Create app.py

app.py

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+import random
+import os
+import time
+from queue import Queue
+from threading import Thread
+
+import symusic
+
+import transformers
+import gradio as gr
+
+print('\n\n\n')
+print('Loading model...')
+# pipe = transformers.pipeline("text-generation", model="openai-community/gpt2")
+pipe = transformers.pipeline(
+    "text-generation", 
+    model="dx2102/llama-midi",
+    torch_dtype="bfloat16",
+    device_map="auto",
+)
+print('Done')
+
+default_prefix = '''pitch duration wait
+
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+'''
+default_prefix_len = default_prefix.count('\n') - 2
+
+
+def postprocess(txt, path):
+    # saves the text representation to a midi file
+    txt = txt.split('\n\n')[-1]
+
+    notes = []
+    now = 0
+    # we need to ignore the invalid output by the model
+    try:
+        for line in txt.split('\n'):
+            pitch, duration, wait = [int(x) for x in line.split()]
+            # Eg. Note(time=7.47, duration=5.25, pitch=43, velocity=64, ttype='Quarter')
+            notes.append(symusic.core.NoteSecond(
+                time=now/1000,
+                duration=duration/1000,
+                pitch=int(pitch),
+                velocity=80,
+            ))
+            now += wait
+    except Exception as e:
+        print('Ignored error:', e)
+
+    try:
+        track = symusic.core.TrackSecond()
+        track.notes = symusic.core.NoteSecondList(notes)
+        score = symusic.Score(ttype='Second')
+        score.tracks.append(track)
+        score.dump_midi(path)
+    except Exception as e:
+        print('Ignored error:', e)
+
+with gr.Blocks() as demo:
+    chatbot_box = gr.Chatbot(type="messages", render_markdown=False, sanitize_html=False)
+    prefix_box = gr.Textbox(value=default_prefix, label="prefix")
+    with gr.Row():
+        submit_btn = gr.Button("Submit")
+        clear_btn = gr.Button("Clear")
+    with gr.Row():
+        get_audio_btn = gr.Button("Convert to audio")
+        get_midi_btn = gr.Button("Convert to MIDI")
+    audio_box = gr.Audio()
+    midi_box = gr.File()
+    piano_roll_box = gr.Image()
+
+    def user_fn(user_message, history: list):
+        return "", history + [{"role": "user", "content": user_message}]
+
+    def bot_fn(history: list):
+        prefix = history[-1]["content"]
+        history.append({"role": "assistant", "content": ""})
+        if prefix.startswith("pitch duration wait\n\n"):
+            history[-1]["content"] += "Generating with the given prefix...\n"
+        else:
+            history[-1]["content"] += f"Generating from scratch with a default prefix of {default_prefix_len} notes...\n"
+            prefix = default_prefix
+        queue = Queue()
+        class MyStreamer:
+            def put(self, tokens):
+                for token in tokens.flatten():
+                    text = pipe.tokenizer.decode(token.item())
+                    if text == '<|begin_of_text|>':
+                        continue
+                    queue.put(text)
+            def end(self):
+                queue.put(None)
+        def background_fn():
+            result = pipe(
+                prefix,
+                streamer=MyStreamer(), 
+                max_length=1000,
+                temperature=0.95,
+            )
+            print('Generated text:')
+            print(result[0]['generated_text'])
+            print()
+        Thread(target=background_fn).start()
+        while True:
+            text = queue.get()
+            if text is None:
+                break
+            history[-1]["content"] += text
+            yield history
+
+    prefix_box.submit(user_fn, [prefix_box, chatbot_box], [prefix_box, chatbot_box], queue=False).then(
+        bot_fn, chatbot_box, chatbot_box
+    )
+    submit_btn.click(user_fn, [prefix_box, chatbot_box], [prefix_box, chatbot_box], queue=False).then(
+        bot_fn, chatbot_box, chatbot_box
+    )
+    clear_btn.click(lambda: None, None, chatbot_box, queue=False)
+
+    def get_audio_fn(history):
+        i = random.randint(0, 1000_000_000)
+        path = f'./temp/{i}.mid'
+        try:
+            postprocess(history[-1]["content"], path)
+        except Exception as e:
+            raise gr.Error(f'Error: {type(e)}, {e}')
+        # turn midi into audio with timidity
+        os.system(f'timidity ./temp/{i}.mid -Ow -o ./temp/{i}.wav')
+        # wav to mp3
+        os.system(f'lame -b 320 ./temp/{i}.wav ./temp/{i}.mp3')
+        return f'./temp/{i}.mp3'
+    
+    get_audio_btn.click(get_audio_fn, chatbot_box, audio_box, queue=False)
+
+    def get_midi_fn(history):
+        i = random.randint(0, 1000_000_000)
+        # turn the text into midi
+        try:
+            postprocess(history[-1]["content"], f'./temp/{i}.mid')
+        except Exception as e:
+            raise gr.Error(f'Error: {type(e)}, {e}')
+        # also render the piano roll
+        import matplotlib.pyplot as plt
+        plt.figure(figsize=(12, 4))
+        now = 0
+        for line in history[-1]["content"].split('\n\n')[-1].split('\n'):
+            try:
+                pitch, duration, wait = [int(x) for x in line.split()]
+            except Exception as e:
+                continue
+            plt.plot([now, now+duration], [pitch, pitch], color='black')
+            now += wait
+        plt.savefig(f'./temp/{i}.svg')
+        return f'./temp/{i}.mid', f'./temp/{i}.svg'
+    
+    get_midi_btn.click(get_midi_fn, inputs=chatbot_box, outputs=[midi_box, piano_roll_box], queue=False)
+
+
+demo.launch()