Use openai compatible as vendor

api/app/routers/asr.py

@@ -16,16 +16,22 @@ from ..schemas import (
 
 router = APIRouter(prefix="/asr", tags=["ASR Models"])
 
-SILICONFLOW_DEFAULT_ASR_MODEL = "FunAudioLLM/SenseVoiceSmall"
+OPENAI_COMPATIBLE_DEFAULT_ASR_MODEL = "FunAudioLLM/SenseVoiceSmall"
 
 
-def _is_siliconflow_vendor(vendor: str) -> bool:
+def _is_openai_compatible_vendor(vendor: str) -> bool:
-    return (vendor or "").strip().lower() in {"siliconflow", "硅基流动"}
+    normalized = (vendor or "").strip().lower()
+    return normalized in {
+        "openai compatible",
+        "openai-compatible",
+        "siliconflow",  # backward compatibility
+        "硅基流动",      # backward compatibility
+    }
 
 
 def _default_asr_model(vendor: str) -> str:
-    if _is_siliconflow_vendor(vendor):
+    if _is_openai_compatible_vendor(vendor):
-        return SILICONFLOW_DEFAULT_ASR_MODEL
+        return OPENAI_COMPATIBLE_DEFAULT_ASR_MODEL
     return "whisper-1"
 
 
@@ -129,7 +135,7 @@ def test_asr_model(
         # 连接性测试优先，避免依赖真实音频输入
         headers = {"Authorization": f"Bearer {model.api_key}"}
         with httpx.Client(timeout=60.0) as client:
-            if model.vendor.lower() in ["siliconflow", "paraformer"]:
+            if _is_openai_compatible_vendor(model.vendor) or model.vendor.lower() == "paraformer":
                 response = client.get(f"{model.base_url}/asr", headers=headers)
             elif model.vendor.lower() == "openai":
                 response = client.get(f"{model.base_url}/audio/models", headers=headers)
@@ -258,7 +264,7 @@ async def preview_asr_model(
         raise HTTPException(status_code=400, detail="Uploaded audio file is empty")
 
     effective_api_key = (api_key or "").strip() or (model.api_key or "").strip()
-    if not effective_api_key and _is_siliconflow_vendor(model.vendor):
+    if not effective_api_key and _is_openai_compatible_vendor(model.vendor):
         effective_api_key = os.getenv("SILICONFLOW_API_KEY", "").strip()
     if not effective_api_key:
         raise HTTPException(status_code=400, detail=f"API key is required for ASR model: {model.name}")

api/app/routers/assistants.py

@@ -13,8 +13,13 @@ from ..schemas import (
 router = APIRouter(prefix="/assistants", tags=["Assistants"])
 
 
-def _is_siliconflow_vendor(vendor: Optional[str]) -> bool:
+def _is_openai_compatible_vendor(vendor: Optional[str]) -> bool:
-    return (vendor or "").strip().lower() in {"siliconflow", "硅基流动"}
+    return (vendor or "").strip().lower() in {
+        "siliconflow",
+        "硅基流动",
+        "openai compatible",
+        "openai-compatible",
+    }
 
 
 def _resolve_runtime_metadata(db: Session, assistant: Assistant) -> dict:
@@ -47,11 +52,11 @@ def _resolve_runtime_metadata(db: Session, assistant: Assistant) -> dict:
     if assistant.asr_model_id:
         asr = db.query(ASRModel).filter(ASRModel.id == assistant.asr_model_id).first()
         if asr:
-            asr_provider = "siliconflow" if _is_siliconflow_vendor(asr.vendor) else "buffered"
+            asr_provider = "openai_compatible" if _is_openai_compatible_vendor(asr.vendor) else "buffered"
             metadata["services"]["asr"] = {
                 "provider": asr_provider,
                 "model": asr.model_name or asr.name,
-                "apiKey": asr.api_key if asr_provider == "siliconflow" else None,
+                "apiKey": asr.api_key if asr_provider == "openai_compatible" else None,
             }
         else:
             warnings.append(f"ASR model not found: {assistant.asr_model_id}")
@@ -61,12 +66,12 @@ def _resolve_runtime_metadata(db: Session, assistant: Assistant) -> dict:
     elif assistant.voice:
         voice = db.query(Voice).filter(Voice.id == assistant.voice).first()
         if voice:
-            tts_provider = "siliconflow" if _is_siliconflow_vendor(voice.vendor) else "edge"
+            tts_provider = "openai_compatible" if _is_openai_compatible_vendor(voice.vendor) else "edge"
             metadata["services"]["tts"] = {
                 "enabled": True,
                 "provider": tts_provider,
                 "model": voice.model,
-                "apiKey": voice.api_key if tts_provider == "siliconflow" else None,
+                "apiKey": voice.api_key if tts_provider == "openai_compatible" else None,
                 "voice": voice.voice_key or voice.id,
                 "speed": assistant.speed or voice.speed,
             }

api/app/routers/tools.py

@@ -467,7 +467,13 @@ def _test_asr_model(db: Session, model_id: str, result: AutotestResult):
         headers = {"Authorization": f"Bearer {model.api_key}"}
 
         with httpx.Client(timeout=30.0) as client:
-            if model.vendor.lower() in ["siliconflow", "paraformer"]:
+            normalized_vendor = (model.vendor or "").strip().lower()
+            if normalized_vendor in [
+                "openai compatible",
+                "openai-compatible",
+                "siliconflow",  # backward compatibility
+                "paraformer",
+            ]:
                 response = client.get(
                     f"{model.base_url}/asr",
                     headers=headers

api/app/routers/voices.py

@@ -13,20 +13,26 @@ from ..schemas import VoiceCreate, VoiceOut, VoicePreviewRequest, VoicePreviewRe
 
 router = APIRouter(prefix="/voices", tags=["Voices"])
 
-SILICONFLOW_DEFAULT_MODEL = "FunAudioLLM/CosyVoice2-0.5B"
+OPENAI_COMPATIBLE_DEFAULT_MODEL = "FunAudioLLM/CosyVoice2-0.5B"
 
 
-def _is_siliconflow_vendor(vendor: str) -> bool:
+def _is_openai_compatible_vendor(vendor: str) -> bool:
-    return vendor.strip().lower() in {"siliconflow", "硅基流动"}
+    normalized = (vendor or "").strip().lower()
+    return normalized in {
+        "openai compatible",
+        "openai-compatible",
+        "siliconflow",  # backward compatibility
+        "硅基流动",      # backward compatibility
+    }
 
 
 def _default_base_url(vendor: str) -> Optional[str]:
-    if _is_siliconflow_vendor(vendor):
+    if _is_openai_compatible_vendor(vendor):
         return "https://api.siliconflow.cn/v1"
     return None
 
 
-def _build_siliconflow_voice_key(voice: Voice, model: str) -> str:
+def _build_openai_compatible_voice_key(voice: Voice, model: str) -> str:
     if voice.voice_key:
         return voice.voice_key
     if ":" in voice.id:
@@ -65,8 +71,8 @@ def create_voice(data: VoiceCreate, db: Session = Depends(get_db)):
     model = data.model
     voice_key = data.voice_key
 
-    if _is_siliconflow_vendor(vendor):
+    if _is_openai_compatible_vendor(vendor):
-        model = model or SILICONFLOW_DEFAULT_MODEL
+        model = model or OPENAI_COMPATIBLE_DEFAULT_MODEL
         if not voice_key:
             raw_id = (data.id or data.name).strip()
             voice_key = raw_id if ":" in raw_id else f"{model}:{raw_id}"
@@ -115,11 +121,11 @@ def update_voice(id: str, data: VoiceUpdate, db: Session = Depends(get_db)):
         update_data["vendor"] = update_data["vendor"].strip()
 
     vendor_for_defaults = update_data.get("vendor", voice.vendor)
-    if _is_siliconflow_vendor(vendor_for_defaults):
+    if _is_openai_compatible_vendor(vendor_for_defaults):
-        model = update_data.get("model") or voice.model or SILICONFLOW_DEFAULT_MODEL
+        model = update_data.get("model") or voice.model or OPENAI_COMPATIBLE_DEFAULT_MODEL
         voice_key = update_data.get("voice_key") or voice.voice_key
         update_data["model"] = model
-        update_data["voice_key"] = voice_key or _build_siliconflow_voice_key(voice, model)
+        update_data["voice_key"] = voice_key or _build_openai_compatible_voice_key(voice, model)
 
     for field, value in update_data.items():
         setattr(voice, field, value)
@@ -152,7 +158,7 @@ def preview_voice(id: str, data: VoicePreviewRequest, db: Session = Depends(get_
         raise HTTPException(status_code=400, detail="Preview text cannot be empty")
 
     api_key = (data.api_key or "").strip() or (voice.api_key or "").strip()
-    if not api_key and _is_siliconflow_vendor(voice.vendor):
+    if not api_key and _is_openai_compatible_vendor(voice.vendor):
         api_key = os.getenv("SILICONFLOW_API_KEY", "").strip()
     if not api_key:
         raise HTTPException(status_code=400, detail=f"API key is required for voice: {voice.name}")
@@ -161,11 +167,11 @@ def preview_voice(id: str, data: VoicePreviewRequest, db: Session = Depends(get_
     if not base_url:
         raise HTTPException(status_code=400, detail=f"Base URL is required for voice: {voice.name}")
 
-    model = voice.model or SILICONFLOW_DEFAULT_MODEL
+    model = voice.model or OPENAI_COMPATIBLE_DEFAULT_MODEL
     payload = {
         "model": model,
         "input": text,
-        "voice": voice.voice_key or _build_siliconflow_voice_key(voice, model),
+        "voice": voice.voice_key or _build_openai_compatible_voice_key(voice, model),
         "response_format": "mp3",
         "speed": data.speed if data.speed is not None else voice.speed,
     }

api/docs/asr.md

@@ -20,7 +20,7 @@ interface ASRModel {
   id: string;           // 模型唯一标识 (8位UUID)
   user_id: number;      // 所属用户ID
   name: string;        // 模型显示名称
-  vendor: string;      // 供应商: "OpenAI" | "SiliconFlow" | "Paraformer" | 等
+  vendor: string;      // 供应商: "OpenAI Compatible" | "Paraformer" | 等
   language: string;     // 识别语言: "zh" | "en" | "Multi-lingual"
   base_url: string;     // API Base URL
   api_key: string;     // API Key
@@ -64,7 +64,7 @@ GET /api/v1/asr
       "id": "abc12345",
       "user_id": 1,
       "name": "Whisper 多语种识别",
-      "vendor": "OpenAI",
+      "vendor": "OpenAI Compatible",
       "language": "Multi-lingual",
       "base_url": "https://api.openai.com/v1",
       "api_key": "sk-***",
@@ -78,7 +78,7 @@ GET /api/v1/asr
       "id": "def67890",
       "user_id": 1,
       "name": "SenseVoice 中文识别",
-      "vendor": "SiliconFlow",
+      "vendor": "OpenAI Compatible",
       "language": "zh",
       "base_url": "https://api.siliconflow.cn/v1",
       "api_key": "sf-***",
@@ -114,7 +114,7 @@ GET /api/v1/asr/{id}
   "id": "abc12345",
   "user_id": 1,
   "name": "Whisper 多语种识别",
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "language": "Multi-lingual",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-***",
@@ -140,7 +140,7 @@ POST /api/v1/asr
 ```json
 {
   "name": "SenseVoice 中文识别",
-  "vendor": "SiliconFlow",
+  "vendor": "OpenAI Compatible",
   "language": "zh",
   "base_url": "https://api.siliconflow.cn/v1",
   "api_key": "sk-your-api-key",
@@ -157,7 +157,7 @@ POST /api/v1/asr
 | 字段 | 类型 | 必填 | 说明 |
 |------|------|------|------|
 | name | string | 是 | 模型显示名称 |
-| vendor | string | 是 | 供应商: "OpenAI" / "SiliconFlow" / "Paraformer" |
+| vendor | string | 是 | 供应商: "OpenAI Compatible" / "Paraformer" |
 | language | string | 是 | 语言: "zh" / "en" / "Multi-lingual" |
 | base_url | string | 是 | API Base URL |
 | api_key | string | 是 | API Key |
@@ -347,7 +347,7 @@ class ASRTestResponse(BaseModel):
 
