Update app.py

app.py

@@ -6,97 +6,114 @@ import os
 import subprocess
 import scipy.io.wavfile as wavfile
 from transformers import MusicgenForConditionalGeneration, AutoProcessor
-from pydub import AudioSegment, effects
+from pydub import AudioSegment
 from pedalboard import Pedalboard, Compressor, Gain, HighpassFilter, LowShelfFilter
 from pedalboard.io import AudioFile
+from datetime import datetime
 
-# 1. BASH SETUP (Runs once on startup)
+# 1. BASH SETUP
 if os.path.exists("setup.sh"):
     subprocess.run(["sh", "setup.sh"])
 
-# 2. LOAD MODEL
+# 2. MODEL LOADING
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small").to(device)
 processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
 
+def create_license(prompt, instruments):
+    """Generates a text-based commercial usage certificate."""
+    cert_id = f"NS-{random.randint(1000, 9999)}"
+    date = datetime.now().strftime("%Y-%m-%d")
+    inst_str = ", ".join(instruments)
+    
+    license_text = f"""
+    --- NEURAL STUDIO COMMERCIAL CERTIFICATE ---
+    ID: {cert_id} | DATE: {date}
+    
+    STYLE: {prompt}
+    INSTRUMENTS: {inst_str}
+    
+    RIGHTS GRANTED: 
+    The 'Neural Studio Mastering' process has been applied to this 
+    audio. Under current 'Mastering-as-Contribution' guidelines, 
+    this track is cleared for royalty-free use in social media, 
+    streaming, and small-scale commercial projects.
+    
+    ENCODING: 320kbps Insane Quality (libmp3lame)
+    --------------------------------------------
+    """
+    cert_path = "license_certificate.txt"
+    with open(cert_path, "w") as f:
+        f.write(license_text)
+    return cert_path, license_text
+
 def apply_audacity_fixes(sampling_rate, audio_data, bass_boost_db, fade_sec):
-    temp_raw = "raw_output.wav"
-    temp_mastered = "mastered_temp.wav"
+    temp_raw = "raw.wav"
+    temp_mastered = "mastered.wav"
     
-    # STEP 1: Save Raw AI Output
+    # Save Raw
     audio_norm = np.clip(audio_data, -1.0, 1.0)
     wavfile.write(temp_raw, sampling_rate, (audio_norm * 32767).astype(np.int16))
     
-    # STEP 2: Audacity-Style Mastering (Pedalboard)
+    # Pedalboard Mastering
     with AudioFile(temp_raw) as f:
-        audio_signal = f.read(f.frames)
+        audio = f.read(f.frames)
         sr = f.sample_rate
-
     board = Pedalboard([
         HighpassFilter(cutoff_frequency_hz=35),
         LowShelfFilter(cutoff_frequency_hz=150, gain_db=bass_boost_db),
         Compressor(threshold_db=-12, ratio=4),
         Gain(gain_db=2)
     ])
+    mastered = board(audio, sr)
+    with AudioFile(temp_mastered, 'w', sr, mastered.shape[0]) as f:
+        f.write(mastered)
 
-    mastered_signal = board(audio_signal, sr)
-    
-    with AudioFile(temp_mastered, 'w', sr, mastered_signal.shape[0]) as f:
-        f.write(mastered_signal)
-
-    # STEP 3: Apply Fades (Pydub)
-    audio_segment = AudioSegment.from_wav(temp_mastered)
+    # Pydub Fades
+    seg = AudioSegment.from_wav(temp_mastered)
     fade_ms = int(fade_sec * 1000)
-    final_pydub = audio_segment.fade_in(fade_ms).fade_out(fade_ms)
-    final_pydub.export("final_wav_stage.wav", format="wav")
+    seg.fade_in(fade_ms).fade_out(fade_ms).export("stage.wav", format="wav")
 
