTION_API_KEY:-}
       ZENMUX_PAYG_API_KEY: ${ZENMUX_PAYG_API_KEY:-}
       OPENROUTER_API_KEY: ${OPENROUTER_API_KEY:-}
+      BAILIAN_CN_API_KEY: ${BAILIAN_CN_API_KEY:-}
+      BAILIAN_CN_API_BASE: ${BAILIAN_CN_API_BASE:-https://ws-v68kvjnmhkiejaxo.cn-beijing.maas.aliyuncs.com/api/v1}
     volumes:
       - ./models.yaml:/etc/litellm/models.yaml:ro
       - ./provider_routes.py:/etc/litellm/provider_routes.py:ro
       - ./render_config.py:/etc/litellm/render_config.py:ro
       - ./vertex_dictation.py:/etc/litellm/vertex_dictation.py:ro
       - ./zenmux_transcription.py:/etc/litellm/zenmux_transcription.py:ro
+      - ./bailian_transcription.py:/etc/litellm/bailian_transcription.py:ro
       - google-adc:/credentials:ro
     entrypoint: ["/bin/sh", "-c"]
     command:

servers/bwh-hk-cmi/litellm/provider_routes.py

@@ -75,6 +75,22 @@ def namespace_config(config):
     return config
 
 
+def add_bailian_routes(config, env, vocabulary_path):
+    if env.get('BAILIAN_CN_API_KEY'):
+        base = env.get('BAILIAN_CN_API_BASE')
+        if not base:
+            raise ValueError('BAILIAN_CN_API_BASE required for Beijing Bailian')
+        for personal in [False, True]:
+            params = {'model': 'dashscope/qwen-audio-3.1-asr-flash',
+                      'api_base': base, 'api_key': 'os.environ/BAILIAN_CN_API_KEY',
+                      'max_retries': 0}
+            if personal:
+                params['bailian_vocabulary_path'] = vocabulary_path
+            config['model_list'].append({'model_name': 'bailian-cn/qwen-audio-3.1-asr-flash' +
+                ('-personal' if personal else ''), 'litellm_params': params})
+    return config
+
+
 def build_config(catalog, env, exists, namespaced=True):
     routes = []
     fallbacks = []
@@ -146,7 +162,8 @@ def build_config(catalog, env, exists, namespaced=True):
         # Only explicitly approved open-model routes have cross-provider fallbacks.
         'router_settings': {'num_retries': 1, 'timeout': 180, 'fallbacks': fallbacks},
     }
-    return namespace_config(config) if namespaced else config
+    return add_bailian_routes(namespace_config(config), env,
+        '/etc/litellm/personal-vocabulary.json') if namespaced else config
 
 
 if __name__ == '__main__':

servers/bwh-hk-cmi/litellm/render_config.py

@@ -4,7 +4,7 @@ from pathlib import Path
 
 import yaml
 
-from provider_routes import build_config, namespace_config
+from provider_routes import build_config, namespace_config, add_bailian_routes
 
 
 def build_hk_config(catalog, env):
@@ -47,7 +47,7 @@ def build_hk_config(catalog, env):
                 'model': 'vertex_ai/' + model,
                 'vertex_project': 'os.environ/VERTEXAI_PROJECT',
                 'vertex_location': 'os.environ/VERTEXAI_LOCATION'}})
-    return namespace_config(config)
+    return add_bailian_routes(namespace_config(config), env, '/credentials/personal-vocabulary.json')
 
 
 if __name__ == '__main__':