 ```json
 {
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-xxx",
   "model_name": "whisper-1",
@@ -357,11 +357,11 @@ class ASRTestResponse(BaseModel):
 }
 ```
 
-### SiliconFlow Paraformer
+### OpenAI Compatible Paraformer
 
 ```json
 {
-  "vendor": "SiliconFlow",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.siliconflow.cn/v1",
   "api_key": "sf-xxx",
   "model_name": "paraformer-v2",
@@ -393,7 +393,7 @@ class ASRTestResponse(BaseModel):
 | test_filter_asr_models_by_language | 按语言过滤测试 |
 | test_filter_asr_models_by_enabled | 按启用状态过滤测试 |
 | test_create_asr_model_with_hotwords | 热词配置测试 |
-| test_test_asr_model_siliconflow | SiliconFlow 供应商测试 |
+| test_test_asr_model_siliconflow | OpenAI Compatible 供应商测试 |
 | test_test_asr_model_openai | OpenAI 供应商测试 |
 | test_different_asr_languages | 多语言测试 |
 | test_different_asr_vendors | 多供应商测试 |

api/docs/llm.md

@@ -20,7 +20,7 @@ interface LLMModel {
   id: string;           // 模型唯一标识 (8位UUID)
   user_id: number;      // 所属用户ID
   name: string;         // 模型显示名称
-  vendor: string;       // 供应商: "OpenAI" | "SiliconFlow" | "Dify" | "FastGPT" | 等
+  vendor: string;       // 供应商: "OpenAI Compatible" | "Dify" | "FastGPT" | 等
   type: string;        // 类型: "text" | "embedding" | "rerank"
   base_url: string;     // API Base URL
   api_key: string;      // API Key
@@ -64,7 +64,7 @@ GET /api/v1/llm
       "id": "abc12345",
       "user_id": 1,
       "name": "GPT-4o",
-      "vendor": "OpenAI",
+      "vendor": "OpenAI Compatible",
       "type": "text",
       "base_url": "https://api.openai.com/v1",
       "api_key": "sk-***",
@@ -79,7 +79,7 @@ GET /api/v1/llm
       "id": "def67890",
       "user_id": 1,
       "name": "Embedding-3-Small",
-      "vendor": "OpenAI",
+      "vendor": "OpenAI Compatible",
       "type": "embedding",
       "base_url": "https://api.openai.com/v1",
       "api_key": "sk-***",
@@ -111,7 +111,7 @@ GET /api/v1/llm/{id}
   "id": "abc12345",
   "user_id": 1,
   "name": "GPT-4o",
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "type": "text",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-***",
@@ -137,7 +137,7 @@ POST /api/v1/llm
 ```json
 {
   "name": "GPT-4o",
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "type": "text",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-your-api-key",
@@ -314,11 +314,11 @@ class LLMModelTestResponse(BaseModel):
 
 ## 供应商配置示例
 
-### OpenAI
+### OpenAI Compatible (OpenAI Endpoint)
 
 ```json
 {
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-xxx",
   "model_name": "gpt-4o",
@@ -327,11 +327,11 @@ class LLMModelTestResponse(BaseModel):
 }
 ```
 
-### SiliconFlow
+### OpenAI Compatible
 
 ```json
 {
-  "vendor": "SiliconFlow",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.siliconflow.com/v1",
   "api_key": "sf-xxx",
   "model_name": "deepseek-v3",
@@ -356,7 +356,7 @@ class LLMModelTestResponse(BaseModel):
 
 ```json
 {
-  "vendor": "OpenAI",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.openai.com/v1",
   "api_key": "sk-xxx",
   "model_name": "text-embedding-3-small",

api/docs/model-access.md

@@ -20,7 +20,7 @@ interface LLMModel {
   id: string;           // 模型唯一标识
   user_id: number;      // 所属用户ID
   name: string;         // 模型显示名称
-  vendor: string;       // 供应商: "OpenAI Compatible" | "SiliconFlow" | "Dify" | "FastGPT"
+  vendor: string;       // 供应商: "OpenAI Compatible" | "Dify" | "FastGPT"
   type: string;         // 类型: "text" | "embedding" | "rerank"
   base_url: string;     // API Base URL
   api_key: string;       // API Key
@@ -57,7 +57,7 @@ interface TTSModel {
   id: string;
   user_id: number;
   name: string;
-  vendor: string;       // "Ali" | "Volcano" | "Minimax" | "硅基流动"
+  vendor: string;       // "OpenAI Compatible" | "Ali" | "Volcano" | "Minimax"
   language: string;      // "zh" | "en"
   voice_list?: string[]; // 支持的声音列表
   enabled: boolean;
@@ -316,7 +316,6 @@ class LLMModelType(str, Enum):
 
 class LLMModelVendor(str, Enum):
     OPENAI_COMPATIBLE = "OpenAI Compatible"
-    SILICONFLOW = "SiliconFlow"
     DIFY = "Dify"
     FASTGPT = "FastGPT"
 
@@ -389,11 +388,11 @@ class ASRModelOut(ASRModelBase):
 }
 ```
 
