Update app.py

app.py

@@ -2,17 +2,17 @@ import gradio as gr
 from TTS.api import TTS
 import time
 import os
-from fastapi import FastAPI
-from pydantic import BaseModel
-import base64
 
-# ------------------- TTS Setup -------------------
+# Fixed model (YourTTS in English)
 YOURTTS_MODEL = "tts_models/multilingual/multi-dataset/your_tts"
-FIXED_SPEAKER_PATH = "speakers/voice1.wav"
 
+# Fixed speaker file (pre-cloned voice)
+FIXED_SPEAKER_PATH = "speakers/voice2.wav"
+
+# Initialize model once
 tts = TTS(YOURTTS_MODEL, gpu=False)
 
-def synthesize(text: str):
+def synthesize(text):
     output_path = "output.wav"
     start_time = time.time()
 
@@ -41,7 +41,7 @@ def synthesize(text: str):
         "speaker_used": FIXED_SPEAKER_PATH.split("/")[-1]
     }
 
-# ------------------- Gradio UI -------------------
+# ------------------ Gradio UI ------------------
 with gr.Blocks() as demo:
     gr.Markdown("## 🗣️ YourTTS Voice Cloning (English Only, Fixed Speaker)")
 
@@ -52,6 +52,7 @@ with gr.Blocks() as demo:
     )
 
     generate_btn = gr.Button("🔊 Generate Speech")
+
     output_audio = gr.Audio(label="Output Audio", type="filepath")
     metadata_json = gr.JSON(label="Meta Info (Time, Model, RTF, etc.)")
 
@@ -61,35 +62,16 @@ with gr.Blocks() as demo:
         outputs=[output_audio, metadata_json]
     )
 
-# ------------------- FastAPI Setup -------------------
-app = FastAPI(title="YourTTS FastAPI")
-
-class TTSRequest(BaseModel):
-    text: str
-
-@app.post("/synthesize/")
-async def tts_endpoint(req: TTSRequest):
-    output_path, metadata = synthesize(req.text)
-    if output_path is None:
-        return {"error": metadata.get("error")}
-
-    # Return Base64-encoded audio
-    with open(output_path, "rb") as f:
-        audio_bytes = f.read()
-    audio_base64 = base64.b64encode(audio_bytes).decode("utf-8")
-
-    return {
-        "audio_base64": audio_base64,
-        "metadata": metadata
-    }
-
-# ------------------- Launch -------------------
-if __name__ == "__main__":
-    import threading
-    import uvicorn
-
-    # Start Gradio UI in a separate thread
-    threading.Thread(target=lambda: demo.launch(server_name="0.0.0.0", server_port=7860)).start()
-
-    # Start FastAPI
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+# ------------------ API Interface ------------------
+api_demo = gr.Interface(
+    fn=synthesize,
+    inputs=[gr.Text(label="Text")],   # Only text input
+    outputs=[
+        gr.Audio(type="filepath", label="Generated Audio"),
+        gr.JSON(label="Metadata")
+    ],
+    title="YourTTS Voice Cloning (English Only, Fixed Speaker)"
+)
+
+# Launch the app with both UI and API
+demo.launch(server_name="0.0.0.0", server_port=7860, show_api=True)