Getting Started
Installation
pip
uv
Setup
There's a small amount of setup required before we get started with Blackfish. Fortunately, it's mostly automated.
SSH
Using Blackfish from your laptop requires a seamless (i.e., password-less) method of communicating with remote clusters. On many systems, this is simple to setup with the ssh-keygen
and ssh-copy-id
utilitites. First, make sure that you are connected to your institution's network (or VPN), then type the following at the command-line:
ssh-keygen -t rsa # generates ~/.ssh/id_rsa.pub and ~/.ssh/id_rsa
ssh-copy-id <user>@<host> # answer yes to transfer the public key
These commands create a secure public-private key pair and send the public key to the HPC server you need access to. You now have password-less access to your HPC server!
Warning
Blackfish depends on seamless interaction with your university's HPC cluster. Before proceeding, make sure that you have enabled password-less login and are connected to your institutions network or VPN, if required.
Initialization
To initialize Blackfish, just type
and answer the prompts to create a new default profile.Note
If your default profile connects to an HPC cluster, then Blackfish will attempt to set up the remote host at this point. Profile creation will fail if you're unable to connect to the HPC server and you'll need to re-run the blackfish init
command or create a profile with blackfish profile create
(see below).
Models and Images
Blackfish works best with locally available model files and container images. Having these files available locally allows Blackfish to avoid slow downloads during deployment. See the section on Obtaining Service Images and Models for more information, or talk to your institution's HPC cluster admins.
Configuration
The application and command-line interface (CLI) pull their settings from environment variables and/or (for the application) arguments provided at start-up. The most important environment variables are:
BLACKFISH_HOST='localhost' # host for local instance of the Blackfish app
BLACKFISH_PORT=8000 # port for local instance of the Blackfish app
BLACKFISH_HOME_DIR='~/.blackfish' # location to store application data
BLACKFISH_DEV_MODE=1 # run the application with development settings
BLACKFISH_TOKEN='sealsaretasty' # a user-defined secret auth token
Running the application in development mode is recommended for development only on a shared system as it does not use authentication.
Profiles
The blackfish profile
command provides methods for managing Blackfish profiles. Profiles
are useful if you have access to multiple HPC resources or have multiple accounts on an HPC server.
Each profile consists of some combination of the following attributes, depending on the profile
type.
Tip
Blackfish profiles are stored in $BLACKFISH_HOME/profiles.cfg
. On Linux, this is
$HOME/.blackfish/profiles.cfg
by default. You can modify this file directly, if needed, but you'll
need to need setup any required remote resources by hand.
Schemas
Each profile specifies a number of attributes that allow Blackfish to find resources (e.g., model
files) and deploy services accordingly. The exact attributes depend on the profile schema. There are currently two profile schemas: LocalProfile
("local") and SlurmProfile
("slurm"). All profiles require the following attributes:
name
: the unique profile name. The "default" profile is used by Blackfish when a profile isn't explicitly provided.schema
: one of "slurm" or "local". The profile schema determines how services associated with this profile are deployed by Blackfish. Use "slurm" if this profile will run jobs on HPC and "local" to run jobs on your laptop (or wherever Blackfish is installed).
The additional attribute requirements for specific types are listed below.
Slurm
A Slurm profile specifies how to schedule services on a (possibly) remote server (e.g., HPC cluster) running Slurm from a local machine.
host
: a HPC server to run services on, e.g.<cluster>@<university>.edu
orlocalhost
(if running Blackfish on an HPC cluster).user
: a user name on the HPC server.home
: a location on the HPC server to store application data, e.g.,/home/<user>/.blackfish
cache
: a location on the HPC server to store additional (typically shared) model images and files. Blackfish does not attempt to create this directory for you, but it does require that it can be found.
Local
A local profile specifies how to run services on a local machine, i.e., your laptop or desktop, without a job scheduler. This is useful for development and for running models that do not require large amounts of resource, especially if the model is able to use the GPU on your laptop.
home
: a location on the local machine to store application data, e.g.,/home/<user>/.blackfish
cache
: a location on the local machine to store additional (typically shared) model images and files. Blackfish does not attempt to create this directory for you, but it does require that it can be found.