-### SiliconFlow
+### OpenAI Compatible
 
 ```json
 {
-  "vendor": "SiliconFlow",
+  "vendor": "OpenAI Compatible",
   "base_url": "https://api.siliconflow.com/v1",
   "api_key": "sf-xxx",
   "model_name": "deepseek-v3"

api/init_db.py

@@ -135,21 +135,21 @@ def rebuild_vector_store(reset_doc_status: bool = True):
 def init_default_data():
     with db_session() as db:
         # 检查是否已有数据
-        # SiliconFlow CosyVoice 2.0 预设声音 (8个)
+        # OpenAI Compatible (SiliconFlow API) CosyVoice 2.0 预设声音 (8个)
         # 参考: https://docs.siliconflow.cn/cn/api-reference/audio/create-speech
         voices = [
             # 男声 (Male Voices)
-            Voice(id="alex", name="Alex", vendor="SiliconFlow", gender="Male", language="en",
+            Voice(id="alex", name="Alex", vendor="OpenAI Compatible", gender="Male", language="en",
                   description="Steady male voice.", is_system=True),
-            Voice(id="david", name="David", vendor="SiliconFlow", gender="Male", language="en",
+            Voice(id="david", name="David", vendor="OpenAI Compatible", gender="Male", language="en",
                   description="Cheerful male voice.", is_system=True),
             # 女声 (Female Voices)
-            Voice(id="bella", name="Bella", vendor="SiliconFlow", gender="Female", language="en",
+            Voice(id="bella", name="Bella", vendor="OpenAI Compatible", gender="Female", language="en",
                   description="Passionate female voice.", is_system=True),
-            Voice(id="claire", name="Claire", vendor="SiliconFlow", gender="Female", language="en",
+            Voice(id="claire", name="Claire", vendor="OpenAI Compatible", gender="Female", language="en",
                   description="Gentle female voice.", is_system=True),
         ]
-        seed_if_empty(db, Voice, voices, "✅ 默认声音数据已初始化 (SiliconFlow CosyVoice 2.0)")
+        seed_if_empty(db, Voice, voices, "✅ 默认声音数据已初始化 (OpenAI Compatible CosyVoice 2.0)")
 
 
 def init_default_tools(recreate: bool = False):
@@ -181,7 +181,7 @@ def init_default_assistants():
                 voice="anna",
                 speed=1.0,
                 hotwords=[],
-                tools=["calculator", "current_time"],
+                tools=["current_time"],
                 interruption_sensitivity=500,
                 config_mode="platform",
                 llm_model_id="deepseek-chat",
@@ -215,7 +215,7 @@ def init_default_assistants():
                 voice="alex",
                 speed=1.0,
                 hotwords=["grammar", "vocabulary", "practice"],
-                tools=["calculator"],
+                tools=["current_time"],
                 interruption_sensitivity=400,
                 config_mode="platform",
             ),
@@ -294,7 +294,7 @@ def init_default_llm_models():
                 id="deepseek-chat",
                 user_id=1,
                 name="DeepSeek Chat",
-                vendor="SiliconFlow",
+                vendor="OpenAI Compatible",
                 type="text",
                 base_url="https://api.deepseek.com",
                 api_key="YOUR_API_KEY",  # 用户需替换
@@ -320,7 +320,7 @@ def init_default_llm_models():
                 id="text-embedding-3-small",
                 user_id=1,
                 name="Embedding 3 Small",
-                vendor="OpenAI",
+                vendor="OpenAI Compatible",
                 type="embedding",
                 base_url="https://api.openai.com/v1",
                 api_key="YOUR_API_KEY",
@@ -339,7 +339,7 @@ def init_default_asr_models():
                 id="FunAudioLLM/SenseVoiceSmall",
                 user_id=1,
                 name="FunAudioLLM/SenseVoiceSmall",
-                vendor="SiliconFlow",
+                vendor="OpenAI Compatible",
                 language="Multi-lingual",
                 base_url="https://api.siliconflow.cn/v1",
                 api_key="YOUR_API_KEY",
@@ -353,7 +353,7 @@ def init_default_asr_models():
                 id="TeleAI/TeleSpeechASR",
                 user_id=1,
                 name="TeleAI/TeleSpeechASR",
-                vendor="SiliconFlow",
+                vendor="OpenAI Compatible",
                 language="Multi-lingual",
                 base_url="https://api.siliconflow.cn/v1",
                 api_key="YOUR_API_KEY",

engine/.env.example

@@ -41,19 +41,19 @@ LLM_MODEL=gpt-4o-mini
 LLM_TEMPERATURE=0.7
 
 # TTS
-# edge: no SiliconFlow key needed
+# edge: no API key needed
-# siliconflow: requires SILICONFLOW_API_KEY
+# openai_compatible: compatible with SiliconFlow-style endpoints
-TTS_PROVIDER=siliconflow
+TTS_PROVIDER=openai_compatible
 TTS_VOICE=anna
 TTS_SPEED=1.0
 
-# SiliconFlow (used by TTS and/or ASR when provider=siliconflow)
+# SiliconFlow (used by TTS and/or ASR when provider=openai_compatible)
 SILICONFLOW_API_KEY=your_siliconflow_api_key_here
 SILICONFLOW_TTS_MODEL=FunAudioLLM/CosyVoice2-0.5B
 SILICONFLOW_ASR_MODEL=FunAudioLLM/SenseVoiceSmall
 
 # ASR
-ASR_PROVIDER=siliconflow
+ASR_PROVIDER=openai_compatible
 # Interim cadence and minimum audio before interim decode.
 ASR_INTERIM_INTERVAL_MS=500
 ASR_MIN_AUDIO_MS=300

engine/app/config.py

@@ -44,7 +44,10 @@ class Settings(BaseSettings):
     llm_temperature: float = Field(default=0.7, description="LLM temperature for response generation")
     
     # TTS Configuration
-    tts_provider: str = Field(default="siliconflow", description="TTS provider (edge, siliconflow)")
+    tts_provider: str = Field(
+        default="openai_compatible",
+        description="TTS provider (edge, openai_compatible; siliconflow alias supported)"
+    )
     tts_voice: str = Field(default="anna", description="TTS voice name")
     tts_speed: float = Field(default=1.0, description="TTS speech speed multiplier")
     
@@ -53,7 +56,10 @@ class Settings(BaseSettings):
     siliconflow_tts_model: str = Field(default="FunAudioLLM/CosyVoice2-0.5B", description="SiliconFlow TTS model")
     
     # ASR Configuration
-    asr_provider: str = Field(default="siliconflow", description="ASR provider (siliconflow, buffered)")
+    asr_provider: str = Field(
+        default="openai_compatible",
+        description="ASR provider (openai_compatible, buffered; siliconflow alias supported)"
+    )
     siliconflow_asr_model: str = Field(default="FunAudioLLM/SenseVoiceSmall", description="SiliconFlow ASR model")
     asr_interim_interval_ms: int = Field(default=500, description="Interval for interim ASR results in ms")
     asr_min_audio_ms: int = Field(default=300, description="Minimum audio duration before first ASR result")

engine/core/duplex_pipeline.py

@@ -30,8 +30,8 @@ from processors.vad import SileroVAD, VADProcessor
 from services.asr import BufferedASRService
 from services.base import BaseASRService, BaseLLMService, BaseTTSService, LLMMessage, LLMStreamEvent
 from services.llm import MockLLMService, OpenAILLMService
-from services.siliconflow_asr import SiliconFlowASRService
+from services.openai_compatible_asr import OpenAICompatibleASRService
-from services.siliconflow_tts import SiliconFlowTTSService
+from services.openai_compatible_tts import OpenAICompatibleTTSService
 from services.streaming_text import extract_tts_sentence, has_spoken_content
 from services.tts import EdgeTTSService, MockTTSService
 
@@ -60,57 +60,6 @@ class DuplexPipeline:
     _TOOL_WAIT_TIMEOUT_SECONDS = 15.0
     _SERVER_TOOL_TIMEOUT_SECONDS = 15.0
     _DEFAULT_TOOL_SCHEMAS: Dict[str, Dict[str, Any]] = {
-        "search": {
-            "name": "search",
-            "description": "Search the internet for recent information",
-            "parameters": {
-                "type": "object",
-                "properties": {"query": {"type": "string"}},
-                "required": ["query"],
-            },
-        },
-        "calculator": {
-            "name": "calculator",
-            "description": "Evaluate a math expression",
-            "parameters": {
-                "type": "object",
-                "properties": {"expression": {"type": "string"}},
-                "required": ["expression"],
-            },
-        },
-        "weather": {
-            "name": "weather",
-            "description": "Get weather by city name",
-            "parameters": {
-                "type": "object",
-                "properties": {"city": {"type": "string"}},
-                "required": ["city"],
-            },
-        },
-        "translate": {
-            "name": "translate",
-            "description": "Translate text to target language",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "text": {"type": "string"},
-                    "target_lang": {"type": "string"},
-                },
-                "required": ["text", "target_lang"],
-            },
-        },
-        "knowledge": {
-            "name": "knowledge",
-            "description": "Query knowledge base by question",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "query": {"type": "string"},
-                    "kb_id": {"type": "string"},
-                },
-                "required": ["query"],
-            },
-        },
         "current_time": {
             "name": "current_time",
             "description": "Get current local time",
@@ -120,51 +69,6 @@ class DuplexPipeline:
                 "required": [],
             },
         },
-        "code_interpreter": {
-            "name": "code_interpreter",
-            "description": "Execute Python code in a controlled environment",
-            "parameters": {
-                "type": "object",
-                "properties": {"code": {"type": "string"}},
-                "required": ["code"],
-            },
-        },
-        "turn_on_camera": {
-            "name": "turn_on_camera",
-            "description": "Turn on camera on client device",
-            "parameters": {
-                "type": "object",
-                "properties": {},
-                "required": [],
-            },
-        },
-        "turn_off_camera": {
-            "name": "turn_off_camera",
-            "description": "Turn off camera on client device",
-            "parameters": {
-                "type": "object",
-                "properties": {},
-                "required": [],
-            },
-        },
-        "increase_volume": {
-            "name": "increase_volume",
-            "description": "Increase speaker volume",
-            "parameters": {
-                "type": "object",
-                "properties": {"step": {"type": "integer"}},
-                "required": [],
-            },
-        },
-        "decrease_volume": {
-            "name": "decrease_volume",
-            "description": "Decrease speaker volume",
-            "parameters": {
-                "type": "object",
-                "properties": {"step": {"type": "integer"}},
-                "required": [],
-            },
-        },
     }
 
     def __init__(
@@ -386,6 +290,11 @@ class DuplexPipeline:
                 return False
         return None
 
+    @staticmethod
+    def _is_openai_compatible_provider(provider: Any) -> bool:
+        normalized = str(provider or "").strip().lower()
+        return normalized in {"openai_compatible", "openai-compatible", "siliconflow"}
+
     def _tts_output_enabled(self) -> bool:
         enabled = self._coerce_bool(self._runtime_tts.get("enabled"))
         if enabled is not None:
@@ -495,15 +404,15 @@ class DuplexPipeline:
                     tts_model = self._runtime_tts.get("model") or settings.siliconflow_tts_model
                     tts_speed = float(self._runtime_tts.get("speed") or settings.tts_speed)
 
-                    if tts_provider == "siliconflow" and tts_api_key:
+                    if self._is_openai_compatible_provider(tts_provider) and tts_api_key:
-                        self.tts_service = SiliconFlowTTSService(
+                        self.tts_service = OpenAICompatibleTTSService(
                             api_key=tts_api_key,
                             voice=tts_voice,
                             model=tts_model,
                             sample_rate=settings.sample_rate,
                             speed=tts_speed
                         )
-                        logger.info("Using SiliconFlow TTS service")
+                        logger.info("Using OpenAI-compatible TTS service (SiliconFlow implementation)")
                     else:
                         self.tts_service = EdgeTTSService(
                             voice=tts_voice,
@@ -531,8 +440,8 @@ class DuplexPipeline:
                 asr_interim_interval = int(self._runtime_asr.get("interimIntervalMs") or settings.asr_interim_interval_ms)
                 asr_min_audio_ms = int(self._runtime_asr.get("minAudioMs") or settings.asr_min_audio_ms)
 
-                if asr_provider == "siliconflow" and asr_api_key:
+                if self._is_openai_compatible_provider(asr_provider) and asr_api_key:
-                    self.asr_service = SiliconFlowASRService(
+                    self.asr_service = OpenAICompatibleASRService(
                         api_key=asr_api_key,
                         model=asr_model,
                         sample_rate=settings.sample_rate,
@@ -540,7 +449,7 @@ class DuplexPipeline:
                         min_audio_for_interim_ms=asr_min_audio_ms,
                         on_transcript=self._on_transcript_callback
                     )
-                    logger.info("Using SiliconFlow ASR service")
+                    logger.info("Using OpenAI-compatible ASR service (SiliconFlow implementation)")
                 else:
                     self.asr_service = BufferedASRService(
                         sample_rate=settings.sample_rate

engine/docs/ws_v1_schema.md

@@ -66,7 +66,7 @@ Rules:
         "baseUrl": "https://api.openai.com/v1"
       },
       "asr": {
-        "provider": "siliconflow",
+        "provider": "openai_compatible",
         "model": "FunAudioLLM/SenseVoiceSmall",
