diff --git a/api/api.py b/api/api.py
index 4c94422..2cdb4cb 100644
--- a/api/api.py
+++ b/api/api.py
@@ -3,10 +3,8 @@
 import tempfile
 import logging
 from typing import Dict
-from modal import Image, Stub, web_endpoint, asgi_app
-from fastapi import FastAPI, Response
+from modal import Image, Stub, web_endpoint
 from fastapi.responses import StreamingResponse
-from fastapi.middleware.cors import CORSMiddleware
 
 # Define the GPU type to be used for processing
 GPU_TYPE = "T4"
@@ -21,9 +19,7 @@ def download_models():
 
     # Define model names for the translator and vocoder
     model_name = "seamlessM4T_v2_large"
-    vocoder_name = (
-        "vocoder_v2" if model_name == "seamlessM4T_v2_large" else "vocoder_36langs"
-    )
+    vocoder_name = "vocoder_v2" if model_name == "seamlessM4T_v2_large" else "vocoder_36langs"
 
     # Initialize the translator model with specified parameters
     Translator(
@@ -105,7 +101,6 @@ async def generate_seamlessm4t_speech(item: Dict):
     - Dict: A dictionary containing the status code, message, detected speech chunks, and the translated text.
     """
     # import wave
-    import os
 
     import torch
     import torchaudio
@@ -148,9 +143,7 @@ async def generate_seamlessm4t_speech(item: Dict):
         print(speech_timestamps_seconds)
         # translator = download_models()
         model_name = "seamlessM4T_v2_large"
-        vocoder_name = (
-            "vocoder_v2" if model_name == "seamlessM4T_v2_large" else "vocoder_36langs"
-        )
+        vocoder_name = "vocoder_v2" if model_name == "seamlessM4T_v2_large" else "vocoder_36langs"
 
         translator = Translator(
             model_name,
@@ -189,9 +182,7 @@ async def generate():
                 )
                 resampled_waveform = resampler(waveform)
                 torchaudio.save("resampled.wav", resampled_waveform, resample_rate)
-                translated_text, _ = translator.predict(
-                    "resampled.wav", "s2tt", target_lang
-                )
+                translated_text, _ = translator.predict("resampled.wav", "s2tt", target_lang)
                 text.append(str(translated_text[0]))
                 # os.remove(new_audio_name)
                 # os.remove("resampled.wav")