Update app.py

app.py

@@ -1,28 +1,24 @@
-# Simple Text-to-Speech | CPU-only HF Space
-
+import tempfile
+from gtts import gTTS
 import gradio as gr
-from transformers import pipeline
-
-# ── load once on startup (≈120 MB, CPU-friendly) ─────────────────────
-tts = pipeline(
-    "text-to-speech",
-    model="facebook/fastspeech2-en-ljspeech",
-    vocoder="facebook/hifigan-en-ljspeech",
-    device=-1                 # force CPU
-)
 
 def speak(text: str):
     if not text.strip():
         return None
-    out = tts(text)
-    return (out["sampling_rate"], out["audio"])
+    # Generate speech via Google Translate TTS
+    tts = gTTS(text)
+    # Write to a temp file and return its path
+    tmp = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
+    tts.write_to_fp(tmp)
+    tmp.flush()
+    return tmp.name
 
-with gr.Blocks(title="TTS Demo") as demo:
-    gr.Markdown("# 🔊 Simple Text-to-Speech\nType text, click **Speak**.")
-    txt = gr.Textbox(lines=3, placeholder="Enter English text here…")
+with gr.Blocks(title="🗣️ Simple TTS (gTTS)") as demo:
+    gr.Markdown("# 🗣️ Text-to-Speech\nType any text below and click **Speak**.")
+    inp = gr.Textbox(lines=3, placeholder="Enter text here...")
     btn = gr.Button("Speak 🔈", variant="primary")
-    audio = gr.Audio(label="Output", type="numpy")
-    btn.click(speak, txt, audio)
+    out = gr.Audio(label="Output audio", type="filepath")
+    btn.click(speak, inp, out)
 
 if __name__ == "__main__":
     demo.launch(server_name="0.0.0.0")