Delete app.py

app.py

@@ -1,67 +0,0 @@
-import sys, os, torch
-# sys.path.append("Testing/")
-import gradio as gr
-from inference import infer, prepare_inputs, load_t2s_model, load_cfm, create_wav_header
-from tqdm import tqdm
-
-# Setup
-os.makedirs("generated_samples/", exist_ok=True)
-device = "cuda" if torch.cuda.is_available() else "cpu"
-print("Using device", device)
-
-# Model checkpoints
-m1_checkpoint = "pretrained_checkpoint/m1_gemma_benchmark_1_latest_weights.pt"
-m2_checkpoint = "pretrained_checkpoint/m2.pt"
-vocoder_checkpoint = 'pretrained_checkpoint/700_580k_multilingual_infer_ready/'
-
-global FM, vocoder, m2, mu, std, m1
-
-# Load models
-FM, vocoder, m2, mu, std = load_cfm(m2_checkpoint, vocoder_checkpoint, device)
-m1 = load_t2s_model(m1_checkpoint, device)
-
-
-# Speaker reference clips
-speaker_refs = {
-    "Speaker1": [
-            "speakers/female1/train_hindifemale_02794.wav",
-            "speakers/female1/train_hindifemale_04167.wav",
-            "speakers/female1/train_hindifemale_02795.wav"
-        ]
-}
-
-# Available languages (can be extended)
-available_languages = ["hindi"]
-
-# Inference function
-def generate_audio(text, speaker_name, language):
-    if speaker_name not in speaker_refs:
-        return f"Reference clips not available for {speaker_name}", None
-
-    ref_clips = speaker_refs[speaker_name]   
-
-    text_ids, code_ids, language_code, ref_mels_m1, ref_mels_m2 = prepare_inputs(
-        text.lower(),
-        ref_clips_m1=ref_clips,
-        ref_clips_m2=ref_clips,
-        language=language,
-        device=device
-    )
-
-    audio_wav = infer(m1, m2, vocoder, FM, mu, std, text_ids, code_ids, language_code, ref_mels_m1, ref_mels_m2, device)
-    return 24000,audio_wav
-
-# Gradio UI
-interface = gr.Interface(
-    fn=generate_audio,
-    inputs=[
-        gr.Textbox(label="Enter Text"),
-        gr.Dropdown(choices=list(speaker_refs.keys()), label="Select Speaker"),
-        gr.Dropdown(choices=available_languages, label="Select Language")
-    ],
-    outputs=gr.Audio(label="Generated Speech"),
-    title="MAHATTSv2 Demo",
-    description="Enter text, choose a speaker and language to generate speech."
-)
-
-interface.launch(share=True,server_port=9999)