servers/bwh-hk-cmi/litellm/test_config.py

@@ -7,6 +7,14 @@ from render_config import build_hk_config
 
 
 class RoutingTests(unittest.TestCase):
+    def test_bailian_personal_uses_hk_private_vocabulary(self):
+        catalog = yaml.safe_load(Path(__file__).with_name('models.yaml').read_text())
+        routes = build_hk_config(catalog, {'BAILIAN_CN_API_KEY':'synthetic',
+            'BAILIAN_CN_API_BASE':'https://ws-test.cn-beijing.maas.aliyuncs.com/api/v1'})['model_list']
+        self.assertEqual(len(routes),2)
+        self.assertEqual(routes[1]['litellm_params']['bailian_vocabulary_path'],
+                         '/credentials/personal-vocabulary.json')
+
     def test_all_providers(self):
         catalog = yaml.safe_load(Path(__file__).with_name('models.yaml').read_text())
         env = {key: 'synthetic' for key in ['ZENMUX_SUBSCRIPTION_API_KEY',

servers/bwh-hk-cmi/litellm/vertex_dictation.py

@@ -46,7 +46,9 @@ if __name__ == '__main__':
     import sys
     from litellm import run_server
     from zenmux_transcription import install as install_zenmux_asr
+    from bailian_transcription import install as install_bailian_asr
     install_zenmux_asr()
+    install_bailian_asr()
     install()
     sys.argv[0] = 'litellm'
     sys.exit(run_server())

servers/bwh-hk-cmi/litellm/百炼北京ASR.md

@@ -0,0 +1,24 @@
+# 百炼北京原厂 ASR
+
+2026-10-27 上线，仅北京，不配置新加坡或跨地域回退。客户端沿用本机 LiteLLM 的 /v1/audio/transcriptions、现有客户端 key、multipart 文件上传，推荐 response_format=json。
+
+| 模型名 | 行为 |
+| --- | --- |
+| bailian-cn/qwen-audio-3.1-asr-flash | 原厂识别，无词表注入 |
+| bailian-cn/qwen-audio-3.1-asr-flash-personal | 相同模型，原生 vocabulary 注入既有 20 个人名／公司名，每词权重 3 |
+
+上游为业务空间专属域名 `https://ws-v68kvjnmhkiejaxo.cn-beijing.maas.aliyuncs.com/api/v1`，使用原生 `/services/aigc/multimodal-generation/generation`，不是 compatible-mode。已用 .145 现有 BAILIAN_API_KEY 实测该空间可用；部署后凭据权威是各 Arcane Project 的 BAILIAN_CN_API_KEY，原始 key 不进入 Git。
+
+当前 LiteLLM 1.104.2 没有 DashScope 原生转写配置，启动适配器仅接管 dashscope provider 的 qwen-audio-3.1-asr-flash。普通 Gemini、Vertex、ZenMux 和 OpenAI 不变。不增加服务、端口或镜像，不重新部署会议管线。
+
+文件原字节转为 Base64 Data URI。WAV 从文件头读取采样率，非 WAV 不伪造采样率；上游可选 prompt 作为 input_text 上下文，不覆盖、不做二次 LLM 改写，最多 400 字。生产个人词表从当前节点已有私有文件读取，不把词表放到 Git。DashScope 自定义参数在 SDK 中进入 extra_body，适配器需取出私有词表路径，再生成 parameters.vocabulary；私有路径不能泄漏上游。
+
+不启用 streaming、时间戳或说话人分离，不承诺自动去口语化；原厂默认识别行为不额外覆盖。上传 Base64 Data URI 保守限制 10 MB，超限明确拒绝，不自动把文件上传公网。json 为已验证的推荐响应格式。
+
+配置验证：先运行每目录 test_config.py，再在固定镜像中执行 scripts/test-bailian-asr-wire.py，检查同步/异步真实 SDK 的 HTTP 请求体、热词、原字节保持及其他 provider 不受影响。
+
+原厂 A/B：2026-07-21 电话前 90 秒，无热词两处“洛奇”，指定临时热词“洛启、普华”（权重 3）后两处“洛启”，耗时分别 3.432／3.649 秒。该结果只证明该片段短词表有改善，不代表已有 20 词表一定同等改善或整体 CER/WER。
+
+上线后必须验证：两节点普通／个人路由公开音频、现有客户端 key 权限、词表开关和 native vocabulary 请求体。新模型不因部署便自动获得 virtual key 权限；仅为用户批准的应用增加这两条路线，不扩大到全部模型。
+
+官方文档：https://help.aliyun.com/zh/model-studio/fun-asr-flash-recorded-speech-recognition-http-api