         "apiKey": "sf-...",
         "interimIntervalMs": 500,
@@ -74,7 +74,7 @@ Rules:
       },
       "tts": {
         "enabled": true,
-        "provider": "siliconflow",
+        "provider": "openai_compatible",
         "model": "FunAudioLLM/CosyVoice2-0.5B",
         "apiKey": "sf-...",
         "voice": "anna",

engine/services/__init__.py

@@ -15,8 +15,8 @@ from services.base import (
 from services.llm import OpenAILLMService, MockLLMService
 from services.tts import EdgeTTSService, MockTTSService
 from services.asr import BufferedASRService, MockASRService
-from services.siliconflow_asr import SiliconFlowASRService
+from services.openai_compatible_asr import OpenAICompatibleASRService, SiliconFlowASRService
-from services.siliconflow_tts import SiliconFlowTTSService
+from services.openai_compatible_tts import OpenAICompatibleTTSService, SiliconFlowTTSService
 from services.streaming_tts_adapter import StreamingTTSAdapter
 from services.realtime import RealtimeService, RealtimeConfig, RealtimePipeline
 
@@ -38,8 +38,10 @@ __all__ = [
     # ASR
     "BufferedASRService",
     "MockASRService",
+    "OpenAICompatibleASRService",
     "SiliconFlowASRService",
     # TTS (SiliconFlow)
+    "OpenAICompatibleTTSService",
     "SiliconFlowTTSService",
     "StreamingTTSAdapter",
     # Realtime

engine/services/openai_compatible_asr.py

@@ -0,0 +1,321 @@
+"""OpenAI-compatible ASR (Automatic Speech Recognition) Service.
+
+Uses the SiliconFlow API for speech-to-text transcription.
+API: https://docs.siliconflow.cn/cn/api-reference/audio/create-audio-transcriptions
+"""
+
+import asyncio
+import io
+import wave
+from typing import AsyncIterator, Optional, Callable, Awaitable
+from loguru import logger
+
+try:
+    import aiohttp
+    AIOHTTP_AVAILABLE = True
+except ImportError:
+    AIOHTTP_AVAILABLE = False
+    logger.warning("aiohttp not available - OpenAICompatibleASRService will not work")
+
+from services.base import BaseASRService, ASRResult, ServiceState
+
+
+class OpenAICompatibleASRService(BaseASRService):
+    """
+    OpenAI-compatible ASR service for speech-to-text transcription.
+    
+    Features:
+    - Buffers incoming audio chunks
+    - Provides interim transcriptions periodically (for streaming to client)
+    - Final transcription on EOU
+    
+    API Details:
+    - Endpoint: POST https://api.siliconflow.cn/v1/audio/transcriptions
+    - Models: FunAudioLLM/SenseVoiceSmall (default), TeleAI/TeleSpeechASR
+    - Input: Audio file (multipart/form-data)
+    - Output: {"text": "transcribed text"}
+    """
+    
+    # Supported models
+    MODELS = {
+        "sensevoice": "FunAudioLLM/SenseVoiceSmall",
+        "telespeech": "TeleAI/TeleSpeechASR",
+    }
+    
+    API_URL = "https://api.siliconflow.cn/v1/audio/transcriptions"
+    
+    def __init__(
+        self,
+        api_key: str,
+        model: str = "FunAudioLLM/SenseVoiceSmall",
+        sample_rate: int = 16000,
+        language: str = "auto",
+        interim_interval_ms: int = 500,  # How often to send interim results
+        min_audio_for_interim_ms: int = 300,  # Min audio before first interim
+        on_transcript: Optional[Callable[[str, bool], Awaitable[None]]] = None
+    ):
+        """
+        Initialize OpenAI-compatible ASR service.
+        
+        Args:
+            api_key: Provider API key
+            model: ASR model name or alias
+            sample_rate: Audio sample rate (16000 recommended)
+            language: Language code (auto for automatic detection)
+            interim_interval_ms: How often to generate interim transcriptions
+            min_audio_for_interim_ms: Minimum audio duration before first interim
+            on_transcript: Callback for transcription results (text, is_final)
+        """
+        super().__init__(sample_rate=sample_rate, language=language)
+        
+        if not AIOHTTP_AVAILABLE:
+            raise RuntimeError("aiohttp is required for OpenAICompatibleASRService")
+        
+        self.api_key = api_key
+        self.model = self.MODELS.get(model.lower(), model)
+        self.interim_interval_ms = interim_interval_ms
+        self.min_audio_for_interim_ms = min_audio_for_interim_ms
+        self.on_transcript = on_transcript
+        
+        # Session
+        self._session: Optional[aiohttp.ClientSession] = None
+        
+        # Audio buffer
+        self._audio_buffer: bytes = b""
+        self._current_text: str = ""
+        self._last_interim_time: float = 0
+        
+        # Transcript queue for async iteration
+        self._transcript_queue: asyncio.Queue[ASRResult] = asyncio.Queue()
+        
+        # Background task for interim results
+        self._interim_task: Optional[asyncio.Task] = None
+        self._running = False
+        
+        logger.info(f"OpenAICompatibleASRService initialized with model: {self.model}")
+    
+    async def connect(self) -> None:
+        """Connect to the service."""
+        self._session = aiohttp.ClientSession(
+            headers={
+                "Authorization": f"Bearer {self.api_key}"
+            }
+        )
+        self._running = True
+        self.state = ServiceState.CONNECTED
+        logger.info("OpenAICompatibleASRService connected")
+    
+    async def disconnect(self) -> None:
+        """Disconnect and cleanup."""
+        self._running = False
+        
+        if self._interim_task:
+            self._interim_task.cancel()
+            try:
+                await self._interim_task
+            except asyncio.CancelledError:
+                pass
+            self._interim_task = None
+        
+        if self._session:
+            await self._session.close()
+            self._session = None
+        
+        self._audio_buffer = b""
+        self._current_text = ""
+        self.state = ServiceState.DISCONNECTED
+        logger.info("OpenAICompatibleASRService disconnected")
+    
+    async def send_audio(self, audio: bytes) -> None:
+        """
+        Buffer incoming audio data.
+        
+        Args:
+            audio: PCM audio data (16-bit, mono)
+        """
+        self._audio_buffer += audio
+    
+    async def transcribe_buffer(self, is_final: bool = False) -> Optional[str]:
+        """
+        Transcribe current audio buffer.
+        
+        Args:
+            is_final: Whether this is the final transcription
+            
+        Returns:
+            Transcribed text or None if not enough audio
+        """
+        if not self._session:
+            logger.warning("ASR session not connected")
+            return None
+        
+        # Check minimum audio duration
+        audio_duration_ms = len(self._audio_buffer) / (self.sample_rate * 2) * 1000
+        
+        if not is_final and audio_duration_ms < self.min_audio_for_interim_ms:
+            return None
+        
+        if audio_duration_ms < 100:  # Less than 100ms - too short
+            return None
+        
+        try:
+            # Convert PCM to WAV in memory
+            wav_buffer = io.BytesIO()
+            with wave.open(wav_buffer, 'wb') as wav_file:
+                wav_file.setnchannels(1)
+                wav_file.setsampwidth(2)  # 16-bit
+                wav_file.setframerate(self.sample_rate)
+                wav_file.writeframes(self._audio_buffer)
+            
+            wav_buffer.seek(0)
+            wav_data = wav_buffer.read()
+            
+            # Send to API
+            form_data = aiohttp.FormData()
+            form_data.add_field(
+                'file',
+                wav_data,
+                filename='audio.wav',
+                content_type='audio/wav'
+            )
+            form_data.add_field('model', self.model)
+            
+            async with self._session.post(self.API_URL, data=form_data) as response:
+                if response.status == 200:
+                    result = await response.json()
+                    text = result.get("text", "").strip()
+                    
+                    if text:
+                        self._current_text = text
+                        
+                        # Notify via callback
+                        if self.on_transcript:
+                            await self.on_transcript(text, is_final)
+                        
+                        # Queue result
+                        await self._transcript_queue.put(
+                            ASRResult(text=text, is_final=is_final)
+                        )
+                        
+                        logger.debug(f"ASR {'final' if is_final else 'interim'}: {text[:50]}...")
+                        return text
+                else:
+                    error_text = await response.text()
+                    logger.error(f"ASR API error {response.status}: {error_text}")
+                    return None
+                    
+        except Exception as e:
+            logger.error(f"ASR transcription error: {e}")
+            return None
+    
+    async def get_final_transcription(self) -> str:
+        """
+        Get final transcription and clear buffer.
+        
+        Call this when EOU is detected.
+        
+        Returns:
+            Final transcribed text
+        """
+        # Transcribe full buffer as final
+        text = await self.transcribe_buffer(is_final=True)
+        
+        # Clear buffer
+        result = text or self._current_text
+        self._audio_buffer = b""
+        self._current_text = ""
+        
+        return result
+    
+    def get_and_clear_text(self) -> str:
+        """
+        Get accumulated text and clear buffer.
+        
+        Compatible with BufferedASRService interface.
+        """
+        text = self._current_text
+        self._current_text = ""
+        self._audio_buffer = b""
+        return text
+    
+    def get_audio_buffer(self) -> bytes:
+        """Get current audio buffer."""
+        return self._audio_buffer
+    
+    def get_audio_duration_ms(self) -> float:
+        """Get current audio buffer duration in milliseconds."""
+        return len(self._audio_buffer) / (self.sample_rate * 2) * 1000
+    
+    def clear_buffer(self) -> None:
+        """Clear audio and text buffers."""
+        self._audio_buffer = b""
+        self._current_text = ""
+    
+    async def receive_transcripts(self) -> AsyncIterator[ASRResult]:
+        """
+        Async iterator for transcription results.
+        
+        Yields:
+            ASRResult with text and is_final flag
+        """
+        while self._running:
+            try:
+                result = await asyncio.wait_for(
+                    self._transcript_queue.get(),
+                    timeout=0.1
+                )
+                yield result
+            except asyncio.TimeoutError:
+                continue
+            except asyncio.CancelledError:
+                break
+    
+    async def start_interim_transcription(self) -> None:
+        """
+        Start background task for interim transcriptions.
+        
+        This periodically transcribes buffered audio for
+        real-time feedback to the user.
+        """
+        if self._interim_task and not self._interim_task.done():
+            return
+        
+        self._interim_task = asyncio.create_task(self._interim_loop())
+    
+    async def stop_interim_transcription(self) -> None:
+        """Stop interim transcription task."""
+        if self._interim_task:
+            self._interim_task.cancel()
+            try:
+                await self._interim_task
+            except asyncio.CancelledError:
+                pass
+            self._interim_task = None
+    
+    async def _interim_loop(self) -> None:
+        """Background loop for interim transcriptions."""
+        import time
+        
+        while self._running:
+            try:
+                await asyncio.sleep(self.interim_interval_ms / 1000)
+                
+                # Check if we have enough new audio
+                current_time = time.time()
+                time_since_last = (current_time - self._last_interim_time) * 1000
+                
+                if time_since_last >= self.interim_interval_ms:
+                    audio_duration = self.get_audio_duration_ms()
+                    
+                    if audio_duration >= self.min_audio_for_interim_ms:
+                        await self.transcribe_buffer(is_final=False)
+                        self._last_interim_time = current_time
+                        
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.error(f"Interim transcription error: {e}")
+
+
+# Backward-compatible alias
+SiliconFlowASRService = OpenAICompatibleASRService

engine/services/openai_compatible_tts.py

@@ -0,0 +1,315 @@
+"""OpenAI-compatible TTS Service with streaming support.
+
+Uses SiliconFlow's CosyVoice2 or MOSS-TTSD models for low-latency
+text-to-speech synthesis with streaming.
+
+API Docs: https://docs.siliconflow.cn/cn/api-reference/audio/create-speech
+"""
+
+import os
+import asyncio
+import aiohttp
+from typing import AsyncIterator, Optional
+from loguru import logger
+
+from services.base import BaseTTSService, TTSChunk, ServiceState
+from services.streaming_tts_adapter import StreamingTTSAdapter  # backward-compatible re-export
+
+
+class OpenAICompatibleTTSService(BaseTTSService):
+    """
+    OpenAI-compatible TTS service with streaming support.
+    
+    Supports CosyVoice2-0.5B and MOSS-TTSD-v0.5 models.
+    """
+    
+    # Available voices
+    VOICES = {
+        "alex": "FunAudioLLM/CosyVoice2-0.5B:alex",
+        "anna": "FunAudioLLM/CosyVoice2-0.5B:anna",
+        "bella": "FunAudioLLM/CosyVoice2-0.5B:bella",
+        "benjamin": "FunAudioLLM/CosyVoice2-0.5B:benjamin",
+        "charles": "FunAudioLLM/CosyVoice2-0.5B:charles",
+        "claire": "FunAudioLLM/CosyVoice2-0.5B:claire",
+        "david": "FunAudioLLM/CosyVoice2-0.5B:david",