Commands
ls - List profiles
To view all profiles, type
add - Create a profile
Creating a new profile is as simple as typing
and following the prompts (see attribute descriptions above). Note that profile names are unique.
show - View a profile
You can view a list of all profiles with the blackfish profile ls
command. If you want to view a
specific profile, use the blackfish profile show
command instead, e.g.
Leaving off the --name
option above will display the default profile, which is used by most
commands if no profile is explicitly provided.
update - Modify a profile
To modify a profile, use the blackfish profile update
command, e.g.
--name
is specified. Note that you cannot change
the name or type attributes of a profile.
rm - Delete a profile
To delete a profile, type blackfish profile rm --name <profile>
. By default, the command
requires you to confirm before deleting.
Usage
Once you've initialized Blackfish and created a profile, you're ready to go. Their are two ways ways to interact with Blackfish: in a browser, via the user interface (UI), or at the command-line using the Blackfish CLI. In either case, the entrypoint is to type
in the command-line. If everything worked, you should see a message stating the application startup is complete.At this point, we need to decide how we want to interact with Blackfish. The UI is available in your browser by heading over to http://localhost:8000
. It's a relatively straight-forward interface, and we have detailed usage examples on the user interface page, so let's instead take a look at the CLI.
Open a new terminal tab or window. First, let's see what type of services are available.
blackfish run --help
Usage: blackfish run [OPTIONS] COMMAND [ARGS]...
Run an inference service.
The format of options approximately follows that of Slurm's `sbatch` command.
╭─ Options ─────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --time TEXT The duration to run the service for, e.g., 1:00 (one hour). │
│ --ntasks-per-node INTEGER The number of tasks per compute node. │
│ --mem INTEGER The memory required per compute node in GB, e.g., 16 (G). │
│ --gres INTEGER The number of GPU devices required per compute node, e.g., 1. │
│ --partition TEXT The HPC partition to run the service on. │
│ --constraint TEXT Required compute node features, e.g., 'gpu80'. │
│ --profile -p TEXT The Blackfish profile to use. │
│ --help Show this message and exit. │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ────────────────────────────────────────────────────────────────────────────────────────────────╮
│ speech-recognition Start a speech recognition service hosting MODEL with access to INPUT_DIR on the │
│ service host. MODEL is specified as a repo ID, e.g., openai/whisper-tiny. │
│ text-generation Start a text generation service hosting MODEL, where MODEL is specified as a repo ID, │
│ e.g., openai/whisper-tiny. │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────╯
text-generation
, which is a service that generates text given an input prompt. There are a variety of models that we might use to perform this task, so let's check out what's available on our setup.
Models
blackfish model ls
REPO REVISION PROFILE IMAGE
openai/whisper-tiny 169d4a4341b33bc18d8881c4b69c2e104e1cc0af default speech-recognition
openai/whisper-tiny be0ba7c2f24f0127b27863a23a08002af4c2c279 default speech-recognition
openai/whisper-small 973afd24965f72e36ca33b3055d56a652f456b4d default speech-recognition
TinyLlama/TinyLlama-1.1B-Chat-v1.0 ac2ae5fab2ce3f9f40dc79b5ca9f637430d24971 default text-generation
meta-llama/Meta-Llama-3-70B b4d08b7db49d488da3ac49adf25a6b9ac01ae338 macbook text-generation
openai/whisper-tiny 169d4a4341b33bc18d8881c4b69c2e104e1cc0af macbook speech-recognition
TinyLlama/TinyLlama-1.1B-Chat-v1.0 4f42c91d806a19ae1a46af6c3fb5f4990d884cd6 macbook text-generation
TinyLlama/TinyLlama-1.1B-Chat-v1.0
is listed twice. The first listing refers to a specific version of this model—
ac2ae5fab2ce3f9f40dc79b5ca9f637430d24971
—that is available to the default
profile; the second listing refers to a different version ("revision") of the same model—4f42c91d806a19ae1a46af6c3fb5f4990d884cd6
—that is available to the macbook
profile. For reproducibility, it's important to keep track of the exact revision used.
Let's go ahead and try to run one of these models.
Services
A service is a containerized API that is called to perform a specific task, such a text generation, using a model specified by the user when the API is created. Services perform inference in an "online" fashion, meaning that, in general, they process requests one input at a time. Users can create as many services as they like (and have resources to support) and interact with them simultaneously. Services are completely managed by the user: as the creator of a service, you are the only person that can stop or restart the service, and you control access to the service via an authentication token.
