diff --git a/scripts/tts_mlx.py b/scripts/tts_mlx.py
index 050fce5..8e08677 100644
--- a/scripts/tts_mlx.py
+++ b/scripts/tts_mlx.py
@@ -10,23 +10,24 @@
 
 import argparse
 import json
-from pathlib import Path
 import queue
+import sys
 import time
 
-import numpy as np
 import mlx.core as mx
 import mlx.nn as nn
+import numpy as np
 import sentencepiece
-import sphn
-import time
-
 import sounddevice as sd
-
-from moshi_mlx.client_utils import make_log
+import sphn
 from moshi_mlx import models
+from moshi_mlx.client_utils import make_log
+from moshi_mlx.models.tts import (
+    DEFAULT_DSM_TTS_REPO,
+    DEFAULT_DSM_TTS_VOICE_REPO,
+    TTSModel,
+)
 from moshi_mlx.utils.loaders import hf_get
-from moshi_mlx.models.tts import TTSModel, DEFAULT_DSM_TTS_REPO, DEFAULT_DSM_TTS_VOICE_REPO
 
 
 def log(level: str, msg: str):
@@ -34,15 +35,32 @@ def log(level: str, msg: str):
 
 
 def main():
-    parser = argparse.ArgumentParser(prog='moshi-tts', description='Run Moshi')
+    parser = argparse.ArgumentParser(
+        description="Run Kyutai TTS using the PyTorch implementation"
+    )
     parser.add_argument("inp", type=str, help="Input file, use - for stdin")
-    parser.add_argument("out", type=str, help="Output file to generate, use - for playing the audio")
-    parser.add_argument("--hf-repo", type=str, default=DEFAULT_DSM_TTS_REPO,
-                        help="HF repo in which to look for the pretrained models.")
-    parser.add_argument("--voice-repo", default=DEFAULT_DSM_TTS_VOICE_REPO,
-                        help="HF repo in which to look for pre-computed voice embeddings.")
-    parser.add_argument("--voice", default="expresso/ex03-ex01_happy_001_channel1_334s.wav")
-    parser.add_argument("--quantize", type=int, help="The quantization to be applied, e.g. 8 for 8 bits.")
+    parser.add_argument(
+        "out", type=str, help="Output file to generate, use - for playing the audio"
+    )
+    parser.add_argument(
+        "--hf-repo",
+        type=str,
+        default=DEFAULT_DSM_TTS_REPO,
+        help="HF repo in which to look for the pretrained models.",
+    )
+    parser.add_argument(
+        "--voice-repo",
+        default=DEFAULT_DSM_TTS_VOICE_REPO,
+        help="HF repo in which to look for pre-computed voice embeddings.",
+    )
+    parser.add_argument(
+        "--voice", default="expresso/ex03-ex01_happy_001_channel1_334s.wav"
+    )
+    parser.add_argument(
+        "--quantize",
+        type=int,
+        help="The quantization to be applied, e.g. 8 for 8 bits.",
+    )
     args = parser.parse_args()
 
     mx.random.seed(299792458)
@@ -96,7 +114,7 @@ def main():
     if tts_model.valid_cfg_conditionings:
         # Model was trained with CFG distillation.
         cfg_coef_conditioning = tts_model.cfg_coef
-        tts_model.cfg_coef = 1.
+        tts_model.cfg_coef = 1.0
         cfg_is_no_text = False
         cfg_is_no_prefix = False
     else:
@@ -105,17 +123,25 @@ def main():
     mimi = tts_model.mimi
 
     log("info", f"reading input from {args.inp}")
-    with open(args.inp, "r") as fobj:
-        text_to_tts = fobj.read().strip()
+    if args.inp == "-":
+        if sys.stdin.isatty():  # Interactive
+            print("Enter text to synthesize (Ctrl+D to end input):")
+        text_to_tts = sys.stdin.read().strip()
+    else:
+        with open(args.inp, "r") as fobj:
+            text_to_tts = fobj.read().strip()
 
     all_entries = [tts_model.prepare_script([text_to_tts])]
     if tts_model.multi_speaker:
         voices = [tts_model.get_voice_path(args.voice)]
     else:
         voices = []
-    all_attributes = [tts_model.make_condition_attributes(voices, cfg_coef_conditioning)]
+    all_attributes = [
+        tts_model.make_condition_attributes(voices, cfg_coef_conditioning)
+    ]
 
     wav_frames = queue.Queue()
+
     def _on_audio_hook(audio_tokens):
         if (audio_tokens == -1).any():
             return
@@ -141,16 +167,20 @@ def main():
         return result
 
     if args.out == "-":
+
         def audio_callback(outdata, _a, _b, _c):
             try:
                 pcm_data = wav_frames.get(block=False)
                 outdata[:, 0] = pcm_data
             except queue.Empty:
                 outdata[:] = 0
-        with sd.OutputStream(samplerate=mimi.sample_rate,
-                             blocksize=1920,
-                             channels=1,
-                             callback=audio_callback):
+
+        with sd.OutputStream(
+            samplerate=mimi.sample_rate,
+            blocksize=1920,
+            channels=1,
+            callback=audio_callback,
+        ):
             run()
             time.sleep(3)
             while True: