Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+import soundfile as sf
+import tempfile
+
+# Streamlit page setup
+st.set_page_config(page_title="Hugging Face Text-to-Speech", page_icon="🎤", layout="centered")
+st.title("🎤 Text to Speech Converter (Hugging Face)")
+
+# Text input from user
+text = st.text_area("Enter the text you want to convert to speech:", height=150)
+
+# Choose model
+model_name = st.selectbox(
+    "Select a Hugging Face TTS model:",
+    ["suno/bark-small", "facebook/speecht5_tts", "espnet/kan-bayashi_ljspeech_vits"],
+    index=0
+)
+
+if st.button("Convert to Speech"):
+    if text.strip() == "":
+        st.warning("Please enter some text.")
+    else:
+        st.info("Generating speech... please wait ⏳")
+        tts = pipeline("text-to-speech", model=model_name)
+        output = tts(text)
+
+        # Get audio and sampling rate
+        audio = output["audio"]
+        sr = output["sampling_rate"]
+
+        # Save audio to a temporary file
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmpfile:
+            sf.write(tmpfile.name, audio, sr)
+            audio_path = tmpfile.name
+
+        st.success("✅ Conversion complete!")
+        st.audio(audio_path, format="audio/wav")
+        st.download_button(
+            label="📥 Download Audio",
+            data=open(audio_path, "rb").read(),
+            file_name="tts_output.wav",
+            mime="audio/wav"
+        )