@RunLLM, The resources can be edited on @task(). What is the difference between 'requests' and 'limits'?

In Flyte, 'requests' and 'limits' are used to manage resource allocation for tasks, similar to Kubernetes. 'Requests' specify the minimum resources required for a task to run, guiding the scheduler to place the task on a node with sufficient resources. 'Limits' define the maximum resources a task can use, acting as a hard cap to prevent overconsumption. Would you like more detail? Sources: - Customizing task resources - Flyte - Customizing Task Resources Example - Simplifying task resource assignment 👍 1 button 👎 0 button 💡 Hint: Mention @RunLLM in the thread for followups.

@RunLLM, what is 'mem' and what is 'ephemeral_storage'? thanks

In Flyte, 'mem' refers to the memory allocated to a task, specified in units like MiB or GiB. 'Ephemeral_storage' is temporary storage used by the task for operations like caching and logging, also specified in units like MiB or GiB. Would you like more detail? Sources: - flytekit/core/resources.py - flytekit/core/resources.html - flytekit.Resources 👍 1 button 👎 0 button 💡 Hint: Mention @RunLLM in the thread for followups.

@RunLLM, how can I indicate multiple image values in 'pyflyte --image', could you please give us an example?

To indicate multiple image values in

pyflyte run

using the

--image

flag, you can specify each image with a unique name. Here's an example:

pyflyte run --remote --image mindmeld="ghcr.io/flyteorg/flytecookbook:core-latest" --image borebuster="ghcr.io/flyteorg/flytekit:py3.9-latest" multi_images.py multi_images_wf

Would you like more detail? Sources: - Multiple images in a workflow - Specifying multiple images - Using different images for different tasks

@RunLLM, with your suggestion, I get the following error: Failed with Unknown Exception <class 'ValueError'> Reason: Only one default image can be specified. Received multiple Image(name='default', fqn='cgp1988/flyte_my_image_v1', tag='latest', digest=None) & Image(name='default', fqn='cgp1988/flyte_my_image', tag='latest', digest=None) for <Option image_config>

The error indicates that multiple images are being specified with the same name 'default'. Each image should have a unique name. Ensure that you are not using 'default' for more than one image. Here's an example of how to correctly specify multiple images:

pyflyte run --remote --image mindmeld="ghcr.io/flyteorg/flytecookbook:core-latest" --image borebuster="ghcr.io/flyteorg/flytekit:py3.9-latest" multi_images.py multi_images_wf

Ensure that each image has a unique identifier like 'mindmeld' and 'borebuster'. Would you like more detail? Sources: - Multiple images in a workflow - Specifying multiple images - Using different images for different tasks 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, what is a

launchplan?

A

LaunchPlan

in Flyte is a configuration that defines how to execute a workflow. It includes a set of bound workflow inputs, optional runtime overrides like notifications and schedules, and can specify default or fixed inputs. LaunchPlans are the only means to invoke workflow executions, allowing workflows to be shared, scheduled, and executed with predefined or user-specified inputs. Would you like more detail? Sources: - Launch Plans - Launch Plans Example - Launch Plans Concept 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, how can we execute a project, not as a launchplan, but as an API?

To execute a project via API in Flyte, you can use the FlyteRemote API. This allows you to programmatically fetch and execute workflows or tasks. Here's an example:

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="flyte.example.net"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

Would you like more detail? Sources: - Running tasks - Running tasks - Flyte - Remote Workflow Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, how can we execute a project, not as a launchplan, but as an API step by step, from the code to the execution required

To execute a project via API in Flyte, follow these steps: 1. Set Up FlyteRemote: Initialize the FlyteRemote object with the appropriate configuration. 2. Fetch Workflow: Retrieve the workflow you want to execute. 3. Execute Workflow: Run the workflow with the required inputs. Here's a step-by-step guide with code snippets: Step 1: Set Up FlyteRemote

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="flyte.example.net"),
    default_project="flytesnacks",
    default_domain="development",
)

Step 2: Fetch Workflow

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

Step 3: Execute Workflow

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

# Or use execution_name_prefix to avoid repeated execution names
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name_prefix="flyte", wait=True
)

Full Example

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="flyte.example.net"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

# Or use execution_name_prefix to avoid repeated execution names
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name_prefix="flyte", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()

Would you like more detail? Sources: - Running tasks - Running tasks - Flyte - Remote Workflow Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, but how can I run it, which terminal executions I need to use?