servers/tools-pve/litellm/.env.example

@@ -6,6 +6,8 @@ LITELLM_SALT_KEY=
 ZENMUX_SUBSCRIPTION_API_KEY=
 ZENMUX_PAYG_API_KEY=
 OPENROUTER_API_KEY=
+BAILIAN_CN_API_KEY=
+BAILIAN_CN_API_BASE=https://ws-v68kvjnmhkiejaxo.cn-beijing.maas.aliyuncs.com/api/v1
 GOOGLE_AI_STUDIO_API_KEY=
 VERTEXAI_ENABLED=false
 VERTEXAI_PROJECT=

servers/tools-pve/litellm/bailian_transcription.py

@@ -0,0 +1,119 @@
+"""Bridge OpenAI file uploads to Beijing Bailian's native ASR API."""
+import base64
+import io
+import json
+from pathlib import Path
+from urllib.parse import urlsplit
+import wave
+
+from litellm.llms.base_llm.audio_transcription.transformation import AudioTranscriptionRequestData
+from litellm.llms.openai.transcriptions.whisper_transformation import OpenAIWhisperAudioTranscriptionConfig
+from litellm.litellm_core_utils.audio_utils.utils import process_audio_file
+from litellm.types.utils import TranscriptionResponse, TranscriptionUsageDurationObject
+
+MODEL = 'qwen-audio-3.1-asr-flash'
+FORMATS = {'audio/wav':'wav','audio/x-wav':'wav','audio/wave':'wav',
+    'audio/mpeg':'mp3','audio/mp3':'mp3','audio/flac':'flac','audio/x-flac':'flac',
+    'audio/mp4':'m4a','audio/m4a':'m4a','audio/x-m4a':'m4a',
+    'audio/ogg':'ogg','audio/webm':'webm','video/webm':'webm','audio/aac':'aac'}
+VOCABULARY_PATHS = frozenset({'/etc/litellm/personal-vocabulary.json',
+                              '/credentials/personal-vocabulary.json'})
+
+
+def vocabulary(path):
+    if path not in VOCABULARY_PATHS:
+        raise ValueError('Unexpected personal vocabulary path')
+    words = json.loads(Path(path).read_text())
+    if not isinstance(words,list) or not 1 <= len(words) <= 100:
+        raise ValueError('Personal vocabulary must contain 1-100 terms')
+    if any(not isinstance(w,str) or not w.strip() or len(w)>100 for w in words):
+        raise ValueError('Invalid personal vocabulary term')
+    return {w.strip():3 for w in words}
+
+
+class BailianTranscriptionConfig(OpenAIWhisperAudioTranscriptionConfig):
+    @property
+    def has_native_transcription_endpoint(self):
+        return True
+
+    def get_supported_openai_params(self,model):
+        return ['language','response_format','prompt']
+
+    def map_openai_params(self,non_default_params,optional_params,model,drop_params):
+        result=super().map_openai_params(non_default_params,optional_params,model,drop_params)
+        if result.get('response_format') not in (None,'json','text'):
+            raise ValueError('Bailian dictation supports json/text without timestamps')
+        return result
+
+    def validate_environment(self,headers,model,messages,optional_params,litellm_params,
+                             api_key=None,api_base=None):
+        if not api_key:raise ValueError('Beijing Bailian API key required')
+        return {**headers,'Authorization':'Bearer '+api_key,'Content-Type':'application/json',
+                'X-DashScope-SSE':'disable'}
+
+    def get_complete_url(self,api_base,api_key,model,optional_params,litellm_params,stream=None):
+        parsed=urlsplit(api_base or '')
+        if (model != MODEL or parsed.scheme != 'https' or
+            not (parsed.hostname or '').endswith('.cn-beijing.maas.aliyuncs.com') or
+            parsed.path.rstrip('/') != '/api/v1' or parsed.port not in (None,443) or
+            parsed.username or parsed.password or parsed.query or parsed.fragment):
+            raise ValueError('Bailian ASR restricted to Beijing workspace native endpoints')
