Create simpler_app.py

simpler_app.py

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+import gradio as gr
+import requests
+import json
+# from volcenginesdkarkruntime import Ark
+import torch
+import torchaudio
+from einops import rearrange
+import argparse
+import json
+import os
+import spaces
+from tqdm import tqdm
+import random
+import numpy as np
+import sys
+import base64
+from diffrhythm.infer.infer_utils import (
+    get_reference_latent,
+    get_lrc_token,
+    get_style_prompt,
+    prepare_model,
+    get_negative_style_prompt
+)
+from diffrhythm.infer.infer import inference
+
+MAX_SEED = np.iinfo(np.int32).max
+device='cuda'
+cfm, tokenizer, muq, vae = prepare_model(device)
+cfm = torch.compile(cfm)
+
+def infer_music(lrc, ref_audio_path, seed=42, randomize_seed=False, steps=32, file_type='wav', max_frames=2048, device='cuda'):
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    torch.manual_seed(seed)
+    sway_sampling_coef = -1 if steps < 32 else None
+    lrc_prompt, start_time = get_lrc_token(lrc, tokenizer, device)
+    style_prompt = get_style_prompt(muq, ref_audio_path)
+    negative_style_prompt = get_negative_style_prompt(device)
+    latent_prompt = get_reference_latent(device, max_frames)
+    generated_song = inference(cfm_model=cfm, 
+                               vae_model=vae, 
+                               cond=latent_prompt, 
+                               text=lrc_prompt, 
+                               duration=max_frames, 
+                               style_prompt=style_prompt,
+                               negative_style_prompt=negative_style_prompt,
+                               steps=steps,
+                               sway_sampling_coef=sway_sampling_coef,
+                               start_time=start_time,
+                               file_type=file_type
+                               )
+    return generated_song
+
+import re 
+from transformers import pipeline
+
+zephyr_model = "HuggingFaceH4/zephyr-7b-beta"
+mixtral_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+
+pipe = pipeline("text-generation", model=zephyr_model, torch_dtype=torch.bfloat16, device_map="auto")
+
+
+
+def prepare_lyrics_with_llm(theme, tags, lyrics):
+
+    language = "English"
+    standard_sys = f"""
+Please generate a complete song with lyrics in {language}, following the {tags} style and centered around the theme "{theme}".
+If {lyrics} is provided, format it accordingly. 
+If {lyrics} is None, generate original lyrics based on the given theme and style. 
+
+Strictly adhere to the following requirements:
+
+### Mandatory Formatting Rules
+1. Only output the formatted lyrics—do not include any explanations, introductions, or additional messages.
+2. Only include timestamps and lyrics. Do not use brackets, side notes, or section markers (e.g., chorus, instrumental, outro).
+3. Each line must follow the format [mm:ss.xx]Lyrics content, with no spaces between the timestamp and lyrics. The lyrics should be continuous and complete.
+4. The total song length must not exceed 1 minute 30 seconds.
+5. Timestamps should be naturally distributed. The first lyric must not start at [00:00.00]—consider an intro before the lyrics begin.
+
+### Prohibited Examples (Do Not Include)
+- Incorrect: [01:30.00](Piano solo)
+- Incorrect: [00:45.00][Chorus]
+"""
+
+    instruction = f"""
+<|system|>
+{standard_sys}</s>
+<|user|>
+theme: {theme}
+tags: {tags}
+lyrics: {lyrics}
+"""
+    
+    prompt = f"{instruction.strip()}</s>"    
+    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+    pattern = r'\<\|system\|\>(.*?)\<\|assistant\|\>'
+    cleaned_text = re.sub(pattern, '', outputs[0]["generated_text"], flags=re.DOTALL)
+    
+    print(f"SUGGESTED Lyrics: {cleaned_text}")
+    return cleaned_text.lstrip("\n")
+
+def general_process(theme, tags, lyrics):
+    result = prepare_lyrics_with_llm(theme, tags, lyrics)
+    return None, result
+
+    
+with gr.Blocks(css=css) as demo:
+    with gr.Column():
+        gr.Markdown("# Simpler Diff Rythm")
+
+        theme_song = gr.Textbox(label="Theme")
+        style_tags = gr.Textbox(label="Music style tags")
+        lyrics = gr.Textbox(label="Lyrics optional")
+        submit_btn = gr.Button("Submit")
+        song_result = gr.Audio(label="Song result")
+        generated_lyrics = gr.Textbox(label="Generated Lyrics")
+
+    submit_btn.click(
+        fn = general_process,
+        inputs = [theme_song, style_tags, lyrics],
+        outputs = [song_result, generated_lyrics]
+    )
+
+demo.queue().launch(show_api=False, show_error=True, ssr_mode=False)