Add ffmpeg

Dockerfile

@@ -9,7 +9,7 @@ RUN DEBIAN_FRONTEND="noninteractive" apt-get -qq update && \
     DEBIAN_FRONTEND="noninteractive" apt-get install -y tzdata
 
 RUN apt-get update -qq && \
-    apt-get install -qq python3-pip build-essential libasound2-dev libjack-dev wget cmake pkg-config libglib2.0-dev
+    apt-get install -qq python3-pip build-essential libasound2-dev libjack-dev wget cmake pkg-config libglib2.0-dev ffmpeg
 
 # Download libfluidsynth source
 RUN wget https://github.com/FluidSynth/fluidsynth/archive/refs/tags/v2.3.3.tar.gz && \

main.py

@@ -17,20 +17,32 @@ DESCRIPTION = """
 # 🎵 Multitrack Midi Generator 🎶
 This interactive application uses an AI model to generate music sequences based on a chosen genre and various user inputs.
 
-## Features:
-- 🎼 Select the genre for the music.
-- 🌡️ Use the "Temperature" slider to adjust the randomness of the music generated (higher values will produce more random outputs).
-- ⏱️ Adjust the "Tempo" slider to change the speed of the music.
-- 🎹 Use the buttons to generate a new song from scratch, continue generation with the current settings, remove the last added instrument, regenerate the last added instrument with a new one, or change the tempo of the current song.
-
-## Outputs:
-The app outputs the following:
-
-- 🎧 The audio of the generated song.
-- 📁 A MIDI file of the song.
-- 📊 A plot of the song's sequence.
-- 🎸 A list of the generated instruments.
-- 📝 The text sequence of the song.
+<table>
+    <tr>
+        <td valign="top">
+
+        ## Features:
+        - 🎼 Select the genre for the music.
+        - 🌡️ Use the "Temperature" slider to adjust the randomness of the music generated (higher values will produce more random outputs).
+        - ⏱️ Adjust the "Tempo" slider to change the speed of the music.
+        - 🎹 Use the buttons to generate a new song from scratch, continue generation with the current settings, remove the last added instrument, regenerate the last added instrument with a new one, or change the tempo of the current song.
+
+        </td>
+        <td valign="top">
+
+        ## Outputs:
+        The app outputs the following:
+
+        - 🎧 The audio of the generated song.
+        - 📁 A MIDI file of the song.
+        - 📊 A plot of the song's sequence.
+        - 🎸 A list of the generated instruments.
+        - 📝 The text sequence of the song.
+
+        </td>
+    </tr>
+</table>
+
 Enjoy creating your own AI-generated music! 🎵
 """
 

utils.py

@@ -16,9 +16,7 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # Load the tokenizer and the model
 tokenizer = AutoTokenizer.from_pretrained("juancopi81/lmd_8bars_tokenizer")
-model = AutoModelForCausalLM.from_pretrained(
-    "juancopi81/lmd-8bars-2048-epochs20_v3"
-)
+model = AutoModelForCausalLM.from_pretrained("juancopi81/lmd-8bars-2048-epochs20_v3")
 
 # Move model to device
 model = model.to(device)
@@ -60,9 +58,7 @@ def get_instruments(text_sequence: str) -> List[str]:
     return instruments
 
 
-def generate_new_instrument(
-    seed: str, temp: float = 0.75
-) -> str:
+def generate_new_instrument(seed: str, temp: float = 0.75) -> str:
     """
     Generates a new instrument sequence from a given seed and temperature.
 
@@ -242,9 +238,7 @@ def generate_song(
     else:
         seed_string = text_sequence
 
-    generated_sequence = generate_new_instrument(
-        seed=seed_string, temp=temp
-    )
+    generated_sequence = generate_new_instrument(seed=seed_string, temp=temp)
     audio, midi_file, fig, instruments_str, num_tokens = get_outputs_from_string(
         generated_sequence, qpm
     )