+        "diana": "FunAudioLLM/CosyVoice2-0.5B:diana",
+    }
+    
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        voice: str = "anna",
+        model: str = "FunAudioLLM/CosyVoice2-0.5B",
+        sample_rate: int = 16000,
+        speed: float = 1.0
+    ):
+        """
+        Initialize OpenAI-compatible TTS service.
+        
+        Args:
+            api_key: Provider API key (defaults to SILICONFLOW_API_KEY env var)
+            voice: Voice name (alex, anna, bella, benjamin, charles, claire, david, diana)
+            model: Model name
+            sample_rate: Output sample rate (8000, 16000, 24000, 32000, 44100)
+            speed: Speech speed (0.25 to 4.0)
+        """
+        # Resolve voice name
+        if voice in self.VOICES:
+            full_voice = self.VOICES[voice]
+        else:
+            full_voice = voice
+            
+        super().__init__(voice=full_voice, sample_rate=sample_rate, speed=speed)
+        
+        self.api_key = api_key or os.getenv("SILICONFLOW_API_KEY")
+        self.model = model
+        self.api_url = "https://api.siliconflow.cn/v1/audio/speech"
+        
+        self._session: Optional[aiohttp.ClientSession] = None
+        self._cancel_event = asyncio.Event()
+    
+    async def connect(self) -> None:
+        """Initialize HTTP session."""
+        if not self.api_key:
+            raise ValueError("SiliconFlow API key not provided. Set SILICONFLOW_API_KEY env var.")
+        
+        self._session = aiohttp.ClientSession(
+            headers={
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json"
+            }
+        )
+        self.state = ServiceState.CONNECTED
+        logger.info(f"SiliconFlow TTS service ready: voice={self.voice}, model={self.model}")
+    
+    async def disconnect(self) -> None:
+        """Close HTTP session."""
+        if self._session:
+            await self._session.close()
+            self._session = None
+        self.state = ServiceState.DISCONNECTED
+        logger.info("SiliconFlow TTS service disconnected")
+    
+    async def synthesize(self, text: str) -> bytes:
+        """Synthesize complete audio for text."""
+        audio_data = b""
+        async for chunk in self.synthesize_stream(text):
+            audio_data += chunk.audio
+        return audio_data
+    
+    async def synthesize_stream(self, text: str) -> AsyncIterator[TTSChunk]:
+        """
+        Synthesize audio in streaming mode.
+        
+        Args:
+            text: Text to synthesize
+            
+        Yields:
+            TTSChunk objects with PCM audio
+        """
+        if not self._session:
+            raise RuntimeError("TTS service not connected")
+        
+        if not text.strip():
+            return
+        
+        self._cancel_event.clear()
+        
+        payload = {
+            "model": self.model,
+            "input": text,
+            "voice": self.voice,
+            "response_format": "pcm",
+            "sample_rate": self.sample_rate,
+            "stream": True,
+            "speed": self.speed
+        }
+        
+        try:
+            async with self._session.post(self.api_url, json=payload) as response:
+                if response.status != 200:
+                    error_text = await response.text()
+                    logger.error(f"SiliconFlow TTS error: {response.status} - {error_text}")
+                    return
+                
+                # Stream audio chunks
+                chunk_size = self.sample_rate * 2 // 10  # 100ms chunks
+                buffer = b""
+                pending_chunk = None
+                
+                async for chunk in response.content.iter_any():
+                    if self._cancel_event.is_set():
+                        logger.info("TTS synthesis cancelled")
+                        return
+                    
+                    buffer += chunk
+                    
+                    # Yield complete chunks
+                    while len(buffer) >= chunk_size:
+                        audio_chunk = buffer[:chunk_size]
+                        buffer = buffer[chunk_size:]
+
+                        # Keep one full chunk buffered so we can always tag the true
+                        # last full chunk as final when stream length is an exact multiple.
+                        if pending_chunk is not None:
+                            yield TTSChunk(
+                                audio=pending_chunk,
+                                sample_rate=self.sample_rate,
+                                is_final=False
+                            )
+                        pending_chunk = audio_chunk
+                
+                # Flush pending chunk(s) and remaining tail.
+                if pending_chunk is not None:
+                    if buffer:
+                        yield TTSChunk(
+                            audio=pending_chunk,
+                            sample_rate=self.sample_rate,
+                            is_final=False
+                        )
+                        pending_chunk = None
+                    else:
+                        yield TTSChunk(
+                            audio=pending_chunk,
+                            sample_rate=self.sample_rate,
+                            is_final=True
+                        )
+                        pending_chunk = None
+
+                if buffer:
+                    yield TTSChunk(
+                        audio=buffer,
+                        sample_rate=self.sample_rate,
+                        is_final=True
+                    )
+                    
+        except asyncio.CancelledError:
+            logger.info("TTS synthesis cancelled via asyncio")
+            raise
+        except Exception as e:
+            logger.error(f"TTS synthesis error: {e}")
+            raise
+    
+    async def cancel(self) -> None:
+        """Cancel ongoing synthesis."""
+        self._cancel_event.set()
+
+
+class StreamingTTSAdapter:
+    """
+    Adapter for streaming LLM text to TTS with sentence-level chunking.
+    
+    This reduces latency by starting TTS as soon as a complete sentence
+    is received from the LLM, rather than waiting for the full response.
+    """
+    
+    # Sentence delimiters
+    SENTENCE_ENDS = {'，', '。', '！', '？', '.', '!', '?', '\n'}
+    
+    def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
+        self.tts_service = tts_service
+        self.transport = transport
+        self.session_id = session_id
+        self._buffer = ""
+        self._cancel_event = asyncio.Event()
+        self._is_speaking = False
+
+    def _is_non_sentence_period(self, text: str, idx: int) -> bool:
+        """Check whether '.' should NOT be treated as a sentence delimiter."""
+        if text[idx] != ".":
+            return False
+
+        # Decimal/version segment: 1.2, v1.2.3
+        if idx > 0 and idx < len(text) - 1 and text[idx - 1].isdigit() and text[idx + 1].isdigit():
+            return True
+
+        # Number abbreviations: No.1 / No. 1
+        left_start = idx - 1
+        while left_start >= 0 and text[left_start].isalpha():
+            left_start -= 1
+        left_token = text[left_start + 1:idx].lower()
+        if left_token == "no":
+            j = idx + 1
+            while j < len(text) and text[j].isspace():
+                j += 1
+            if j < len(text) and text[j].isdigit():
+                return True
+
+        return False
+    
+    async def process_text_chunk(self, text_chunk: str) -> None:
+        """
+        Process a text chunk from LLM and trigger TTS when sentence is complete.
+        
+        Args:
+            text_chunk: Text chunk from LLM streaming
+        """
+        if self._cancel_event.is_set():
+            return
+        
+        self._buffer += text_chunk
+        
+        # Check for sentence completion
+        while True:
+            split_idx = -1
+            for i, char in enumerate(self._buffer):
+                if char == "." and self._is_non_sentence_period(self._buffer, i):
+                    continue
+                if char in self.SENTENCE_ENDS:
+                    split_idx = i
+                    break
+            if split_idx < 0:
+                break
+
+            end_idx = split_idx + 1
+            while end_idx < len(self._buffer) and self._buffer[end_idx] in self.SENTENCE_ENDS:
+                end_idx += 1
+
+            sentence = self._buffer[:end_idx].strip()
+            self._buffer = self._buffer[end_idx:]
+
+            if sentence and any(ch.isalnum() for ch in sentence):
+                await self._speak_sentence(sentence)
+    
+    async def flush(self) -> None:
+        """Flush remaining buffer."""
+        if self._buffer.strip() and not self._cancel_event.is_set():
+            await self._speak_sentence(self._buffer.strip())
+        self._buffer = ""
+    
+    async def _speak_sentence(self, text: str) -> None:
+        """Synthesize and send a sentence."""
+        if not text or self._cancel_event.is_set():
+            return
+        
+        self._is_speaking = True
+        
+        try:
+            async for chunk in self.tts_service.synthesize_stream(text):
+                if self._cancel_event.is_set():
+                    break
+                await self.transport.send_audio(chunk.audio)
+                await asyncio.sleep(0.01)  # Prevent flooding
+        except Exception as e:
+            logger.error(f"TTS speak error: {e}")
+        finally:
+            self._is_speaking = False
+    
+    def cancel(self) -> None:
+        """Cancel ongoing speech."""
+        self._cancel_event.set()
+        self._buffer = ""
+    
+    def reset(self) -> None:
+        """Reset for new turn."""
+        self._cancel_event.clear()
+        self._buffer = ""
+        self._is_speaking = False
+    
+    @property
+    def is_speaking(self) -> bool:
+        return self._is_speaking
+
+
+# Backward-compatible alias
+SiliconFlowTTSService = OpenAICompatibleTTSService

engine/services/siliconflow_asr.py

@@ -1,317 +1,8 @@
-"""SiliconFlow ASR (Automatic Speech Recognition) Service.
+"""Backward-compatible imports for legacy siliconflow_asr module."""
 
-Uses the SiliconFlow API for speech-to-text transcription.
+from services.openai_compatible_asr import OpenAICompatibleASRService
-API: https://docs.siliconflow.cn/cn/api-reference/audio/create-audio-transcriptions
-"""
 
-import asyncio
+# Backward-compatible alias
-import io
+SiliconFlowASRService = OpenAICompatibleASRService
-import wave
-from typing import AsyncIterator, Optional, Callable, Awaitable
-from loguru import logger
 
-try:
+__all__ = ["OpenAICompatibleASRService", "SiliconFlowASRService"]
-    import aiohttp
-    AIOHTTP_AVAILABLE = True
-except ImportError:
-    AIOHTTP_AVAILABLE = False
-    logger.warning("aiohttp not available - SiliconFlowASRService will not work")
-
-from services.base import BaseASRService, ASRResult, ServiceState
-
-
-class SiliconFlowASRService(BaseASRService):
-    """
-    SiliconFlow ASR service for speech-to-text transcription.
-    
-    Features:
-    - Buffers incoming audio chunks
-    - Provides interim transcriptions periodically (for streaming to client)
-    - Final transcription on EOU
-    
-    API Details:
-    - Endpoint: POST https://api.siliconflow.cn/v1/audio/transcriptions
-    - Models: FunAudioLLM/SenseVoiceSmall (default), TeleAI/TeleSpeechASR
-    - Input: Audio file (multipart/form-data)
-    - Output: {"text": "transcribed text"}
-    """
-    
-    # Supported models
-    MODELS = {
-        "sensevoice": "FunAudioLLM/SenseVoiceSmall",
-        "telespeech": "TeleAI/TeleSpeechASR",
-    }
-    
-    API_URL = "https://api.siliconflow.cn/v1/audio/transcriptions"
-    
-    def __init__(
-        self,
-        api_key: str,
-        model: str = "FunAudioLLM/SenseVoiceSmall",
-        sample_rate: int = 16000,
-        language: str = "auto",
-        interim_interval_ms: int = 500,  # How often to send interim results
-        min_audio_for_interim_ms: int = 300,  # Min audio before first interim
-        on_transcript: Optional[Callable[[str, bool], Awaitable[None]]] = None
-    ):
-        """
-        Initialize SiliconFlow ASR service.
-        
-        Args:
-            api_key: SiliconFlow API key
-            model: ASR model name or alias
-            sample_rate: Audio sample rate (16000 recommended)
-            language: Language code (auto for automatic detection)
-            interim_interval_ms: How often to generate interim transcriptions
-            min_audio_for_interim_ms: Minimum audio duration before first interim
-            on_transcript: Callback for transcription results (text, is_final)
-        """
-        super().__init__(sample_rate=sample_rate, language=language)
-        
-        if not AIOHTTP_AVAILABLE:
-            raise RuntimeError("aiohttp is required for SiliconFlowASRService")
-        
-        self.api_key = api_key
-        self.model = self.MODELS.get(model.lower(), model)
-        self.interim_interval_ms = interim_interval_ms
-        self.min_audio_for_interim_ms = min_audio_for_interim_ms
-        self.on_transcript = on_transcript
-        
-        # Session
-        self._session: Optional[aiohttp.ClientSession] = None
-        
-        # Audio buffer
-        self._audio_buffer: bytes = b""
-        self._current_text: str = ""
-        self._last_interim_time: float = 0
-        
-        # Transcript queue for async iteration
-        self._transcript_queue: asyncio.Queue[ASRResult] = asyncio.Queue()
-        
-        # Background task for interim results
-        self._interim_task: Optional[asyncio.Task] = None
-        self._running = False
-        
-        logger.info(f"SiliconFlowASRService initialized with model: {self.model}")
-    
-    async def connect(self) -> None:
-        """Connect to the service."""
-        self._session = aiohttp.ClientSession(
-            headers={
-                "Authorization": f"Bearer {self.api_key}"
-            }
-        )
-        self._running = True
-        self.state = ServiceState.CONNECTED
-        logger.info("SiliconFlowASRService connected")
-    
-    async def disconnect(self) -> None:
-        """Disconnect and cleanup."""
-        self._running = False
-        
-        if self._interim_task:
-            self._interim_task.cancel()
-            try:
-                await self._interim_task
-            except asyncio.CancelledError:
-                pass
-            self._interim_task = None
-        
-        if self._session:
-            await self._session.close()
-            self._session = None
-        
-        self._audio_buffer = b""
-        self._current_text = ""
-        self.state = ServiceState.DISCONNECTED
-        logger.info("SiliconFlowASRService disconnected")
-    
-    async def send_audio(self, audio: bytes) -> None:
-        """
-        Buffer incoming audio data.
-        
-        Args:
-            audio: PCM audio data (16-bit, mono)
-        """
-        self._audio_buffer += audio
-    
-    async def transcribe_buffer(self, is_final: bool = False) -> Optional[str]:
-        """
-        Transcribe current audio buffer.
-        
-        Args:
-            is_final: Whether this is the final transcription
-            
-        Returns:
-            Transcribed text or None if not enough audio
-        """
-        if not self._session:
-            logger.warning("ASR session not connected")
-            return None
-        
-        # Check minimum audio duration
-        audio_duration_ms = len(self._audio_buffer) / (self.sample_rate * 2) * 1000
-        
-        if not is_final and audio_duration_ms < self.min_audio_for_interim_ms:
-            return None
-        
-        if audio_duration_ms < 100:  # Less than 100ms - too short
-            return None
-        
-        try:
-            # Convert PCM to WAV in memory
-            wav_buffer = io.BytesIO()
-            with wave.open(wav_buffer, 'wb') as wav_file:
-                wav_file.setnchannels(1)
-                wav_file.setsampwidth(2)  # 16-bit
-                wav_file.setframerate(self.sample_rate)
-                wav_file.writeframes(self._audio_buffer)
-            
-            wav_buffer.seek(0)
-            wav_data = wav_buffer.read()
-            
-            # Send to API
-            form_data = aiohttp.FormData()
-            form_data.add_field(
-                'file',
-                wav_data,
-                filename='audio.wav',
-                content_type='audio/wav'
-            )
-            form_data.add_field('model', self.model)
-            
-            async with self._session.post(self.API_URL, data=form_data) as response:
-                if response.status == 200:
-                    result = await response.json()
-                    text = result.get("text", "").strip()
-                    
-                    if text:
-                        self._current_text = text
-                        
-                        # Notify via callback
-                        if self.on_transcript:
-                            await self.on_transcript(text, is_final)
-                        
-                        # Queue result
-                        await self._transcript_queue.put(
-                            ASRResult(text=text, is_final=is_final)
-                        )
-                        
-                        logger.debug(f"ASR {'final' if is_final else 'interim'}: {text[:50]}...")
-                        return text
-                else:
-                    error_text = await response.text()
-                    logger.error(f"ASR API error {response.status}: {error_text}")
-                    return None
-                    
-        except Exception as e:
-            logger.error(f"ASR transcription error: {e}")
-            return None
-    
-    async def get_final_transcription(self) -> str:
-        """
-        Get final transcription and clear buffer.
-        
-        Call this when EOU is detected.
-        
-        Returns:
-            Final transcribed text
-        """
-        # Transcribe full buffer as final
-        text = await self.transcribe_buffer(is_final=True)
-        
-        # Clear buffer
-        result = text or self._current_text
-        self._audio_buffer = b""
-        self._current_text = ""
-        
-        return result
-    
-    def get_and_clear_text(self) -> str:
-        """
-        Get accumulated text and clear buffer.
-        
-        Compatible with BufferedASRService interface.
-        """
-        text = self._current_text
-        self._current_text = ""
-        self._audio_buffer = b""
-        return text
-    
-    def get_audio_buffer(self) -> bytes:
-        """Get current audio buffer."""
-        return self._audio_buffer
-    
-    def get_audio_duration_ms(self) -> float:
-        """Get current audio buffer duration in milliseconds."""
-        return len(self._audio_buffer) / (self.sample_rate * 2) * 1000
-    
-    def clear_buffer(self) -> None:
-        """Clear audio and text buffers."""
-        self._audio_buffer = b""
-        self._current_text = ""
-    
-    async def receive_transcripts(self) -> AsyncIterator[ASRResult]:
-        """
-        Async iterator for transcription results.
-        
-        Yields:
-            ASRResult with text and is_final flag
-        """
-        while self._running:
-            try:
-                result = await asyncio.wait_for(
-                    self._transcript_queue.get(),
-                    timeout=0.1
-                )
-                yield result
-            except asyncio.TimeoutError:
-                continue
-            except asyncio.CancelledError:
-                break
-    
-    async def start_interim_transcription(self) -> None:
-        """
-        Start background task for interim transcriptions.
-        
-        This periodically transcribes buffered audio for
-        real-time feedback to the user.
-        """
-        if self._interim_task and not self._interim_task.done():
-            return
-        
-        self._interim_task = asyncio.create_task(self._interim_loop())
-    
-    async def stop_interim_transcription(self) -> None:
-        """Stop interim transcription task."""
-        if self._interim_task:
-            self._interim_task.cancel()
-            try:
-                await self._interim_task
-            except asyncio.CancelledError:
-                pass
-            self._interim_task = None
-    
-    async def _interim_loop(self) -> None:
-        """Background loop for interim transcriptions."""
-        import time
-        
-        while self._running:
-            try:
-                await asyncio.sleep(self.interim_interval_ms / 1000)
-                
-                # Check if we have enough new audio
-                current_time = time.time()
-                time_since_last = (current_time - self._last_interim_time) * 1000
-                
-                if time_since_last >= self.interim_interval_ms:
-                    audio_duration = self.get_audio_duration_ms()
-                    
-                    if audio_duration >= self.min_audio_for_interim_ms:
-                        await self.transcribe_buffer(is_final=False)
-                        self._last_interim_time = current_time
-                        
-            except asyncio.CancelledError:
-                break
-            except Exception as e:
-                logger.error(f"Interim transcription error: {e}")

engine/services/siliconflow_tts.py

@@ -1,311 +1,8 @@
-"""SiliconFlow TTS Service with streaming support.
+"""Backward-compatible imports for legacy siliconflow_tts module."""
 
-Uses SiliconFlow's CosyVoice2 or MOSS-TTSD models for low-latency
+from services.openai_compatible_tts import OpenAICompatibleTTSService, StreamingTTSAdapter
-text-to-speech synthesis with streaming.
 
-API Docs: https://docs.siliconflow.cn/cn/api-reference/audio/create-speech
+# Backward-compatible alias
-"""
+SiliconFlowTTSService = OpenAICompatibleTTSService
 
-import os
+__all__ = ["OpenAICompatibleTTSService", "SiliconFlowTTSService", "StreamingTTSAdapter"]
-import asyncio
-import aiohttp
-from typing import AsyncIterator, Optional
-from loguru import logger
-
-from services.base import BaseTTSService, TTSChunk, ServiceState
-from services.streaming_tts_adapter import StreamingTTSAdapter  # backward-compatible re-export
-
-
-class SiliconFlowTTSService(BaseTTSService):
-    """
-    SiliconFlow TTS service with streaming support.
-    
-    Supports CosyVoice2-0.5B and MOSS-TTSD-v0.5 models.
-    """
-    
-    # Available voices
-    VOICES = {
-        "alex": "FunAudioLLM/CosyVoice2-0.5B:alex",
-        "anna": "FunAudioLLM/CosyVoice2-0.5B:anna",
-        "bella": "FunAudioLLM/CosyVoice2-0.5B:bella",
-        "benjamin": "FunAudioLLM/CosyVoice2-0.5B:benjamin",
-        "charles": "FunAudioLLM/CosyVoice2-0.5B:charles",
-        "claire": "FunAudioLLM/CosyVoice2-0.5B:claire",
-        "david": "FunAudioLLM/CosyVoice2-0.5B:david",
-        "diana": "FunAudioLLM/CosyVoice2-0.5B:diana",
-    }
-    
-    def __init__(
-        self,
-        api_key: Optional[str] = None,
-        voice: str = "anna",
-        model: str = "FunAudioLLM/CosyVoice2-0.5B",
-        sample_rate: int = 16000,
-        speed: float = 1.0
-    ):
-        """
-        Initialize SiliconFlow TTS service.
-        
-        Args:
-            api_key: SiliconFlow API key (defaults to SILICONFLOW_API_KEY env var)
-            voice: Voice name (alex, anna, bella, benjamin, charles, claire, david, diana)
-            model: Model name
-            sample_rate: Output sample rate (8000, 16000, 24000, 32000, 44100)
-            speed: Speech speed (0.25 to 4.0)
-        """
-        # Resolve voice name
-        if voice in self.VOICES:
-            full_voice = self.VOICES[voice]
-        else:
-            full_voice = voice
-            
-        super().__init__(voice=full_voice, sample_rate=sample_rate, speed=speed)
-        
-        self.api_key = api_key or os.getenv("SILICONFLOW_API_KEY")
-        self.model = model
-        self.api_url = "https://api.siliconflow.cn/v1/audio/speech"
-        
-        self._session: Optional[aiohttp.ClientSession] = None
-        self._cancel_event = asyncio.Event()
-    
-    async def connect(self) -> None:
-        """Initialize HTTP session."""
-        if not self.api_key:
-            raise ValueError("SiliconFlow API key not provided. Set SILICONFLOW_API_KEY env var.")
-        
-        self._session = aiohttp.ClientSession(
-            headers={
-                "Authorization": f"Bearer {self.api_key}",
-                "Content-Type": "application/json"
-            }
-        )
-        self.state = ServiceState.CONNECTED
-        logger.info(f"SiliconFlow TTS service ready: voice={self.voice}, model={self.model}")
-    
-    async def disconnect(self) -> None:
-        """Close HTTP session."""
-        if self._session:
-            await self._session.close()
-            self._session = None
-        self.state = ServiceState.DISCONNECTED
-        logger.info("SiliconFlow TTS service disconnected")
-    
-    async def synthesize(self, text: str) -> bytes:
-        """Synthesize complete audio for text."""
-        audio_data = b""
-        async for chunk in self.synthesize_stream(text):
-            audio_data += chunk.audio
-        return audio_data
-    
-    async def synthesize_stream(self, text: str) -> AsyncIterator[TTSChunk]:
-        """
-        Synthesize audio in streaming mode.
-        
-        Args:
-            text: Text to synthesize
-            
-        Yields:
-            TTSChunk objects with PCM audio
-        """
-        if not self._session:
-            raise RuntimeError("TTS service not connected")
-        
-        if not text.strip():
-            return
-        
-        self._cancel_event.clear()
-        
-        payload = {
-            "model": self.model,
-            "input": text,
-            "voice": self.voice,
-            "response_format": "pcm",
-            "sample_rate": self.sample_rate,
-            "stream": True,
-            "speed": self.speed
-        }
-        
-        try:
-            async with self._session.post(self.api_url, json=payload) as response:
-                if response.status != 200:
-                    error_text = await response.text()
-                    logger.error(f"SiliconFlow TTS error: {response.status} - {error_text}")
-                    return
-                
-                # Stream audio chunks
-                chunk_size = self.sample_rate * 2 // 10  # 100ms chunks
-                buffer = b""
-                pending_chunk = None
-                
-                async for chunk in response.content.iter_any():
-                    if self._cancel_event.is_set():
-                        logger.info("TTS synthesis cancelled")
-                        return
-                    
-                    buffer += chunk
-                    
-                    # Yield complete chunks
-                    while len(buffer) >= chunk_size:
-                        audio_chunk = buffer[:chunk_size]
-                        buffer = buffer[chunk_size:]
-
-                        # Keep one full chunk buffered so we can always tag the true
-                        # last full chunk as final when stream length is an exact multiple.
-                        if pending_chunk is not None:
-                            yield TTSChunk(
-                                audio=pending_chunk,
-                                sample_rate=self.sample_rate,