+        if stream:raise ValueError('Streaming not enabled on this dictation route')
+        return api_base.rstrip('/')+'/services/aigc/multimodal-generation/generation'
+
+    def transform_audio_transcription_request(self,model,audio_file,optional_params,litellm_params):
+        if model != MODEL or optional_params.get('timestamp_granularities'):
+            raise ValueError('Unsupported Bailian dictation model or timestamps')
+        audio=process_audio_file(audio_file)
+        mime=audio.content_type.split(';',1)[0].lower()
+        if mime not in FORMATS:raise ValueError('Unsupported Bailian audio MIME type')
+        if len(audio.file_content)>10_000_000:raise ValueError('Bailian inline audio exceeds 10 MB')
+        parameters={'format':FORMATS[mime]}
+        if parameters['format']=='wav':
+            with wave.open(io.BytesIO(audio.file_content),'rb') as wav:
+                parameters['sample_rate']=str(wav.getframerate())
+        language=optional_params.get('language')
+        if language:parameters['language_hints']=[language]
+        # LiteLLM classifies DashScope as OpenAI-compatible and nests custom kwargs.
+        extra=optional_params.get('extra_body') or {}
+        path=optional_params.get('bailian_vocabulary_path') or extra.get('bailian_vocabulary_path')
+        if path:parameters['vocabulary']=vocabulary(path)
+        prompt=optional_params.get('prompt')
+        messages=[]
+        if prompt:
+            if not isinstance(prompt,str) or len(prompt)>400:
+                raise ValueError('Bailian context prompt must be at most 400 characters')
+            messages.append({'role':'user','content':[{'type':'input_text','text':prompt}]})
+        # Always preserve the original bytes; only WAV metadata supplies sample rate.
+        uri_mime='audio/mp3' if parameters['format']=='mp3' else mime
+        data_uri='data:'+uri_mime+';base64,'+base64.b64encode(audio.file_content).decode()
+        if len(data_uri)>10_000_000:
+            raise ValueError('Bailian inline audio exceeds 10 MB after Base64 encoding')
+        messages.append({'role':'user','content':[{'type':'input_audio','input_audio':{
+            'data':data_uri}}]})
+        return AudioTranscriptionRequestData(data={'model':MODEL,'input':{'messages':messages},
+                                                  'parameters':parameters})
+
+    def transform_audio_transcription_response(self,raw_response):
+        body=raw_response.json()
+        text=body.get('output',{}).get('text',body.get('text'))
+        if not isinstance(text,str):raise ValueError('Bailian returned no transcript')
+        result=TranscriptionResponse(text=text)
+        duration=(body.get('usage') or {}).get('duration')
+        if duration is not None:
+            result.usage=TranscriptionUsageDurationObject(type='duration',seconds=duration)
+            result['duration']=duration
+        return result
+
+
+def install():
+    import litellm
+    from litellm.utils import ProviderConfigManager
+    original=ProviderConfigManager.get_provider_audio_transcription_config
+    if getattr(original,'_bailian_asr_adapter',False):return
+    def select(model,provider):
+        if provider==litellm.LlmProviders.DASHSCOPE and model==MODEL:
+            return BailianTranscriptionConfig()
+        return original(model,provider)
+    select._bailian_asr_adapter=True
+    ProviderConfigManager.get_provider_audio_transcription_config=staticmethod(select)