Commands
run
- Start a service
Looking back at the help message for blackfish run
, we see that there are a few items that we should provide. First, we need to select the type of service to run. We've already decide to run
text-generation
, so we're good there. Next, there are a number of job options that we can provide. With the exception of profile
, job options are based on the Slurm sbatch
command and tell Blackfish the resources required to run a service. Finally, there are a number of "container options" available. To get a list of these, type blackfish run text-generation --help
:
blackfish run text-generation --help
Usage: blackfish run text-generation [OPTIONS] MODEL
Start a text generation service hosting MODEL, where MODEL is specified as a repo ID, e.g.,
openai/whisper-tiny.
See https://huggingface.co/docs/text-generation-inference/en/basic_tutorials/launcher for
additional option details.
╭─ Options ────────────────────────────────────────────────────────────────────────────────────────╮
│ --name -n TEXT Assign a name to the service. A random name is assigned │
│ by default. │
│ --revision -r TEXT Use a specific model revision. The most recent locally │
│ available (i.e., downloaded) revision is used by default. │
│ --disable-custom-kernels Disable custom CUDA kernels. Custom CUDA kernels are not │
│ guaranteed to run on all devices, but will run faster if │
│ they do. │
│ --sharded TEXT Shard the model across multiple GPUs. The API uses all │
│ available GPUs by default. Setting to 'true' with a │
│ single GPU results in an error. │
│ --max-input-length INTEGER The maximum allowed input length (in tokens). │
│ --max-total-tokens INTEGER The maximum allowed total length of input and output (in │
│ tokens). │
│ --dry-run Print the job script but do not run it. │
│ --help Show this message and exit. │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
revision
, which specifies the exact version of the model we want to run. By default, Blackfish selects the most recent locally available version. This container option (as well as --name
) is available for all tasks: the remaining options are task-specific.
We'll choose TinyLlama/TinyLlama-1.1B-Chat-v1.0
for the required MODEL
argument, which we saw earlier is available to the default
and macbook
profiles. This is a relatively small model, but we still want to ask for a GPU to speed things up. Putting it altogether, here's a command to start our service:
blackfish run --profile della --gres 1 --mem 16 --ntasks-per-node 4 --time 00:30:00 --constraint 'amd&gpu40' text-generation TinyLlama/TinyLlama-1.1B-Chat-v1.0 --api-key sealsaretasty
✔ Found 49 models.
✔ Found 1 snapshots.
⚠ No revision provided. Using latest available commit: fe8a4ea1ffedaf415f4da2f062534de366a451e6.
✔ Found model TinyLlama/TinyLlama-1.1B-Chat-v1.0!
✔ Started service: fed36739-70b4-4dc4-8017-a4277563aef9
della
profile. Next, it found a list of available revisions of the model and selected the
most recently published version because no revision was specified. Finally, it sent a request to deploy the model. Helpfully, the CLI returned an ID associated with the new service fed36739-70b4-4dc4-8017-a4277563aef9
, which we can use get information about our service via the blackfish ls
command.
Note
If no --revision
is provided, Blackfish automatically suggests the most recently available downloaded version of the requested model. This reduces the
time-to-first-inference, but may not be desirable for your use case. Download the model before starting your service if you need the most recent version available on Hugging Face.
Tip
Add the --dry-run
flag to preview the start-up script that Blackfish will submit.
ls
- List services
To view a list of your Blackfish services, type
blackfish ls # --filter id=<service_id>,status=<status>
SERVICE ID IMAGE MODEL CREATED UPDATED STATUS PORT NAME PROFILE
97ffde37-7e02 speech_recognition openai/whisper-large-v3 7 hours ago 1 min ago HEALTHY 8082 blackfish-11846 default
fed36739-70b4 text_generation TinyLlama/TinyLlama-1.1B-Chat-v1.0 7 sec ago 5 sec ago PENDING None blackfish-89359 della
default
profile happens to be set up to connect to a remote HPC cluster, so the service is run as a Slurm job. It
may take a few minutes for our Slurm job to start, and it will require additional time for the service to be ready after that. Until then, our service's status will be either SUBMITTED
, PENDING
or STARTING
. Now would be a good time to brew a hot beverage ☕️.
