refactor code using black formatter and add dockerhub push cmd, and update base image to version containing cudnn8

Dockerfile

@@ -1,27 +1,26 @@
 # Use an NVIDIA CUDA base image with Python 3
-FROM nvidia/cuda:11.6.2-base-ubuntu20.04 
+FROM nvidia/cuda:11.6.2-cudnn8-runtime-ubuntu20.04
 
 # Set the working directory in the container
 WORKDIR /usr/src/app
 
-# Copy the requirements.txt file first to leverage Docker cache
-COPY requirements.txt ./
-
 # Avoid interactive prompts from apt-get
 ENV DEBIAN_FRONTEND=noninteractive
 
-# Install any needed packages specified in requirements.txt
-RUN apt-get update && apt-get install -y python3-pip libsndfile1 ffmpeg && \
-    pip3 install --no-cache-dir -r requirements.txt
+# Install any needed packages
+RUN apt-get update && apt-get install -y python3-pip libsndfile1 ffmpeg wget dpkg
 
-# Reset the frontend (not necessary in newer Docker versions)
-ENV DEBIAN_FRONTEND=newt
+# Copy the requirements.txt file
+COPY requirements.txt ./
+
+# Install any needed packages specified in requirements.txt
+RUN pip3 install --no-cache-dir -r requirements.txt
 
 # Copy the rest of your application's code
 COPY . .
 
-# Make port 8765 available to the world outside this container
-EXPOSE 8765
+# Make port 80 available to the world outside this container
+EXPOSE 80
 
 # Define environment variable
 ENV NAME VoiceStreamAI
@@ -30,5 +29,4 @@ ENV NAME VoiceStreamAI
 ENTRYPOINT ["python3", "-m", "src.main"]
 
 # Provide a default command (can be overridden at runtime)
-CMD ["--host", "0.0.0.0", "--port", "8765"]
-
+CMD ["--host", "0.0.0.0", "--port", "80", "--static-path", "./src/static"]

LICENSE.txt

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2024 Alessandro Saccoia
+Copyright (c) 2024
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -13,18 +13,15 @@ VoiceStreamAI is a Python 3 -based server and JavaScript client solution that en
 - Customizable audio chunk processing strategies.
 - Support for multilingual transcription.
 
-## Demo Video
+## Demo
 
+[View Demo Video](https://raw.githubusercontent.com/TyreseDev/VoiceStreamAI/main/img/voicestreamai_test.mp4)
 
-https://github.com/alesaccoia/VoiceStreamAI/assets/1385023/9b5f2602-fe0b-4c9d-af9e-4662e42e23df
-
-## Demo Client
-
-![Client Demo](/img/client.png "Client Demo")
+![Demo Image](https://raw.githubusercontent.com/TyreseDev/VoiceStreamAI/main/img/client.png)
 
 ## Running with Docker
 
-This will not guide you in detail on how to use CUDA in docker, see for example [here](https://medium.com/@kevinsjy997/configure-docker-to-use-local-gpu-for-training-ml-models-70980168ec9b). 
+This will not guide you in detail on how to use CUDA in docker, see for example [here](https://medium.com/@kevinsjy997/configure-docker-to-use-local-gpu-for-training-ml-models-70980168ec9b).
 
 Still, these are the commands for Linux:
 
@@ -52,13 +49,13 @@ After getting your VAD token (see next sections) run:
 
 sudo docker volume create huggingface_models
 
-sudo docker run --gpus all -p 8765:8765 -v huggingface_models:/root/.cache/huggingface  -e PYANNOTE_AUTH_TOKEN='VAD_TOKEN_HERE' voicestreamai
+sudo docker run --gpus all -p 80:80 -v huggingface_models:/root/.cache/huggingface  -e PYANNOTE_AUTH_TOKEN='VAD_TOKEN_HERE' voicestreamai
 ```
 
 The "volume" stuff will allow you not to re-download the huggingface models each time you re-run the container. If you don't need this, just use:
 
 ```bash
-sudo docker run --gpus all -p 8765:8765 -e PYANNOTE_AUTH_TOKEN='VAD_TOKEN_HERE' voicestreamai
+sudo docker run --gpus all -p 80:80 -e PYANNOTE_AUTH_TOKEN='VAD_TOKEN_HERE' voicestreamai
 ```
 
 ## Normal, Manual Installation
@@ -92,7 +89,7 @@ The VoiceStreamAI server can be customized through command line arguments, allow
 - `--asr-type`: Specifies the type of Automatic Speech Recognition (ASR) pipeline to use (default: `faster_whisper`).
 - `--asr-args`: A JSON string containing additional arguments for the ASR pipeline (one can for example change `model_name` for whisper)
 - `--host`: Sets the host address for the WebSocket server (default: `127.0.0.1`).
-- `--port`: Sets the port on which the server listens (default: `8765`).
+- `--port`: Sets the port on which the server listens (default: `80`).
 
 For running the server with the standard configuration:
 
@@ -103,7 +100,7 @@ For running the server with the standard configuration:
 python3 -m src.main --vad-args '{"auth_token": "vad token here"}'
 ```
 
-You can see all the command line options with the command: 
+You can see all the command line options with the command:
 
 ```bash
 python3 -m src.main --help
@@ -112,13 +109,12 @@ python3 -m src.main --help
 ## Client Usage
 
 1. Open the `client/VoiceStreamAI_Client.html` file in a web browser.
-2. Enter the WebSocket address (default is `ws://localhost:8765`).
+2. Enter the WebSocket address (default is `ws://localhost/ws`).
 3. Configure the audio chunk length and offset. See below.
 4. Select the language for transcription.
 5. Click 'Connect' to establish a WebSocket connection.
 6. Use 'Start Streaming' and 'Stop Streaming' to control audio capture.
 
-
 ## Technology Overview
 
 - **Python Server**: Manages WebSocket connections, processes audio streams, and handles voice activity detection and transcription.
@@ -207,10 +203,8 @@ Please make sure that the end variables are in place for example for the VAD aut
 
 ### Dependence on Audio Files
 
-Currently, VoiceStreamAI processes audio by saving chunks to files and then running these files through the models. 
+Currently, VoiceStreamAI processes audio by saving chunks to files and then running these files through the models.
 
 ## Contributors
 
-- Alessandro Saccoia - [[email protected]](mailto:[email protected])
-
 This project is open for contributions. Feel free to fork the repository and submit pull requests.