servers/tools-pve/litellm/compose.yaml

@@ -37,6 +37,8 @@ services:
       ZENMUX_SUBSCRIPTION_API_KEY: ${ZENMUX_SUBSCRIPTION_API_KEY:-}
       ZENMUX_PAYG_API_KEY: ${ZENMUX_PAYG_API_KEY:-}
       OPENROUTER_API_KEY: ${OPENROUTER_API_KEY:-}
+      BAILIAN_CN_API_KEY: ${BAILIAN_CN_API_KEY:-}
+      BAILIAN_CN_API_BASE: ${BAILIAN_CN_API_BASE:-https://ws-v68kvjnmhkiejaxo.cn-beijing.maas.aliyuncs.com/api/v1}
       GOOGLE_AI_STUDIO_API_KEY: ${GOOGLE_AI_STUDIO_API_KEY:-}
       VERTEXAI_ENABLED: ${VERTEXAI_ENABLED:-false}
       VERTEXAI_PROJECT: ${VERTEXAI_PROJECT:-}
@@ -49,6 +51,7 @@ services:
       - ./models.yaml:/etc/litellm/models.yaml:ro
       - ./render_config.py:/etc/litellm/render_config.py:ro
       - ./personal_transcription.py:/etc/litellm/personal_transcription.py:ro
+      - ./bailian_transcription.py:/etc/litellm/bailian_transcription.py:ro
       - /opt/litellm/personal-vocabulary.json:/etc/litellm/personal-vocabulary.json:ro
       - oauth:/tokens
     entrypoint: [/bin/sh, -c]

servers/tools-pve/litellm/personal_transcription.py

@@ -45,6 +45,8 @@ def install():
 if __name__ == '__main__':
     import sys
     from litellm import run_server
+    from bailian_transcription import install as install_bailian_asr
+    install_bailian_asr()
     install()
     sys.argv[0] = 'litellm'
     sys.exit(run_server())

servers/tools-pve/litellm/render_config.py

@@ -75,6 +75,22 @@ def namespace_config(config):
     return config
 
 
+def add_bailian_routes(config, env, vocabulary_path):
+    if env.get('BAILIAN_CN_API_KEY'):
+        base = env.get('BAILIAN_CN_API_BASE')
+        if not base:
+            raise ValueError('BAILIAN_CN_API_BASE required for Beijing Bailian')
+        for personal in [False, True]:
+            params = {'model': 'dashscope/qwen-audio-3.1-asr-flash',
+                      'api_base': base, 'api_key': 'os.environ/BAILIAN_CN_API_KEY',
+                      'max_retries': 0}
+            if personal:
+                params['bailian_vocabulary_path'] = vocabulary_path
+            config['model_list'].append({'model_name': 'bailian-cn/qwen-audio-3.1-asr-flash' +
+                ('-personal' if personal else ''), 'litellm_params': params})
+    return config
+
+
 def build_config(catalog, env, exists, namespaced=True):
     routes = []
     fallbacks = []
@@ -146,7 +162,8 @@ def build_config(catalog, env, exists, namespaced=True):
         # Only explicitly approved open-model routes have cross-provider fallbacks.
         'router_settings': {'num_retries': 1, 'timeout': 180, 'fallbacks': fallbacks},
     }
-    return namespace_config(config) if namespaced else config
+    return add_bailian_routes(namespace_config(config), env,
+        '/etc/litellm/personal-vocabulary.json') if namespaced else config
 
 
 if __name__ == '__main__':

servers/tools-pve/litellm/test_config.py

@@ -18,6 +18,18 @@ class ConfigTests(unittest.TestCase):
     def test_missing_credentials_exclude_routes(self):
         self.assertEqual(build_config(self.catalog, {}, lambda _: False)['model_list'], [])
 
