Audio recording

src/app/api/transcribe/app.py

@@ -1,15 +1,19 @@
-from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, UploadFile, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 import whisper
 import os
 import tempfile
+import logging
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
 
 app = FastAPI()
 model = whisper.load_model("base")  # Load the model once for efficiency
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["http://localhost:3000"],  # Frontend origin (adjust as needed)
+    allow_origins=["*"],  # Frontend origin (adjust as needed)
     allow_credentials=True,
     allow_methods=["*"],  # Allow all HTTP methods (GET, POST, etc.)
     allow_headers=["*"],  # Allow all headers (Authorization, Content-Type, etc.)
@@ -17,17 +21,29 @@ app.add_middleware(
 
 @app.post("/transcribe")
 async def transcribe_audio(file: UploadFile = File(...)):
-    # Save the uploaded file to a temporary location
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_file:
-        temp_file.write(await file.read())
-        temp_path = temp_file.name
+    # Check the file extension
+    file_extension = file.filename.split('.')[-1].lower()
+    if file_extension not in ["mp3", "wav", "flac", "m4a"]:
+        raise HTTPException(status_code=400, detail="Invalid audio file format. Only mp3, wav, flac, or m4a are supported.")
 
     try:
-        # Transcribe the audio
+        # Save the uploaded file to a temporary location
+        with tempfile.NamedTemporaryFile(delete=False, suffix=f".{file_extension}") as temp_file:
+            temp_file.write(await file.read())
+            temp_path = temp_file.name
+
+        logging.info(f"Audio file saved at: {temp_path}")
+
+        # Transcribe the audio using Whisper
         result = model.transcribe(temp_path)
         transcription = result["text"]
-    finally:
+
         # Clean up temporary file
         os.remove(temp_path)
+        logging.info(f"Temporary file {temp_path} removed after transcription.")
 
-    return {"transcription": transcription}
+        return {"transcription": transcription}
+    
+    except Exception as e:
+        logging.error(f"Error during transcription: {e}")
+        raise HTTPException(status_code=500, detail="Internal server error during transcription.")