To execute a Flyte project via API, you need to follow these steps in your terminal: 1. Set Up Environment: Ensure you have the necessary tools installed (

flytectl

,

flytekit

, etc.). 2. Run the Python Script: Execute the Python script that contains the FlyteRemote API calls. Step 1: Set Up Environment Ensure you have

flytectl

and

flytekit

installed. You can install them using:

pip install flytekit
brew install flytectl

Step 2: Run the Python Script Create a Python script (e.g.,

run_workflow.py

) with the following content:

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="flyte.example.net"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

# Or use execution_name_prefix to avoid repeated execution names
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name_prefix="flyte", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()
print(f"Inputs: {input_keys}, Outputs: {output_keys}")

Run the script using Python:

python run_workflow.py

This will execute the workflow via the FlyteRemote API. Would you like more detail? Sources: - Running tasks - Running tasks - Flyte - Remote Workflow Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, thanks, and what if I execute on a remote cluster (demo cluster)?

To execute a Flyte project on a remote cluster (e.g., a demo cluster), follow these steps: 1. Set Up Environment: Ensure you have

flytectl

and

flytekit

installed. 2. Start the Demo Cluster: Use

flytectl

to start the demo cluster. 3. Configure FlyteRemote: Set up the FlyteRemote object to point to the demo cluster. 4. Run the Python Script: Execute the Python script that contains the FlyteRemote API calls. Step 1: Set Up Environment Ensure you have

flytectl

and

flytekit

installed:

pip install flytekit
brew install flytectl

Step 2: Start the Demo Cluster Start the demo cluster using `flytectl`:

flytectl demo start

Step 3: Configure FlyteRemote Create a Python script (e.g.,

run_workflow.py

) with the following content:

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.auto(config_file="~/.flyte/config-sandbox.yaml"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

# Or use execution_name_prefix to avoid repeated execution names
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name_prefix="flyte", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()
print(f"Inputs: {input_keys}, Outputs: {output_keys}")

Step 4: Run the Python Script Run the script using Python:

python run_workflow.py

This will execute the workflow on the remote demo cluster via the FlyteRemote API. Would you like more detail? Sources: - Running tasks - Running tasks - Flyte - Remote Workflow Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, and how can I call this API, at which url?

To call the Flyte API, you need to interact with the Flyte Admin service, which provides a set of endpoints for managing workflows, tasks, projects, and their associated data. The URL for the Flyte Admin API will depend on your specific Flyte deployment. Here’s a general approach: 1. Identify the Flyte Admin Endpoint: This is typically provided during the setup of your Flyte cluster. For a demo cluster, it might be something like

http://localhost:30081

. 2. Use FlyteRemote to Interact with the API: The FlyteRemote object abstracts the direct API calls, but if you need to make raw HTTP requests, you can use the Flyte Admin API endpoints. Example Using FlyteRemote

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="http://localhost:30081"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="workflows.example.wf", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"mean": 1}, execution_name="workflow-execution", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()
print(f"Inputs: {input_keys}, Outputs: {output_keys}")

Example Using Raw HTTP Request If you need to make a raw HTTP request to the Flyte Admin API, you can use the following approach:

import requests
import json

# Define the Flyte Admin API endpoint
url = "http://localhost:30081/api/v1/workflows/flytesnacks/development/workflows.example.wf"

# Define the payload for execution
payload = {
    "project": "flytesnacks",
    "domain": "development",
    "name": "workflows.example.wf",
    "inputs": {
        "mean": 1
    }
}

# Make the HTTP POST request to execute the workflow
response = requests.post(url, data=json.dumps(payload), headers={"Content-Type": "application/json"})

# Print the response
print(response.json())

URL Structure - Base URL:

http://localhost:30081

(or your Flyte Admin endpoint) - API Path:

/api/v1/workflows/{project}/{domain}/{workflow_name}

Replace

{project}

,

{domain}

, and

{workflow_name}

with your specific values. Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, the run_workflow.py that you suggest to fetch a workflow, but, which is this workflow, could you please suggest code?

Certainly! Below is a complete example that includes defining a simple workflow, registering it, and then executing it using the FlyteRemote API. Step 1: Define and Register a Workflow First, create a Python script to define a simple workflow. Save this as

example_workflow.py

.

from flytekit import task, workflow

@task
def add(a: int, b: int) -> int:
    return a + b

@workflow
def example_workflow(a: int, b: int) -> int:
    return add(a=a, b=b)

Step 2: Register the Workflow Use

flytectl

to register the workflow. Run the following commands in your terminal:

flytectl register files --project flytesnacks --domain development --archive example_workflow.py --version v1

Step 3: Execute the Workflow Using FlyteRemote Create another Python script to execute the registered workflow using FlyteRemote. Save this as

run_workflow.py

.

