add metrics, fix response type

requirements.txt

@@ -3,3 +3,4 @@ fastapi
 uvicorn
 whisper_ctranslate2
 opencc
+prometheus-fastapi-instrumentator

whisper_fastapi.py

@@ -4,11 +4,12 @@ import hashlib
 import argparse
 import uvicorn
 from typing import Any
-from fastapi import File, UploadFile, Form, FastAPI, Request, WebSocket
+from fastapi import File, UploadFile, Form, FastAPI, Request, WebSocket, Response
 from fastapi.middleware.cors import CORSMiddleware
 from src.whisper_ctranslate2.whisper_ctranslate2 import Transcribe, TranscriptionOptions
 from src.whisper_ctranslate2.writers import format_timestamp
 import opencc
+from prometheus_fastapi_instrumentator import Instrumentator
 
 parser = argparse.ArgumentParser()
 parser.add_argument("--host", default="0.0.0.0", type=str)
@@ -17,6 +18,8 @@ parser.add_argument("--model", default="large-v2", type=str)
 parser.add_argument("--cache_dir", default=None, type=str)
 args = parser.parse_args()
 app = FastAPI()
+# Instrument your app with default metrics and expose the metrics
+Instrumentator().instrument(app).expose(app, endpoint="/konele/metrics")
 ccc = opencc.OpenCC("t2s.json")
 
 print("Loading model...")
@@ -211,7 +214,7 @@ async def translateapi(
 async def transcription(
     file: UploadFile = File(...),
     prompt: str = Form(""),
-    response_type: str = Form("json"),
+    response_format: str = Form("json"),
 ):
     """Transcription endpoint
 
@@ -230,18 +233,18 @@ async def transcription(
         options=options,
     )
 
-    if response_type == "json":
+    if response_format == "json":
-        return result
+        return Response(content=result, media_type="application/json")
-    elif response_type == "text":
+    elif response_format == "text":
-        return result["text"].strip()
+        return Response(content='\n'.join(s['text'] for s in result['segments']), media_type="plain/text")
-    elif response_type == "tsv":
+    elif response_format == "tsv":
-        return generate_tsv(result)
+        return Response(content=generate_tsv(result), media_type='plain_text')
-    elif response_type == "srt":
+    elif response_format == "srt":
-        return generate_srt(result)
+        return Response(content=generate_srt(result), media_type='plain_text')
-    elif response_type == "vtt":
+    elif response_format == "vtt":
         return generate_vtt(result)
 
-    return {"error": "Invalid response_type"}
+    return {"error": "Invalid response_format"}
 
 
 uvicorn.run(app, host=args.host, port=args.port)