add mixups

app.py

@@ -1,108 +1,106 @@
 import streamlit as st
-import librosa
-import numpy as np
 import requests
+import numpy as np
 import os
-# import noisereduce as nr
-
-# Replace with your actual API endpoint URL
-API_URL = "https://jwry1smafa0ql7pc.us-east-1.aws.endpoints.huggingface.cloud"
+from pydub import AudioSegment
+
+# Try to get API_URL from environment variables, if not found set to a default value
+try:
+    API_URL = os.environ["API_URL"]
+except KeyError:
+    st.error("API_URL environment variable is not set.")
+    st.stop()
+
+# Try to get the Bearer token from environment variables, if not found set to a default value
+try:
+    BEARER_TOKEN = os.environ["BEARER_TOKEN"]
+except KeyError:
+    st.error("BEARER_TOKEN environment variable is not set.")
+    st.stop()
 
-# Retrieve the token from environment variables using `os.getenv()`
-TOKEN = os.getenv("ACCESS_TOKEN")
-
-# Set headers with the retrieved token
 headers = {
-    "Authorization": f"Bearer {TOKEN}",
+    "Authorization": f"Bearer {BEARER_TOKEN}",
+    "Content-Type": "application/json"
 }
 
-
-def query(payload):
-    """Sends a POST request to the API endpoint with the given payload."""
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
-
-
-def main():
-    """
-    Creates the Streamlit app for uploading audio (optional),
-    and sending it to an API for music generation.
-    """
-    st.title("SonglabAI")
-
-    # 25 genres
-    genres = [
-        "Pop", "Rock", "Jazz", "Electronic", "Hip-Hop",
-        "Classical", "Lofi", "Chillpop", "Bossa Nova",
-        "Country", "Reggae", "Funk", "Blues", "Metal",
-        "R&B", "Indie", "Soul", "Folk", "Disco",
-        "Techno", "Ambient", "Dance", "Ska", "Trap"
-    ]
-
-    selected_genre = st.selectbox("Select Genre", genres)
-    prompt = st.text_input("Enter Music Description")
-
-    # bpm
-    bpm = st.number_input("Enter Speed in BPM", min_value=60)
-
-    # Duration input
-    duration = st.slider("Select Duration (in seconds)", 15, 300, 15, step=5)
-
-    uploaded_audio = None
-
-    # Optional audio upload
-    if st.checkbox("Upload Melody"):
-        uploaded_file = st.file_uploader("Choose an audio file", type=["mp3", "wav"])
-        if uploaded_file is not None:
-            try:
-                audio_bytes = uploaded_file.read()
-                audio, sample_rate = librosa.load(audio_bytes, sr=None)  # Avoid resampling
-                if sample_rate != 32000:
-                    st.text("Resampling audio to 32,000 Hz...")
-                    audio = librosa.resample(audio, sample_rate, 32000)
-                uploaded_audio = audio[:int(32000 * 15)]  # Extract first 15 seconds
-            except Exception as e:
-                st.error(f"Error processing audio: {e}")
-
-    if st.button("Generate Music"):
-        if not prompt:
-            st.error("Please enter a music description.")
-        elif selected_genre:
-            st.text("Preparing request...")
-
-            # Prepare the payload based on presence/absence of uploaded audio
-            payload = {
-                "inputs": {"prompt": f"{prompt} {selected_genre} {bpm} bpm", "duration": int(duration)}
-            }
-
-            if uploaded_audio is not None:
-                payload = {"inputs": {"prompt": f"{prompt} {selected_genre} {bpm} bpm", "duration": int(duration),
-                                      "melody": uploaded_audio.tolist()}}
-
-            try:
-                # Send the request and handle the response
-                response = query(payload)
-
-                if "error" in response:
-                    st.error(f"Error from API: {response['error']}")
-                else:
-                    arr = np.array(response[0]["generated_audio"])
-                    sr = 32000
-                    audio = arr.astype(np.float32)
-                    # reduced_noise = nr.reduce_noise(audio, sr=sr)  # Apply noise reduction
-                    # audio = reduced_noise  # Use the noise-reduced audio
