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# fly.toml app configuration file generated for medical-transcription-cpu on 2024-01-22T15:15:29-06:00
#
# See https://fly.io/docs/reference/configuration/ for information about how to use this file.
#
app = "medical-transcription-cpu"
primary_region = "ord"
kill_signal = "SIGTERM"
# TODO: Enable the following line and install the necessary CUDA packages in the Dockerfile for GPU usage.
# The volumes will need to be recreated as well to match the GPU kind.
# See https://fly.io/docs/gpus/gpu-quickstart/
# and https://fly.io/docs/gpus/getting-started-gpus/
# vm.size = "a100-40gb"
[build]
[deploy]
release_command = "/app/bin/migrate"
[[mounts]]
source = "data"
destination = "/data"
initial_size = "40gb"
[env]
ELIXIR_ERL_OPTIONS = "-proto_dist inet6_tcp +sssdio 128"
AUDIO_TAGGER_CACHE_DIR="/data/cache/audio_tagger"
BUMBLEBEE_CACHE_DIR="/data/cache/bumblebee"
XLA_CACHE_DIR="/data/cache/xla"
# XLA_TARGET="cuda120"
PHX_HOST = "medical-transcription-cpu.fly.dev"
PORT = "8080"
RELEASE_COOKIE = "0gfxcPtwryKxI2O1N0eFAg9p4MJGC-oUGShgj_wgvNEGiba5EDEJFA=="
[http_service]
internal_port = 8080
force_https = true
auto_stop_machines = false
auto_start_machines = false
min_machines_running = 0
processes = ["app"]
[http_service.concurrency]
type = "connections"
hard_limit = 1000
soft_limit = 1000
[[vm]]
cpu_kind = "shared"
cpus = 1
memory_mb = 4096
# To generate the vector embeddings for the ICD-9 codelist, we need more RAM available.
# fly scale vm shared-cpu-8x --memory 16384
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