Update app.py

app.py

@@ -10,6 +10,9 @@ from demucs import pretrained
 from demucs.apply import apply_model
 import torchaudio
 from pathlib import Path
+import matplotlib.pyplot as plt
+from io import BytesIO
+from PIL import Image
 
 # === Helper Functions ===
 def audiosegment_to_array(audio):
@@ -95,7 +98,7 @@ def apply_vocal_isolation(audio_path):
     save_track(out_path, vocal_track, model.samplerate)
     return out_path
 
-# === Preset Loader ===
+# === Preset Loader with Fallback ===
 def load_presets():
     try:
         preset_files = [f for f in os.listdir("presets") if f.endswith(".json")]
@@ -116,15 +119,35 @@ def load_presets():
         print("Presets folder not found")
         return {}
 
-# Always define preset_choices, even if empty
 preset_choices = load_presets()
 
-# Provide fallback if no presets found
 if not preset_choices:
-    preset_choices = {"Default": []}
+    preset_choices = {
+        "Default": [],
+        "Clean Podcast": ["Noise Reduction", "Normalize"],
+        "Music Remix": ["Bass Boost", "Stereo Widening"]
+    }
+
+preset_names = list(preset_choices.keys())
+
+# === Waveform Generator ===
+def show_waveform(audio_file):
+    try:
+        audio = AudioSegment.from_file(audio_file)
+        samples = np.array(audio.get_array_of_samples())
+        plt.figure(figsize=(10, 2))
+        plt.plot(samples[:10000], color="blue")
+        plt.axis("off")
+        buf = BytesIO()
+        plt.savefig(buf, format="png", bbox_inches="tight", dpi=100)
+        plt.close()
+        buf.seek(0)
+        return Image.open(buf)
+    except Exception as e:
+        return None
 
 # === Main Processing Function ===
-def process_audio(audio_file, selected_effects, isolate_vocals, preset_name):
+def process_audio(audio_file, selected_effects, isolate_vocals, preset_name, export_format):
     audio = AudioSegment.from_file(audio_file)
 
     effect_map = {
@@ -139,7 +162,6 @@ def process_audio(audio_file, selected_effects, isolate_vocals, preset_name):
         "Normalize": apply_normalize,
     }
 
-    # Apply selected preset or custom effects
     effects_to_apply = preset_choices.get(preset_name, selected_effects)
     for effect_name in effects_to_apply:
         if effect_name in effect_map:
@@ -155,8 +177,8 @@ def process_audio(audio_file, selected_effects, isolate_vocals, preset_name):
             final_audio = audio
 
         output_path = f.name
-        final_audio.export(output_path, format="mp3")
-        return output_path
+        final_audio.export(output_path, format=export_format.lower())
+        return output_path, show_waveform(output_path)
 
 # === Gradio Interface ===
 effect_options = [
@@ -171,19 +193,21 @@ effect_options = [
     "Normalize"
 ]
 
-preset_names = list(preset_choices.keys())
-
 interface = gr.Interface(
     fn=process_audio,
     inputs=[
         gr.Audio(label="Upload Audio", type="filepath"),
         gr.CheckboxGroup(choices=effect_options, label="Apply Effects in Order"),
         gr.Checkbox(label="Isolate Vocals After Effects"),
-        gr.Dropdown(choices=preset_names, label="Select Preset", value=preset_names[0] if preset_names else None)
+        gr.Dropdown(choices=preset_names, label="Select Preset", value=preset_names[0] if preset_names else None),
+        gr.Dropdown(choices=["MP3", "WAV"], label="Export Format", value="MP3")
+    ],
+    outputs=[
+        gr.Audio(label="Processed Audio", type="filepath"),
+        gr.Image(label="Waveform Preview")
     ],
-    outputs=gr.Audio(label="Processed Audio (MP3)", type="filepath"),
     title="AI Audio Studio - Pro Edition",
-    description="Apply multiple effects, isolate vocals, and export polished tracks -- all powered by AI!",
+    description="Apply multiple effects, isolate vocals, and export polished tracks — all powered by AI!",
     allow_flagging="never"
 )