-                                is_final=False
-                            )
-                        pending_chunk = audio_chunk
-                
-                # Flush pending chunk(s) and remaining tail.
-                if pending_chunk is not None:
-                    if buffer:
-                        yield TTSChunk(
-                            audio=pending_chunk,
-                            sample_rate=self.sample_rate,
-                            is_final=False
-                        )
-                        pending_chunk = None
-                    else:
-                        yield TTSChunk(
-                            audio=pending_chunk,
-                            sample_rate=self.sample_rate,
-                            is_final=True
-                        )
-                        pending_chunk = None
-
-                if buffer:
-                    yield TTSChunk(
-                        audio=buffer,
-                        sample_rate=self.sample_rate,
-                        is_final=True
-                    )
-                    
-        except asyncio.CancelledError:
-            logger.info("TTS synthesis cancelled via asyncio")
-            raise
-        except Exception as e:
-            logger.error(f"TTS synthesis error: {e}")
-            raise
-    
-    async def cancel(self) -> None:
-        """Cancel ongoing synthesis."""
-        self._cancel_event.set()
-
-
-class StreamingTTSAdapter:
-    """
-    Adapter for streaming LLM text to TTS with sentence-level chunking.
-    
-    This reduces latency by starting TTS as soon as a complete sentence
-    is received from the LLM, rather than waiting for the full response.
-    """
-    
-    # Sentence delimiters
-    SENTENCE_ENDS = {'，', '。', '！', '？', '.', '!', '?', '\n'}
-    
-    def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
-        self.tts_service = tts_service
-        self.transport = transport
-        self.session_id = session_id
-        self._buffer = ""
-        self._cancel_event = asyncio.Event()
-        self._is_speaking = False
-
-    def _is_non_sentence_period(self, text: str, idx: int) -> bool:
-        """Check whether '.' should NOT be treated as a sentence delimiter."""
-        if text[idx] != ".":
-            return False
-
-        # Decimal/version segment: 1.2, v1.2.3
-        if idx > 0 and idx < len(text) - 1 and text[idx - 1].isdigit() and text[idx + 1].isdigit():
-            return True
-
-        # Number abbreviations: No.1 / No. 1
-        left_start = idx - 1
-        while left_start >= 0 and text[left_start].isalpha():
-            left_start -= 1
-        left_token = text[left_start + 1:idx].lower()
-        if left_token == "no":
-            j = idx + 1
-            while j < len(text) and text[j].isspace():
-                j += 1
-            if j < len(text) and text[j].isdigit():
-                return True
-
-        return False
-    
-    async def process_text_chunk(self, text_chunk: str) -> None:
-        """
-        Process a text chunk from LLM and trigger TTS when sentence is complete.
-        
-        Args:
-            text_chunk: Text chunk from LLM streaming
-        """
-        if self._cancel_event.is_set():
-            return
-        
-        self._buffer += text_chunk
-        
-        # Check for sentence completion
-        while True:
-            split_idx = -1
-            for i, char in enumerate(self._buffer):
-                if char == "." and self._is_non_sentence_period(self._buffer, i):
-                    continue
-                if char in self.SENTENCE_ENDS:
-                    split_idx = i
-                    break
-            if split_idx < 0:
-                break
-
-            end_idx = split_idx + 1
-            while end_idx < len(self._buffer) and self._buffer[end_idx] in self.SENTENCE_ENDS:
-                end_idx += 1
-
-            sentence = self._buffer[:end_idx].strip()
-            self._buffer = self._buffer[end_idx:]
-
-            if sentence and any(ch.isalnum() for ch in sentence):
-                await self._speak_sentence(sentence)
-    
-    async def flush(self) -> None:
-        """Flush remaining buffer."""
-        if self._buffer.strip() and not self._cancel_event.is_set():
-            await self._speak_sentence(self._buffer.strip())
-        self._buffer = ""
-    
-    async def _speak_sentence(self, text: str) -> None:
-        """Synthesize and send a sentence."""
-        if not text or self._cancel_event.is_set():
-            return
-        
-        self._is_speaking = True
-        
-        try:
-            async for chunk in self.tts_service.synthesize_stream(text):
-                if self._cancel_event.is_set():
-                    break
-                await self.transport.send_audio(chunk.audio)
-                await asyncio.sleep(0.01)  # Prevent flooding
-        except Exception as e:
-            logger.error(f"TTS speak error: {e}")
-        finally:
-            self._is_speaking = False
-    
-    def cancel(self) -> None:
-        """Cancel ongoing speech."""
-        self._cancel_event.set()
-        self._buffer = ""
-    
-    def reset(self) -> None:
-        """Reset for new turn."""
-        self._cancel_event.clear()
-        self._buffer = ""
-        self._is_speaking = False
-    
-    @property
-    def is_speaking(self) -> bool:
-        return self._is_speaking

web/pages/ASRLibrary.tsx

@@ -85,7 +85,7 @@ const convertRecordedBlobToWav = async (blob: Blob): Promise<File> => {
 export const ASRLibraryPage: React.FC = () => {
   const [models, setModels] = useState<ASRModel[]>([]);
   const [searchTerm, setSearchTerm] = useState('');
-  const [vendorFilter, setVendorFilter] = useState<string>('all');
+  const [vendorFilter, setVendorFilter] = useState<string>('OpenAI Compatible');
   const [langFilter, setLangFilter] = useState<string>('all');
   const [isAddModalOpen, setIsAddModalOpen] = useState(false);
   const [editingModel, setEditingModel] = useState<ASRModel | null>(null);
@@ -111,7 +111,7 @@ export const ASRLibraryPage: React.FC = () => {
   const filteredModels = models.filter((m) => {
     const q = searchTerm.toLowerCase();
     const matchesSearch = m.name.toLowerCase().includes(q) || (m.modelName || '').toLowerCase().includes(q);
-    const matchesVendor = vendorFilter === 'all' || m.vendor === vendorFilter;
+    const matchesVendor = m.vendor === vendorFilter;
     const matchesLang = langFilter === 'all' || m.language === langFilter || (langFilter !== 'all' && m.language === 'Multi-lingual');
     return matchesSearch && matchesVendor && matchesLang;
   });
@@ -134,8 +134,6 @@ export const ASRLibraryPage: React.FC = () => {
     setModels((prev) => prev.filter((m) => m.id !== id));
   };
 
-  const vendorOptions = Array.from(new Set(models.map((m) => m.vendor).filter(Boolean)));
-
   return (
     <div className="space-y-6 animate-in fade-in py-4 pb-10">
       <div className="flex items-center justify-between">
@@ -162,10 +160,7 @@ export const ASRLibraryPage: React.FC = () => {
             value={vendorFilter}
             onChange={(e) => setVendorFilter(e.target.value)}
           >
-            <option value="all">所有厂商</option>
+            <option value="OpenAI Compatible">OpenAI Compatible</option>
-            {vendorOptions.map((vendor) => (
-              <option key={vendor} value={vendor}>{vendor}</option>
-            ))}
           </select>
         </div>
         <div className="flex items-center space-x-2">
@@ -371,7 +366,6 @@ const ASRModelModal: React.FC<{
               onChange={(e) => setVendor(e.target.value)}
             >
               <option value="OpenAI Compatible">OpenAI Compatible</option>
-              <option value="SiliconFlow">SiliconFlow</option>
             </select>
           </div>
           <div className="space-y-1.5">

web/pages/Assistants.tsx

@@ -5,32 +5,37 @@ import { Button, Input, Badge, Drawer, Dialog } from '../components/UI';
 import { ASRModel, Assistant, KnowledgeBase, LLMModel, TabValue, Tool, Voice } from '../types';
 import { createAssistant, deleteAssistant, fetchASRModels, fetchAssistants, fetchKnowledgeBases, fetchLLMModels, fetchTools, fetchVoices, updateAssistant as updateAssistantApi } from '../services/backendApi';
 
-const isSiliconflowVendor = (vendor?: string) => {
+const isOpenAICompatibleVendor = (vendor?: string) => {
   const normalized = String(vendor || '').trim().toLowerCase();
-  return normalized === 'siliconflow' || normalized === '硅基流动';
+  return (
+    normalized === 'siliconflow' ||
+    normalized === '硅基流动' ||
+    normalized === 'openai compatible' ||
+    normalized === 'openai-compatible'
+  );
 };
 
-const SILICONFLOW_DEFAULT_MODEL = 'FunAudioLLM/CosyVoice2-0.5B';
+const OPENAI_COMPATIBLE_DEFAULT_MODEL = 'FunAudioLLM/CosyVoice2-0.5B';
 
-const buildSiliconflowVoiceKey = (voiceId: string, model?: string) => {
+const buildOpenAICompatibleVoiceKey = (voiceId: string, model?: string) => {
   const id = String(voiceId || '').trim();
   if (!id) return '';
   if (id.includes(':')) return id;
-  return `${model || SILICONFLOW_DEFAULT_MODEL}:${id}`;
+  return `${model || OPENAI_COMPATIBLE_DEFAULT_MODEL}:${id}`;
 };
 
 const resolveRuntimeTtsVoice = (selectedVoiceId: string, voice: Voice) => {
   const explicitKey = String(voice.voiceKey || '').trim();
-  if (!isSiliconflowVendor(voice.vendor)) {
+  if (!isOpenAICompatibleVendor(voice.vendor)) {
     return explicitKey || selectedVoiceId;
   }
   if (voice.isSystem) {
-    const canonical = buildSiliconflowVoiceKey(selectedVoiceId, voice.model);
+    const canonical = buildOpenAICompatibleVoiceKey(selectedVoiceId, voice.model);
     if (!explicitKey) return canonical;
     const explicitSuffix = explicitKey.includes(':') ? explicitKey.split(':').pop() : explicitKey;
     if (explicitSuffix && explicitSuffix !== selectedVoiceId) return canonical;
   }
-  return explicitKey || buildSiliconflowVoiceKey(selectedVoiceId, voice.model);
+  return explicitKey || buildOpenAICompatibleVoiceKey(selectedVoiceId, voice.model);
 };
 
 const renderToolIcon = (icon: string) => {
@@ -1830,11 +1835,11 @@ export const DebugDrawer: React.FC<{
     if (assistant.asrModelId) {
       const asr = asrModels.find((item) => item.id === assistant.asrModelId);
       if (asr) {
-        const asrProvider = isSiliconflowVendor(asr.vendor) ? 'siliconflow' : 'buffered';
+        const asrProvider = isOpenAICompatibleVendor(asr.vendor) ? 'openai_compatible' : 'buffered';
         services.asr = {
           provider: asrProvider,
           model: asr.modelName || asr.name,
-          apiKey: asrProvider === 'siliconflow' ? asr.apiKey : null,
+          apiKey: asrProvider === 'openai_compatible' ? asr.apiKey : null,
         };
       } else {
         warnings.push(`ASR model not found in loaded list: ${assistant.asrModelId}`);
@@ -1844,12 +1849,12 @@ export const DebugDrawer: React.FC<{
     if (assistant.voice) {
       const voice = voices.find((item) => item.id === assistant.voice);
       if (voice) {
-        const ttsProvider = isSiliconflowVendor(voice.vendor) ? 'siliconflow' : 'edge';
+        const ttsProvider = isOpenAICompatibleVendor(voice.vendor) ? 'openai_compatible' : 'edge';
         services.tts = {
           enabled: ttsEnabled,
           provider: ttsProvider,
           model: voice.model,
-          apiKey: ttsProvider === 'siliconflow' ? voice.apiKey : null,
+          apiKey: ttsProvider === 'openai_compatible' ? voice.apiKey : null,
           voice: resolveRuntimeTtsVoice(assistant.voice, voice),
           speed: assistant.speed || voice.speed || 1.0,
         };

web/pages/LLMLibrary.tsx

@@ -13,7 +13,7 @@ const maskApiKey = (key?: string) => {
 export const LLMLibraryPage: React.FC = () => {
   const [models, setModels] = useState<LLMModel[]>([]);
   const [searchTerm, setSearchTerm] = useState('');
-  const [vendorFilter, setVendorFilter] = useState<string>('all');
+  const [vendorFilter, setVendorFilter] = useState<string>('OpenAI Compatible');
   const [typeFilter, setTypeFilter] = useState<string>('all');
   const [isAddModalOpen, setIsAddModalOpen] = useState(false);
   const [editingModel, setEditingModel] = useState<LLMModel | null>(null);
@@ -41,7 +41,7 @@ export const LLMLibraryPage: React.FC = () => {
       m.name.toLowerCase().includes(q) ||
       (m.modelName || '').toLowerCase().includes(q) ||
       (m.baseUrl || '').toLowerCase().includes(q);
-    const matchesVendor = vendorFilter === 'all' || m.vendor === vendorFilter;
+    const matchesVendor = m.vendor === vendorFilter;
     const matchesType = typeFilter === 'all' || m.type === typeFilter;
     return matchesSearch && matchesVendor && matchesType;
   });
@@ -64,8 +64,6 @@ export const LLMLibraryPage: React.FC = () => {
     setModels((prev) => prev.filter((item) => item.id !== id));
   };
 
-  const vendorOptions = Array.from(new Set(models.map((m) => m.vendor).filter(Boolean)));
-
   return (
     <div className="space-y-6 animate-in fade-in py-4 pb-10">
       <div className="flex items-center justify-between">
@@ -92,10 +90,7 @@ export const LLMLibraryPage: React.FC = () => {
             value={vendorFilter}
             onChange={(e) => setVendorFilter(e.target.value)}
           >
-            <option value="all">所有厂商</option>
+            <option value="OpenAI Compatible">OpenAI Compatible</option>
-            {vendorOptions.map((vendor) => (
-              <option key={vendor} value={vendor}>{vendor}</option>
-            ))}
           </select>
         </div>
         <div className="flex items-center space-x-2">
@@ -284,8 +279,6 @@ const LLMModelModal: React.FC<{
             onChange={(e) => setVendor(e.target.value)}
           >
             <option value="OpenAI Compatible">OpenAI Compatible</option>
-            <option value="OpenAI">OpenAI</option>
-            <option value="SiliconFlow">SiliconFlow</option>