Tip
If you ever want more detailed information about a service, you can get it with the
blackfish details <service_id>
command. Again, --help
is your friend if you want more
information.
Now that we're refreshed, let's see how our service is doing. Re-run the command above. If things went smoothly, then we should see that the service's status has changed to HEALTHY
(if your service is still STARTING
, give it another minute and try again).
blackfish ls
SERVICE ID IMAGE MODEL CREATED UPDATED STATUS PORT NAME PROFILE
97ffde37-7e02 speech_recognition openai/whisper-large-v3 7 hours ago 19 sec ago HEALTHY 8082 blackfish-11846 default
fed36739-70b4 text_generation TinyLlama/TinyLlama-1.1B-Chat-v1.0 2 min ago 19 sec ago HEALTHY 8080 blackfish-12328 della
At this point, we can start interacting with the service. Let's say "Hello", shall we?
The details of calling a service depend on the service you are trying to connect to. For the text-generation
service, the primary endpoint is accessed like so:
curl http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sealsaretasty" \
-d '{
"messages": [
{"role": "system", "content": "You are an expert marine biologist."},
{"role": "user", "content": "Why are orcas so awesome?"}
],
"max_completion_tokens": 100,
"temperature": 0.1,
"stream": false
}' | jq
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 1192 100 911 100 281 1652 509 --:--:-- --:--:-- --:--:-- 2159
{
"id": "chatcmpl-b6452981728f4f3cb563960d6639f8a4",
"object": "chat.completion",
"created": 1747826716,
"model": "/data/snapshots/fe8a4ea1ffedaf415f4da2f062534de366a451e6",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"reasoning_content": null,
"content": "Orcas (also known as killer whales) are incredibly intelligent and social animals that are known for their incredible abilities. Here are some reasons why orcas are so awesome:\n\n1. Intelligence: Orcas are highly intelligent and have been observed using tools, communicating with each other, and even learning from their trainers.\n\n2. Social behavior: Orcas are highly social animals and form complex social structures, including family groups, pods,",
"tool_calls": []
},
"logprobs": null,
"finish_reason": "length",
"stop_reason": null
}
],
"usage": {
"prompt_tokens": 40,
"total_tokens": 140,
"completion_tokens": 100,
"prompt_tokens_details": null
},
"prompt_logprobs": null
}
Most services provide a single endpoint that performs a task or pipeline. For text generation, there two main endpoints, /v1/completions
and /v1/chat/completions
. Running services are yours to use as you see fit.
stop
- Stop a service
When we are done with our service, we should shut it off and return its resources to the cluster. To do so, simply type
blackfish stop fed36739-70b4-4dc4-8017-a4277563aef9
✔ Stopped service fed36739-70b4-4dc4-8017-a4277563aef9
blackfish ls
.
rm
- Delete a service
Services aren't automatically deleted from your list, so it's a good idea to remove them when you're done if you don't need them for record keeping:
Speech Recognition
blackfish run --profile default speech-recognition openai/whisper-large-v3
✔ Found 4 models.
✔ Found 1 snapshots.
⚠ No revision provided. Using latest available commit: 06f233fe06e710322aca913c1bc4249a0d71fce1.
✔ Found model openai/whisper-large-v3!
✔ Started service: 70e59004-84d4-4f7c-bf78-95ef96054289
curl http://localhost:8080/transcribe \
-H "Content-Type: application/json" \
-d '{
"audio_path": "/data/audio/NY045-0.mp3",
"response_format": "text"
}' | jq
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 465 100 375 100 90 10 2 0:00:45 0:00:35 0:00:10 91
{
"audio_path": "/data/audio/NY045-0.mp3",
"text": " Oh, going to Cuba. I went to Cuba on Prohibition time, too. And I brought a lot of fancy bottles, a little, like one drink in for souvenirs for all my friends. Well, Atlantic City, the ship was stopped. It was all in the newspapers about it, too. The crew had ripped the walls and put all",
"segments": null,
"task": "transcribe"
}
-
The list of models you see depends on your environment. If you do not have access to a shared HPC cache, your list of models is likely empty. Not to worry—we will see how to add models later on. ↩