-                    # stereo_audio = np.stack((audio, audio), axis=1)
-                    sr = 32000
-                    if audio is not None:
-                        st.success("Audio generation complete.")
-                        st.audio(audio, format="audio/wav", sample_rate=sr)
-                    else:
-                        st.warning(
-                            "Unexpected response structure. Missing 'generated_audio'."
-                        )
-            except Exception as e:
-                st.error(f"Unexpected error: {e}")
-
-
-if __name__ == "__main__":
-    main()
+# Streamlit app title
+st.title("Songlabai")
+
+genres = [
+    "Pop", "Rock", "Hip Hop", "Jazz", "Blues",
+    "Country", "Classical", "Electronic", "Reggae",
+    "Folk", "R&B", "Metal", "Punk", "Indie",
+    "Dance", "World", "Gospel", "Soul", "Funk",
+    "Ambient", "Techno", "Disco", "House", "Trance",
+    "Dubstep"
+]
+
+genre = st.selectbox("Select Genre:", genres)
+energy_levels = ["Low", "Medium", "High"]
+energy_level = st.radio("Energy Level:", energy_levels)
+description = st.text_input("Description:", "")
+
+# Duration input
+duration = st.slider("Duration (in seconds):", min_value=15, max_value=90, value=30, step=1)
+
+# Generate audio based on the user's prompt
+if st.button("Generate Audio"):
+    prompt = f"{genre}, Energy: {energy_level}, Description: {description}"
+    st.text("Generating audio...")
+    response = requests.post(API_URL, headers=headers, json={"inputs": {"prompt": prompt, "duration": duration}})
+    audio = np.array(response.json()[0]['generated_audio'], dtype=np.float32)
+    sample_rate = response.json()[0]['sample_rate']
+    st.audio(audio, format="audio/wav", sample_rate=sample_rate, start_time=0)
+
+# Post-processing options
+st.sidebar.title("Post-processing Options")
+apply_stereo = st.sidebar.checkbox("Apply Stereo Effect")
+reverse = st.sidebar.checkbox("Reverse Audio")
+change_speed = st.sidebar.checkbox("Change Speed")
+if change_speed:
+    speed_factor = st.sidebar.slider("Speed Factor:", min_value=0.1, max_value=2.0, value=1.0, step=0.1)
+
+# Pitch shifting
+st.sidebar.title("Pitch Shifting")
+pitch_shift = st.sidebar.checkbox("Pitch Shift")
+if pitch_shift:
+    pitch_semitones = st.sidebar.slider("Pitch (semitones):", min_value=-12, max_value=12, value=0, step=1)
+
+# Reverb
+st.sidebar.title("Reverb")
+add_reverb = st.sidebar.checkbox("Add Reverb")
+if add_reverb:
+    reverb_room_scale = st.sidebar.slider("Room Scale:", min_value=0.0, max_value=100.0, value=50.0)
+    reverb_damping = st.sidebar.slider("Damping:", min_value=0.0, max_value=100.0, value=50.0)
+    reverb_wet_only = st.sidebar.checkbox("Wet Only", value=False)
+
+# Apply selected post-processing
+if apply_stereo or reverse or change_speed or pitch_shift or add_reverb:
+    st.text("Applying post-processing...")
+
+    # Convert audio to pydub AudioSegment
+    audio_segment = AudioSegment(audio.tobytes(), frame_rate=sample_rate, sample_width=audio.itemsize, channels=1)
+
+    # Apply selected post-processing
+    if apply_stereo:
+        audio_segment = audio_segment.pan(-0.5).overlay(audio_segment.pan(0.5))
+
+    if reverse:
+        audio_segment = audio_segment.reverse()
+
+    if change_speed:
+        audio_segment = audio_segment.speedup(playback_speed=speed_factor)
+
+    if pitch_shift:
+        audio_segment = audio_segment._spawn(audio_segment.raw_data, overrides={
+            "frame_rate": int(audio_segment.frame_rate * (2 ** (pitch_semitones / 12.0)))
+        })
+
+    if add_reverb:
+        audio_segment = audio_segment.reverb(reverberance=reverb_room_scale,
+                                              damping=reverb_damping,
+                                              wet_only=reverb_wet_only,
+                                              room_scale=100)
+
+    # Play the processed audio
+    st.audio(audio_segment.raw_data, format="audio/wav", start_time=0)