Update asr library preview

api/app/routers/asr.py

@@ -1,12 +1,11 @@
-from fastapi import APIRouter, Depends, HTTPException
-from sqlalchemy.orm import Session
-from typing import List, Optional
-import uuid
-import httpx
+import os
 import time
-import base64
-import json
-from datetime import datetime
+import uuid
+from typing import List, Optional
+
+import httpx
+from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
+from sqlalchemy.orm import Session
 
 from ..db import get_db
 from ..models import ASRModel
@@ -17,6 +16,18 @@ from ..schemas import (
 
 router = APIRouter(prefix="/asr", tags=["ASR Models"])
 
+SILICONFLOW_DEFAULT_ASR_MODEL = "FunAudioLLM/SenseVoiceSmall"
+
+
+def _is_siliconflow_vendor(vendor: str) -> bool:
+    return (vendor or "").strip().lower() in {"siliconflow", "硅基流动"}
+
+
+def _default_asr_model(vendor: str) -> str:
+    if _is_siliconflow_vendor(vendor):
+        return SILICONFLOW_DEFAULT_ASR_MODEL
+    return "whisper-1"
+
 
 # ============ ASR Models CRUD ============
 @router.get("")
@@ -219,3 +230,99 @@ def transcribe_audio(
 
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/{id}/preview", response_model=ASRTestResponse)
+async def preview_asr_model(
+    id: str,
+    file: UploadFile = File(...),
+    language: Optional[str] = Form(None),
+    api_key: Optional[str] = Form(None),
+    db: Session = Depends(get_db),
+):
+    """预览 ASR：上传音频并调用 OpenAI-compatible /audio/transcriptions。"""
+    model = db.query(ASRModel).filter(ASRModel.id == id).first()
+    if not model:
+        raise HTTPException(status_code=404, detail="ASR Model not found")
+
+    if not file:
+        raise HTTPException(status_code=400, detail="Audio file is required")
+
+    filename = file.filename or "preview.wav"
+    content_type = file.content_type or "application/octet-stream"
+    if not content_type.startswith("audio/"):
+        raise HTTPException(status_code=400, detail="Only audio files are supported")
+
+    audio_bytes = await file.read()
+    if not audio_bytes:
+        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):
+        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}")
+
+    base_url = (model.base_url or "").strip().rstrip("/")
+    if not base_url:
+        raise HTTPException(status_code=400, detail=f"Base URL is required for ASR model: {model.name}")
+
+    selected_model = (model.model_name or "").strip() or _default_asr_model(model.vendor)
+    data = {"model": selected_model}
+    effective_language = (language or "").strip() or None
+    if effective_language:
+        data["language"] = effective_language
+    if model.hotwords:
+        data["prompt"] = " ".join(model.hotwords)
+
+    headers = {"Authorization": f"Bearer {effective_api_key}"}
+    files = {"file": (filename, audio_bytes, content_type)}
+
+    start_time = time.time()
+    try:
+        with httpx.Client(timeout=90.0) as client:
+            response = client.post(
+                f"{base_url}/audio/transcriptions",
+                headers=headers,
+                data=data,
+                files=files,
+            )
+    except Exception as exc:
+        raise HTTPException(status_code=502, detail=f"ASR request failed: {exc}") from exc
+
+    if response.status_code != 200:
+        detail = response.text
+        try:
+            detail_json = response.json()
+            detail = detail_json.get("error", {}).get("message") or detail_json.get("detail") or detail
+        except Exception:
+            pass
+        raise HTTPException(status_code=502, detail=f"ASR vendor error: {detail}")
+
+    try:
+        payload = response.json()
+    except Exception:
+        payload = {"text": response.text}
+
+    transcript = ""
+    response_language = model.language
+    confidence = None
+    if isinstance(payload, dict):
+        transcript = str(payload.get("text") or payload.get("transcript") or "")
+        response_language = str(payload.get("language") or effective_language or model.language)
+        raw_confidence = payload.get("confidence")
+        if raw_confidence is not None:
+            try:
+                confidence = float(raw_confidence)
+            except (TypeError, ValueError):
+                confidence = None
+
+    latency_ms = int((time.time() - start_time) * 1000)
+    return ASRTestResponse(
+        success=bool(transcript),
+        transcript=transcript,
+        language=response_language,
+        confidence=confidence,
+        latency_ms=latency_ms,
+        message=None if transcript else "No transcript in response",
+    )