A docker compose file is used to run a signalbot, and the signal rest api.
The signalbot docker will automatically get this repo and execute run.py.
A second signalbot docker is made that checks out the devel branch instead of main.
Both containers monitor the github repo and will automatic download updated code.
Execute the docker compose file. In the signalbot docker make sure you make a secrets.txt file that has these vairables:
export SIGNAL_API_URL=signal-cli:8181 # URL for the signal-cli API
export BOT_NUMBER="+1555555555" # The registered Signal number for your bot
export CONTACT_NUMERS="+1555555555" # true/false, a single contact, a ; seperated list of contacts
export GROUP_NAMES="MYGROUP" # true/false, a single group, a ; seperated list of groups
export IGNORE_GROUPS="TurboBot Devel" #optional
export INSTA_USERNAME="myuser"
export INSTA_PASSWORD="mypassword"
export OPENAI_API_KEY="keygoeshere"
Update the docker-compose file to point the signal-cli bot(s) to your repo, or use this one. Default file makes one for main branch and one for devel branch. The run.sh script will just fail back to bash if you dont supply a secrets.sh file in the same folder as the repo.
When you first run this you need to boot signal-cli in normal mode in order to link it to your account. You do that by having it generate a qr code that you scan with your phone. See the signalbot documentation. tldr: http://localhost:8181/v1/qrcodelink?device_name=local
Manually running signal-cli from command line. Be sure to stop the instance first:
docker run --env "MODE=json-rpc" --env "PORT=8181" --env "PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin" --env "GIN_MODE=release" --env "BUILD_VERSION=0.90" --env "SIGNAL_CLI_CONFIG_DIR=/home/.local/share/signal-cli" --env "SIGNAL_CLI_UID=1000" --env "SIGNAL_CLI_GID=1000" --entrypoint "/entrypoint.sh" --volume "/share/CACHEDEV1_DATA/Container/container-station-data/lib/docker/volumes/app-1_signal-cli-data/_data:/home/.local/share/signal-cli" bbernhard/signal-cli-rest-api:latest
This was generated with:
container_id="signal-cli"
docker inspect $container_id | jq -r '
.[] |
"docker run " +
(if .Config.Env then (.Config.Env | map("--env \"" + . + "\"") | join(" ")) else "" end) + " " +
(if .Config.Entrypoint then "--entrypoint \"" + (.Config.Entrypoint | join(" ")) + "\" " else "" end) +
(if .Mounts then (.Mounts | map("--volume \"" + .Source + ":" + .Destination + "\"") | join(" ")) else "" end) + " " +
(if .Config.Cmd then (.Config.Cmd | join(" ")) else "" end) +
" " + .Config.Image
'
You can develop in windows, linux, wsl, and mac all relatively easily.
For Windows I'd suggest using miniconda.
Running the tests on your own windows or linux box is pretty easy.
If on windows just install miniconda and then run pip3 install -r requirements.txt.
Then you can run all the tests with python3 -m unittest discover -s tests -p "test_*.py"
You can also do it in WSL 1 or 2.
Some handlers might also require apt-get packages. i.e. ffmpeg. You can get ffmpeg in miniconda (i.e. conda install ffmpeg) or wsl (via apt-get or whatever).