           </select>
         </div>
 

web/pages/VoiceLibrary.tsx

@@ -1,12 +1,12 @@
 import React, { useEffect, useState, useRef } from 'react';
-import { Search, Mic2, Play, Pause, Upload, Filter, Plus, Volume2, Sparkles, ChevronDown, Pencil, Trash2 } from 'lucide-react';
+import { Search, Mic2, Play, Pause, Upload, Filter, Plus, Volume2, Pencil, Trash2 } from 'lucide-react';
 import { Button, Input, TableHeader, TableRow, TableHead, TableCell, Dialog, Badge } from '../components/UI';
 import { Voice } from '../types';
 import { createVoice, deleteVoice, fetchVoices, previewVoice, updateVoice } from '../services/backendApi';
 
-const SILICONFLOW_DEFAULT_MODEL = 'FunAudioLLM/CosyVoice2-0.5B';
+const OPENAI_COMPATIBLE_DEFAULT_MODEL = 'FunAudioLLM/CosyVoice2-0.5B';
 
-const buildSiliconflowVoiceKey = (rawId: string, model: string): string => {
+const buildOpenAICompatibleVoiceKey = (rawId: string, model: string): string => {
   const id = (rawId || '').trim();
   if (!id) return `${model}:anna`;
   return id.includes(':') ? id : `${model}:${id}`;
@@ -15,7 +15,7 @@ const buildSiliconflowVoiceKey = (rawId: string, model: string): string => {
 export const VoiceLibraryPage: React.FC = () => {
   const [voices, setVoices] = useState<Voice[]>([]);
   const [searchTerm, setSearchTerm] = useState('');
-  const [vendorFilter, setVendorFilter] = useState<'all' | 'Ali' | 'Volcano' | 'Minimax' | '硅基流动' | 'SiliconFlow'>('all');
+  const [vendorFilter, setVendorFilter] = useState<'OpenAI Compatible'>('OpenAI Compatible');
   const [genderFilter, setGenderFilter] = useState<'all' | 'Male' | 'Female'>('all');
   const [langFilter, setLangFilter] = useState<'all' | 'zh' | 'en'>('all');
 
@@ -44,7 +44,7 @@ export const VoiceLibraryPage: React.FC = () => {
 
   const filteredVoices = voices.filter((voice) => {
     const matchesSearch = voice.name.toLowerCase().includes(searchTerm.toLowerCase());
-    const matchesVendor = vendorFilter === 'all' || voice.vendor === vendorFilter;
+    const matchesVendor = voice.vendor === vendorFilter;
     const matchesGender = genderFilter === 'all' || voice.gender === genderFilter;
     const matchesLang = langFilter === 'all' || voice.language === langFilter;
     return matchesSearch && matchesVendor && matchesGender && matchesLang;
@@ -138,12 +138,7 @@ export const VoiceLibraryPage: React.FC = () => {
             value={vendorFilter}
             onChange={(e) => setVendorFilter(e.target.value as any)}
           >
-            <option value="all">所有厂商</option>
+            <option value="OpenAI Compatible">OpenAI Compatible</option>
-            <option value="硅基流动">硅基流动 (SiliconFlow)</option>
-            <option value="SiliconFlow">SiliconFlow</option>
-            <option value="Ali">阿里 (Ali)</option>
-            <option value="Volcano">火山 (Volcano)</option>
-            <option value="Minimax">Minimax</option>
           </select>
         </div>
         <div className="flex items-center space-x-2">
@@ -187,15 +182,12 @@ export const VoiceLibraryPage: React.FC = () => {
               <TableRow key={voice.id}>
                 <TableCell className="font-medium">
                   <div className="flex flex-col">
-                    <span className="flex items-center text-white">
+                    <span className="flex items-center text-white">{voice.name}</span>
-                      {voice.vendor === '硅基流动' && <Sparkles className="w-3 h-3 text-primary mr-1.5" />}
-                      {voice.name}
-                    </span>
                     {voice.description && <span className="text-xs text-muted-foreground">{voice.description}</span>}
                   </div>
                 </TableCell>
                 <TableCell>
-                  <Badge variant={voice.vendor === '硅基流动' ? 'default' : 'outline'}>{voice.vendor}</Badge>
+                  <Badge variant="outline">{voice.vendor}</Badge>
                 </TableCell>
                 <TableCell className="text-muted-foreground">{voice.gender === 'Male' ? '男' : '女'}</TableCell>
                 <TableCell className="text-muted-foreground">{voice.language === 'zh' ? '中文' : 'English'}</TableCell>
@@ -254,17 +246,15 @@ const AddVoiceModal: React.FC<{
   onSuccess: (voice: Voice) => Promise<void>;
   initialVoice?: Voice;
 }> = ({ isOpen, onClose, onSuccess, initialVoice }) => {
-  const [vendor, setVendor] = useState<'硅基流动' | 'Ali' | 'Volcano' | 'Minimax'>('硅基流动');
+  const [vendor, setVendor] = useState<'OpenAI Compatible'>('OpenAI Compatible');
   const [name, setName] = useState('');
 
-  const [sfModel, setSfModel] = useState(SILICONFLOW_DEFAULT_MODEL);
+  const [openaiCompatibleModel, setOpenaiCompatibleModel] = useState(OPENAI_COMPATIBLE_DEFAULT_MODEL);
   const [sfVoiceId, setSfVoiceId] = useState('FunAudioLLM/CosyVoice2-0.5B:anna');
   const [sfSpeed, setSfSpeed] = useState(1);
   const [sfGain, setSfGain] = useState(0);
   const [sfPitch, setSfPitch] = useState(0);
 
-  const [model, setModel] = useState('');
-  const [voiceKey, setVoiceKey] = useState('');
   const [gender, setGender] = useState('Female');
   const [language, setLanguage] = useState('zh');
   const [description, setDescription] = useState('');
@@ -278,17 +268,15 @@ const AddVoiceModal: React.FC<{
 
   useEffect(() => {
     if (!initialVoice) return;
-    const nextVendor = initialVoice.vendor === 'SiliconFlow' ? '硅基流动' : initialVoice.vendor;
+    const nextVendor = 'OpenAI Compatible';
-    const nextModel = initialVoice.model || SILICONFLOW_DEFAULT_MODEL;
+    const nextModel = initialVoice.model || OPENAI_COMPATIBLE_DEFAULT_MODEL;
-    const defaultVoiceKey = buildSiliconflowVoiceKey(initialVoice.id || initialVoice.name || '', nextModel);
+    const defaultVoiceKey = buildOpenAICompatibleVoiceKey(initialVoice.id || initialVoice.name || '', nextModel);
-    setVendor((nextVendor as any) || '硅基流动');
+    setVendor(nextVendor);
     setName(initialVoice.name || '');
     setGender(initialVoice.gender || 'Female');
     setLanguage(initialVoice.language || 'zh');
     setDescription(initialVoice.description || '');
-    setModel(initialVoice.model || '');
+    setOpenaiCompatibleModel(nextModel);
-    setVoiceKey(initialVoice.voiceKey || '');
-    setSfModel(nextModel);
     setSfVoiceId((initialVoice.voiceKey || '').trim() || defaultVoiceKey);
     setSfSpeed(initialVoice.speed ?? 1);
     setSfGain(initialVoice.gain ?? 0);
@@ -325,21 +313,21 @@ const AddVoiceModal: React.FC<{
       return;
     }
 
-    const resolvedSiliconflowVoiceKey = (() => {
+    const resolvedVoiceKey = (() => {
       const current = (sfVoiceId || '').trim();
       if (current) return current;
-      return buildSiliconflowVoiceKey(initialVoice?.id || name, sfModel || SILICONFLOW_DEFAULT_MODEL);
+      return buildOpenAICompatibleVoiceKey(initialVoice?.id || name, openaiCompatibleModel || OPENAI_COMPATIBLE_DEFAULT_MODEL);
     })();
 
     const newVoice: Voice = {
-      id: initialVoice?.id || `${vendor === '硅基流动' ? 'sf' : 'gen'}-${Date.now()}`,
+      id: initialVoice?.id || `oa-${Date.now()}`,
       name,
       vendor,
       gender,
       language,
-      description: description || (vendor === '硅基流动' ? `Model: ${sfModel}` : `Model: ${model}`),
+      description: description || `Model: ${openaiCompatibleModel}`,
-      model: vendor === '硅基流动' ? sfModel : model,
+      model: openaiCompatibleModel,
-      voiceKey: vendor === '硅基流动' ? resolvedSiliconflowVoiceKey : voiceKey,
+      voiceKey: resolvedVoiceKey,
       apiKey,
       baseUrl,
       speed: sfSpeed,
@@ -351,10 +339,8 @@ const AddVoiceModal: React.FC<{
       setIsSaving(true);
       await onSuccess(newVoice);
       setName('');
-      setVendor('硅基流动');
+      setVendor('OpenAI Compatible');
       setDescription('');
-      setModel('');
-      setVoiceKey('');
       setApiKey('');
       setBaseUrl('');
     } catch (error: any) {
@@ -381,19 +367,7 @@ const AddVoiceModal: React.FC<{
       <div className="space-y-4 max-h-[75vh] overflow-y-auto px-1 custom-scrollbar">
         <div className="space-y-1.5">
           <label className="text-[10px] font-black text-muted-foreground uppercase tracking-widest block">厂商 (Vendor)</label>
-          <div className="relative">
+          <Input value={vendor} readOnly className="h-10 border border-white/10 bg-white/5" />
-            <select
-              className="flex h-10 w-full rounded-md border border-white/10 bg-white/5 px-3 py-1 text-sm shadow-sm transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-primary/50 text-foreground appearance-none cursor-pointer [&>option]:bg-card"
-              value={vendor}
-              onChange={(e) => setVendor(e.target.value as any)}
-            >
-              <option value="硅基流动">硅基流动 (SiliconFlow)</option>
-              <option value="Ali">阿里 (Ali)</option>
-              <option value="Volcano">火山 (Volcano)</option>
-              <option value="Minimax">Minimax</option>
-            </select>
-            <ChevronDown className="absolute right-3 top-1/2 -translate-y-1/2 h-4 w-4 text-muted-foreground pointer-events-none" />
-          </div>
         </div>
 
         <div className="h-px bg-white/5"></div>
@@ -403,15 +377,14 @@ const AddVoiceModal: React.FC<{
           <Input value={name} onChange={(e) => setName(e.target.value)} placeholder="例如: 客服小美" />
         </div>
 
-        {vendor === '硅基流动' ? (
         <div className="space-y-4 animate-in fade-in slide-in-from-top-1 duration-200">
             <div className="grid grid-cols-2 gap-4">
               <div className="space-y-1.5">
                 <label className="text-[10px] font-black text-muted-foreground uppercase tracking-widest block">模型 (Model)</label>
                 <Input
                   className="font-mono text-xs"
-                  value={sfModel}
+                  value={openaiCompatibleModel}
-                  onChange={(e) => setSfModel(e.target.value)}
+                  onChange={(e) => setOpenaiCompatibleModel(e.target.value)}
                   placeholder="例如: FunAudioLLM/CosyVoice2-0.5B"
                 />
               </div>
@@ -445,20 +418,6 @@ const AddVoiceModal: React.FC<{
               </div>
             </div>
           </div>
-        ) : (
-          <div className="space-y-4 animate-in fade-in slide-in-from-top-1 duration-200">
-            <div className="grid grid-cols-2 gap-4">
-              <div className="space-y-1.5">
-                <label className="text-[10px] font-black text-muted-foreground uppercase tracking-widest block">模型标识</label>
-                <Input value={model} onChange={(e) => setModel(e.target.value)} placeholder="API Model Key" />
-              </div>
-              <div className="space-y-1.5">
-                <label className="text-[10px] font-black text-muted-foreground uppercase tracking-widest block">发音人标识</label>
-                <Input value={voiceKey} onChange={(e) => setVoiceKey(e.target.value)} placeholder="Voice Key" />
-              </div>
-            </div>
-          </div>
-        )}
 
         <div className="grid grid-cols-2 gap-4">
           <div className="space-y-1.5">
@@ -560,7 +519,7 @@ const CloneVoiceModal: React.FC<{
     const newVoice: Voice = {
       id: `v-${Date.now()}`,
       name,
-      vendor: 'Volcano',
+      vendor: 'OpenAI Compatible',
       gender: 'Female',
       language: 'zh',
       description: description || 'User cloned voice',

web/services/backendApi.ts

@@ -55,8 +55,11 @@ const mapVoice = (raw: AnyRecord): Voice => ({
   id: String(readField(raw, ['id'], '')),
   name: readField(raw, ['name'], ''),
   vendor: ((): string => {
-    const vendor = String(readField(raw, ['vendor'], ''));
+    const vendor = String(readField(raw, ['vendor'], '')).trim().toLowerCase();
-    return vendor.toLowerCase() === 'siliconflow' ? '硅基流动' : vendor;
+    if (vendor === 'siliconflow' || vendor === '硅基流动' || vendor === 'openai-compatible') {
+      return 'OpenAI Compatible';
+    }
+    return String(readField(raw, ['vendor'], 'OpenAI Compatible')) || 'OpenAI Compatible';
   })(),
   gender: readField(raw, ['gender'], ''),
   language: readField(raw, ['language'], ''),
@@ -296,7 +299,7 @@ export const createVoice = async (data: Partial<Voice>): Promise<Voice> => {
   const payload = {
     id: data.id || undefined,
     name: data.name || 'New Voice',
-    vendor: data.vendor === '硅基流动' ? 'SiliconFlow' : (data.vendor || 'SiliconFlow'),
+    vendor: data.vendor || 'OpenAI Compatible',
     gender: data.gender || 'Female',
     language: data.language || 'zh',
     description: data.description || '',
@@ -316,7 +319,7 @@ export const createVoice = async (data: Partial<Voice>): Promise<Voice> => {
 export const updateVoice = async (id: string, data: Partial<Voice>): Promise<Voice> => {
   const payload = {
     name: data.name,
-    vendor: data.vendor === '硅基流动' ? 'SiliconFlow' : data.vendor,
+    vendor: data.vendor,
     gender: data.gender,
     language: data.language,
     description: data.description,

web/services/mockData.ts

@@ -200,7 +200,7 @@ export const mockLLMModels: LLMModel[] = [
   { id: 'm1', name: 'GPT-4o', vendor: 'OpenAI Compatible', type: 'text', baseUrl: 'https://api.openai.com/v1', apiKey: 'sk-***', temperature: 0.7 },
   { id: 'm2', name: 'DeepSeek-V3', vendor: 'OpenAI Compatible', type: 'text', baseUrl: 'https://api.deepseek.com', apiKey: 'sk-***', temperature: 0.5 },
   { id: 'm3', name: 'text-embedding-3-small', vendor: 'OpenAI Compatible', type: 'embedding', baseUrl: 'https://api.openai.com/v1', apiKey: 'sk-***' },
-  { id: 'm4', name: 'bge-reranker-v2-m3', vendor: 'SiliconFlow', type: 'rerank', baseUrl: 'https://api.siliconflow.cn/v1', apiKey: 'sk-***' },
+  { id: 'm4', name: 'bge-reranker-v2-m3', vendor: 'OpenAI Compatible', type: 'rerank', baseUrl: 'https://api.siliconflow.cn/v1', apiKey: 'sk-***' },
 ];
 
 export const mockASRModels: ASRModel[] = [