repaired docker, added docker-compose

Dockerfile

@@ -1,4 +1,6 @@
-FROM ubuntu:14.04
+FROM ubuntu:18.04
+
+ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update && apt-get install -y \
     pkg-config \
@@ -8,19 +10,26 @@ RUN apt-get update && apt-get install -y \
     libblas-dev \
     liblapack-dev \
     libatlas-base-dev \
+    libsndfile1-dev \
+    libasound2-dev \
+    libjack-dev \
     gfortran \
+    ffmpeg \
+    llvm-8 \
     python \
-    python-dev \
-    python-pip \
+    python3 \
+    python3-dev \
+    python3-pip \
+    python3-venv \
+    nvidia-cuda-dev \
     curl && \
-    curl -sL https://deb.nodesource.com/setup_7.x | sudo -E bash - && \
-    apt-get install -y nodejs
+    curl -sL https://deb.nodesource.com/setup_10.x | bash - && \
+    apt update && apt-get install -y nodejs && apt clean
 
-
-RUN pip install -U https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.1-cp27-none-linux_x86_64.whl
+RUN pip3 install --upgrade pip
 
 COPY ./server/requirements.txt /tmp/
-RUN pip install -r /tmp/requirements.txt
+RUN pip3 install -r /tmp/requirements.txt
 
 COPY . /src/
 
@@ -30,4 +39,4 @@ RUN npm install && npm run build
 WORKDIR /src/server/
 
 EXPOSE 8080
-ENTRYPOINT python server.py
+ENTRYPOINT python3 server.py

README.md

@@ -18,35 +18,6 @@ Built by [Yotam Mann](https://github.com/tambien) with friends on the Magenta an
 
 A.I. Duet is composed of two parts, the front-end which is in the `static` folder and the back-end which is in the `server` folder. The front-end client creates short MIDI files using the players's input which is sent to a [Flask](http://flask.pocoo.org/) server. The server takes that MIDI input and "continues" it using [Magenta](https://github.com/tensorflow/magenta) and [TensorFlow](https://www.tensorflow.org/) which is then returned back to the client. 
 
-## INSTALLATION
-
-A.I. Duet only works with [Python 2.7](https://www.python.org/download/releases/2.7/) and it was tested with Node v6. There are two basic ways of installing A.I. Duet: with Docker or without Docker.
-
-If you already have a Python environment setup, install all of the server dependencies and start the server by typing the following in the terminal:
-
-```bash
-cd server
-pip install -r requirements.txt
-```
-
-If this does not work, jump down to the [Docker](#docker) installation instructions, which will walk you through installing A.I. Duet within a Docker container.
-
-If it _did_ install tensorflow and magenta successfully, you can run the server by typing:
-
-```bash
-python server.py
-```
-
-Then to build and install the front-end Javascript code, first make sure you have [Node.js](https://nodejs.org) 6 installed. And then install of the dependencies of the project and build the code by typing the following in the terminal: 
-
-```bash
-cd static
-npm install
-npm run build
-```
-
-You can now play with A.I. Duet at [localhost:8080](http://localhost:8080).
-
 ## DOCKER
 
 [Docker](https://www.docker.com/) is an open-source containerization software which simplifies installation across various OSes. It is the simplest method to build and install both the front-end and back-end components. Once you have Docker installed, you can just run: 
@@ -58,6 +29,15 @@ $ sudo docker run -t -p 8080:8080 ai-duet
 
 You can now play with A.I. Duet at [localhost:8080](http://localhost:8080).
 
+## DOCKER-COMPOSE
+
+```bash
+$ docker-compose build
+$ docker-compose up -d
+```
+
+You can now play with A.I. Duet at [localhost:8080](http://localhost:8080).
+
 ## MIDI SUPPORT
 
 The A.I. Duet supports MIDI keyboard input using [Web Midi API](https://webaudio.github.io/web-midi-api/) and the [WebMIDI](https://github.com/cotejp/webmidi) library. 

docker-compose.yml

@@ -0,0 +1,19 @@
+version: '2'
+
+services:
+  aiduet:
+    build: ./
+    image: aiduet
+    container_name: aiduet
+    hostname: aiduet
+    restart: "no"
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=all
+    devices:
+      - /dev/nvidia0
+      - /dev/nvidiactl
+      - /dev/nvidia-uvm
+      - /dev/nvidia-uvm-tools
+    cap_add:
+      - IPC_LOCK
+    network_mode: host

server/requirements.txt

@@ -1,5 +1,6 @@
-tensorflow==0.12.1
-magenta==0.1.8
-Flask==0.12
-gunicorn==19.6.0
-ipython==5.1.0
+tensorflow-gpu==1.14.0
+magenta==1.1.8
+numba==0.53.1
+Flask
+gunicorn
+ipython

server/server.py

@@ -22,7 +22,7 @@ import sys
 if sys.version_info.major <= 2:
     from cStringIO import StringIO
 else:
-    from io import StringIO
+    from io import StringIO, BytesIO
 import time
 import json
 
@@ -34,7 +34,8 @@ app = Flask(__name__, static_url_path='', static_folder=os.path.abspath('../stat
 def predict():
     now = time.time()
     values = json.loads(request.data)
-    midi_data = pretty_midi.PrettyMIDI(StringIO(''.join(chr(v) for v in values)))
+#    midi_data = pretty_midi.PrettyMIDI(StringIO(''.join(chr(v) for v in values)))
+    midi_data = pretty_midi.PrettyMIDI(BytesIO(b''.join((v).to_bytes(1, 'little') for v in values)))
     duration = float(request.args.get('duration'))
     ret_midi = generate_midi(midi_data, duration)
     return send_file(ret_midi, attachment_filename='return.mid',