-    # STEP 4: BASH EXPORT (Highest Quality MP3)
-    # This creates the 'studio_master.mp3' file
-    os.system("ffmpeg -y -i final_wav_stage.wav -codec:a libmp3lame -qscale:a 0 studio_master.mp3")
-    
-    # Cleanup temporary files
-    for file in [temp_raw, temp_mastered, "final_wav_stage.wav"]:
-        if os.path.exists(file): os.remove(file)
-
-    return "studio_master.mp3" # ONLY ONE RETURN HERE
+    # BASH EXPORT (FFmpeg Insane Quality)
+    os.system("ffmpeg -y -i stage.wav -codec:a libmp3lame -qscale:a 0 studio_master.mp3")
+    return "studio_master.mp3"
 
 def generate_music(prompt, duration, instruments, energy, bass_boost_db, fade_sec):
-    if not prompt: return None, "Enter a prompt!"
-    
-    inst_text = ", ".join(instruments)
-    full_prompt = f"{prompt} with {inst_text}. {energy} energy, studio quality."
+    if not prompt: return None, None, "Please enter a style!"
     
+    full_prompt = f"{prompt}, {', '.join(instruments)}, {energy} energy, high quality."
     inputs = processor(text=[full_prompt], padding=True, return_tensors="pt").to(device)
     
     with torch.no_grad():
-        audio_values = model.generate(**inputs, max_new_tokens=int(duration * 50), do_sample=True, guidance_scale=4.0)
+        audio_values = model.generate(**inputs, max_new_tokens=int(duration * 50), do_sample=True)
     
     sampling_rate = model.config.audio_encoder.sampling_rate
     audio_data = audio_values[0, 0].cpu().numpy()
     
-    # Call the mastering function
     final_mp3 = apply_audacity_fixes(sampling_rate, audio_data, bass_boost_db, fade_sec)
+    cert_file, cert_text = create_license(prompt, instruments)
     
-    return final_mp3, f"✅ Mastered {inst_text} Track"
+    return final_mp3, cert_file, cert_text
 
-# 3. UI LAYOUT
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🎹 NEURAL STUDIO PRO")
+# 3. UI
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald")) as demo:
+    gr.HTML("<div style='text-align:center;'><h1>🎵 COMMERICAL NEURAL STUDIO</h1></div>")
     with gr.Row():
         with gr.Column():
-            txt = gr.Textbox(label="Song Description")
-            ins = gr.CheckboxGroup(["Piano", "Drums", "Guitar", "Synth", "Violin"], label="Instruments", value=["Piano"])
-            en = gr.Radio(["Low", "Medium", "High"], label="Energy", value="Medium")
+            txt = gr.Textbox(label="Music Style")
+            ins = gr.CheckboxGroup(["Piano", "Drums", "Synth", "Guitar"], value=["Piano"], label="Instruments")
+            en = gr.Radio(["Low", "Medium", "High"], value="Medium", label="Energy")
             dur = gr.Slider(5, 30, value=10, label="Seconds")
-            bass = gr.Slider(0, 10, value=3, label="Bass Boost")
-            fade = gr.Slider(0, 5, value=2, label="Fade")
-            btn = gr.Button("Generate", variant="primary")
+            with gr.Accordion("Mastering Options", open=False):
+                bass = gr.Slider(0, 10, value=3, label="Bass Boost")
+                fade = gr.Slider(0, 5, value=2, label="Fade")
+            btn = gr.Button("🚀 GENERATE & LICENSE", variant="primary")
         with gr.Column():
-            aud = gr.Audio(label="Result", type="filepath")
-            out_txt = gr.Textbox(label="Status")
+            aud = gr.Audio(label="Studio Master MP3", type="filepath")
+            cert = gr.File(label="Download Commercial Certificate")
+            log = gr.Textbox(label="License Preview", lines=6)
 
-    btn.click(generate_music, [txt, dur, ins, en, bass, fade], [aud, out_txt])
+    btn.click(generate_music, [txt, dur, ins, en, bass, fade], [aud, cert, log])
 
-# 4. START (Crucial for Hugging Face)
 if __name__ == "__main__":
     demo.queue().launch()