+    def test_bailian_routes_are_native_and_opt_in(self):
+        env = {'BAILIAN_CN_API_KEY': 'synthetic', 'BAILIAN_CN_API_BASE':
+               'https://ws-test.cn-beijing.maas.aliyuncs.com/api/v1'}
+        routes = build_config(self.catalog, env, lambda _: False)['model_list']
+        self.assertEqual(len(routes), 2)
+        self.assertEqual(routes[0]['model_name'], 'bailian-cn/qwen-audio-3.1-asr-flash')
+        self.assertNotIn('bailian_vocabulary_path', routes[0]['litellm_params'])
+        self.assertEqual(routes[1]['litellm_params']['bailian_vocabulary_path'],
+                         '/etc/litellm/personal-vocabulary.json')
+        self.assertEqual(routes[0]['litellm_params']['model'], 'dashscope/qwen-audio-3.1-asr-flash')
+        self.assertNotIn('synthetic', str(routes))
+
     def test_namespaces_preserve_every_legacy_route(self):
         catalog = yaml.safe_load(Path(__file__).with_name('models.yaml').read_text())
         env = {key: 'synthetic' for key in ['ZENMUX_SUBSCRIPTION_API_KEY',

servers/tools-pve/litellm/百炼北京ASR.md

@@ -0,0 +1,24 @@
+# 百炼北京原厂 ASR
+
+2026-10-27 上线，仅北京，不配置新加坡或跨地域回退。客户端沿用本机 LiteLLM 的 /v1/audio/transcriptions、现有客户端 key、multipart 文件上传，推荐 response_format=json。
+
+| 模型名 | 行为 |
+| --- | --- |
+| bailian-cn/qwen-audio-3.1-asr-flash | 原厂识别，无词表注入 |
+| bailian-cn/qwen-audio-3.1-asr-flash-personal | 相同模型，原生 vocabulary 注入既有 20 个人名／公司名，每词权重 3 |
+
+上游为业务空间专属域名 `https://ws-v68kvjnmhkiejaxo.cn-beijing.maas.aliyuncs.com/api/v1`，使用原生 `/services/aigc/multimodal-generation/generation`，不是 compatible-mode。已用 .145 现有 BAILIAN_API_KEY 实测该空间可用；部署后凭据权威是各 Arcane Project 的 BAILIAN_CN_API_KEY，原始 key 不进入 Git。
+
+当前 LiteLLM 1.104.2 没有 DashScope 原生转写配置，启动适配器仅接管 dashscope provider 的 qwen-audio-3.1-asr-flash。普通 Gemini、Vertex、ZenMux 和 OpenAI 不变。不增加服务、端口或镜像，不重新部署会议管线。
+
+文件原字节转为 Base64 Data URI。WAV 从文件头读取采样率，非 WAV 不伪造采样率；上游可选 prompt 作为 input_text 上下文，不覆盖、不做二次 LLM 改写，最多 400 字。生产个人词表从当前节点已有私有文件读取，不把词表放到 Git。DashScope 自定义参数在 SDK 中进入 extra_body，适配器需取出私有词表路径，再生成 parameters.vocabulary；私有路径不能泄漏上游。
+
+不启用 streaming、时间戳或说话人分离，不承诺自动去口语化；原厂默认识别行为不额外覆盖。上传 Base64 Data URI 保守限制 10 MB，超限明确拒绝，不自动把文件上传公网。json 为已验证的推荐响应格式。
+
+配置验证：先运行每目录 test_config.py，再在固定镜像中执行 scripts/test-bailian-asr-wire.py，检查同步/异步真实 SDK 的 HTTP 请求体、热词、原字节保持及其他 provider 不受影响。
+
+原厂 A/B：2026-07-21 电话前 90 秒，无热词两处“洛奇”，指定临时热词“洛启、普华”（权重 3）后两处“洛启”，耗时分别 3.432／3.649 秒。该结果只证明该片段短词表有改善，不代表已有 20 词表一定同等改善或整体 CER/WER。
+
+上线后必须验证：两节点普通／个人路由公开音频、现有客户端 key 权限、词表开关和 native vocabulary 请求体。新模型不因部署便自动获得 virtual key 权限；仅为用户批准的应用增加这两条路线，不扩大到全部模型。
+
+官方文档：https://help.aliyun.com/zh/model-studio/fun-asr-flash-recorded-speech-recognition-http-api