17 releases (10 breaking)
|new 0.21.0||Mar 14, 2023|
|0.19.0||Aug 9, 2022|
|0.17.0||Mar 20, 2022|
|0.13.0||Sep 9, 2021|
|0.3.0||May 9, 2020|
#18 in Audio
123 downloads per month
I don't know how, But They Found Me (BTFM).
btfm is a Discord bot that listens on a voice channel for key phrases, and plays audio clips into the channel in response.
You'll need to register a bot with Discord. Go to the Developer application page and create an application.
BTFM uses a PostgreSQL database to store audio clip metadata. Install PostgreSQL and create a database. For example:
sudo apt install postgresql postgresql-contrib sudo systemctl restart postgresql.service sudo -u postgres createuser btfm sudo -u postgres createdb btfm sudo -u postgres psql -c "ALTER USER btfm PASSWORD 'password';" sudo -u postgres psql -c "ALTER DATABASE btfm OWNER to btfm;"
btfm-server service will create the database schema when it connects. Any migrations required will also
be run automatically on updates.
Create a user for the bot:
$ sudo useradd --home-dir=/var/lib/btfm --create-home btfm
An example configuration file:
# The directory where audio clips and other data is stored. # The server will create two directories in the data directory: "clips" contains # the uploaded audio clips and "tts_cache" stores any text-to-speech audio it creates. # The "tts_cache" directory can be safely removed if it grows too large. data_directory = "/var/lib/btfm/" # The database created in the prior step; substitute the password as necessary. database_url = 'postgres://btfm:password@localhost/btfm' # This is the Discord API token you got during the Discord registration step. discord_token = 'your discord token here' # The channel to join when someone enters; this is available by enabling "Developer Mode" # in the Discord client in the advanced settings, then right-clicking a voice channel and # copying the ID. channel_id = 0 # The server ID to join; this is available by enabling "Developer Mode" in the Discord # client in the advanced settings, then right-clicking a server and copying the ID. guild_id = 0 # The optional channel to log events to; when a clip is matched the bot will post a message # in this text channel. log_channel_id = 0 # Adjust the frequency of playing clips; the odds of a clip being played is # 1 - e^(-x/rate_adjuster) where "x" is the number of seconds since the last clip was played. rate_adjuster = 100 # The bot will play a random clip at the interval provided (in seconds) random_clip_interval = 900 # If set, this is the URL for a mimic3 HTTP API used to convert text-to-speech so the bot can # talk back. mimic_endpoint = "http://localhost:8888/api/" [whisper] # The path to the OpenAI Whisper model to use for transcription. model = "/var/lib/btfm/whisper/base.en.pt" [http_api] # Where the HTTP API used for management listens. url = "127.0.0.1:8080" # The username required to authenticate with the management API user = "admin" # The password required to authenticate with the management API password = "admin" # To enable TLS for the HTTP API, set the following two keys. If # TLS should not be used, ensure these keys don't exist. # # If set, tls_key must also be set and the HTTP API will use TLS tls_certificate = "/var/lib/btfm/fullchain.pem" # If set, tls_certificate must also be set and the HTTP API will use TLS tls_key = "/var/lib/btfm/privkey.pem"
You can place this, for example, in
The Whisper Python API is used to perform transcription, so you need to set up a Python environment and install Whisper. The recommended approach is as follows (assuming you're using Fedora Linux):
sudo dnf install python3-pip sudo -u btfm bash -c \ 'python3 -m venv --upgrade-deps $HOME/.whisper && \ $HOME/.whisper/bin/pip install openai-whisper'
Next, test the installation and download the model to use (replace the model as necessary and be sure to adjust the configured model in btfm.toml to match):
sudo -u btfm bash -c '$HOME/.whisper/bin/whisper --model base.en --model_dir $HOME/whisper/ <an audio file>
An example systemd unit to run BTFM:
[Unit] Description=BTFM Discord bot After=network.target [Service] Type=simple User=btfm Group=btfm Environment="PATH=/var/lib/btfm/.whisper/bin:/usr/bin:/usr/local/bin/" Environment="BTFM_CONFIG=/var/lib/btfm/btfm.toml" Environment="RUST_LOG=warn,btfm=info" ExecStart=/usr/local/bin/btfm-server run Restart=always RestartSec=60 [Install] WantedBy=multi-user.target
If building from source, install make, autotools, libopus headers, gstreamer headers, libsodium headers, and the openssl headers.
Add clips and phrases with the
btfm clip sub-commands:
btfm clip add --phrase "they found me" "I don't know how, but they found me..." run-for-it-marty.mp3
btfm clip --help for available sub-commands and options.
Start the bot with
btfm-server run. See the systemd unit above for details.
btfm-server run --help for command line arguments and documentation. To
obtain the guild and channel ID, go to your Discord User Settings ->
Appearance, and enable Developer Mode. You can then right-click on the server
for and select "Copy ID" for the guild ID, and then right-click the voice
channel you want the bot to watch and "Copy ID" that as well.
If you are so inclined, there is a Dockerfile and some helper scripts in the
that you may find to be handy for development. The scripts assume you have
podman installed. You can use
build.sh to build a development container,
and you can use
cargo.sh to run Rust's cargo tool inside
the container. You can probably guess what
test.sh does, if you are somebody's kid and are