Update app.py

app.py

@@ -6,6 +6,18 @@ import tempfile
 import shutil
 from typing import Optional
 import uvicorn
+
+# Set environment variables for cache directories
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers_cache"
+os.environ["HF_HOME"] = "/tmp/hf_home"
+os.environ["TORCH_HOME"] = "/tmp/torch_home"
+
+# Create directories with appropriate permissions
+os.makedirs("/tmp/transformers_cache", exist_ok=True)
+os.makedirs("/tmp/hf_home", exist_ok=True)
+os.makedirs("/tmp/torch_home", exist_ok=True)
+
+# Import transformers after setting environment variables
 from transformers import pipeline
 
 app = FastAPI(
@@ -14,14 +26,9 @@ app = FastAPI(
     version="1.0.0"
 )
 
-import os
-# Set cache directory to a writable location
-os.environ['TRANSFORMERS_CACHE'] = '/tmp/huggingface_cache'
-os.makedirs('/tmp/huggingface_cache', exist_ok=True)
-
-# Then initialize pipeline as before
-transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-small")
-
+# Initialize the Whisper model pipeline
+# Using whisper-base for better compatibility with Spaces
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base")
 
 @app.get("/")
 def read_root():
@@ -45,7 +52,7 @@ async def transcribe_audio(file: UploadFile = File(...),
         raise HTTPException(status_code=400, detail="Unsupported file format. Please upload WAV, MP3, M4A, or OGG file.")
     
     # Save the uploaded file temporarily
-    with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+    with tempfile.NamedTemporaryFile(delete=False, dir="/tmp") as temp_file:
         shutil.copyfileobj(file.file, temp_file)
         temp_path = temp_file.name