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="http://localhost:30081"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="example_workflow", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"a": 5, "b": 3}, execution_name="workflow-execution", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()
print(f"Inputs: {input_keys}, Outputs: {output_keys}")
print(f"Execution Outputs: {execution.outputs}")

Step 4: Run the Execution Script Run the

run_workflow.py

script using Python:

python run_workflow.py

This will execute the

example_workflow

on the Flyte cluster and print the inputs and outputs of the execution. Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example

@RunLLM, I get this error: flytectl register files --project flytesnacks --domain development --archive example_workflow.py --version v1 {"json":{},"level":"error","msg":"error while un-archiving files in tmp dir due to only .tar, .tar.gz and .tgz extension archives are supported","ts":"2024-05-15T193116+02:00"} Error: only .tar, .tar.gz and .tgz extension archives are supported {"json":{},"level":"error","msg":"only .tar, .tar.gz and .tgz extension archives are supported","ts":"2024-05-15T193116+02:00"}

The error indicates that

flytectl

expects the archive file to be in

.tar

,

.tar.gz

, or

.tgz

format. You need to package your workflow into one of these supported formats before registering it. Here’s how you can do it: 1. Package the Workflow: Use

pyflyte

to package the workflow into a

.tar.gz

file. 2. Register the Packaged Workflow: Use

flytectl

to register the packaged workflow. Step 1: Package the Workflow Create a

flyte_package

directory and move your workflow script there. Then, use

pyflyte

to package it.

mkdir flyte_package
mv example_workflow.py flyte_package/
pyflyte --pkgs flyte_package package

This will create a

flyte-package.tgz

file. Step 2: Register the Packaged Workflow Use

flytectl

to register the packaged workflow:

flytectl register files --project flytesnacks --domain development --archive flyte-package.tgz --version v1

Full Example 1. Define the Workflow: Save as

example_workflow.py

.

from flytekit import task, workflow

@task
def add(a: int, b: int) -> int:
    return a + b

@workflow
def example_workflow(a: int, b: int) -> int:
    return add(a=a, b=b)

2. Package the Workflow:

mkdir flyte_package
mv example_workflow.py flyte_package/
pyflyte --pkgs flyte_package package

3. Register the Packaged Workflow:

flytectl register files --project flytesnacks --domain development --archive flyte-package.tgz --version v1

4. Execute the Workflow Using FlyteRemote: Save as

run_workflow.py

.

from flytekit.remote import FlyteRemote
from flytekit.configuration import Config

# Initialize FlyteRemote
remote = FlyteRemote(
    config=Config.for_endpoint(endpoint="http://localhost:30081"),
    default_project="flytesnacks",
    default_domain="development",
)

# Fetch the workflow
flyte_workflow = remote.fetch_workflow(name="example_workflow", version="v1")

# Execute the workflow
execution = remote.execute(
    flyte_workflow, inputs={"a": 5, "b": 3}, execution_name="workflow-execution", wait=True
)

# Inspecting execution
input_keys = execution.inputs.keys()
output_keys = execution.outputs.keys()
print(f"Inputs: {input_keys}, Outputs: {output_keys}")
print(f"Execution Outputs: {execution.outputs}")

5. Run the Execution Script:

python run_workflow.py

Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, when I try to execute 'flytectl demo start' I get the error 'Error: Malformed version: flytectl/v0.8.20'. How can I uninstall everything and start over again?

To uninstall Flyte and start over, you need to remove the existing Flyte components and then reinstall them. Here are the steps to do this: 1. Uninstall Flyte Components: Remove Flyte components using

flytectl

. 2. Remove Flyte Configuration and Data: Clean up any remaining configuration files and data. 3. Reinstall Flyte Components: Reinstall

flytectl

and other necessary components. 4. Start the Demo Cluster: Start the demo cluster again. Step 1: Uninstall Flyte Components If you have installed Flyte using Helm, you can uninstall it using the following command:

helm uninstall flyte -n flyte

If you used

flytectl

to start the demo cluster, you can stop it using:

flytectl demo stop

Step 2: Remove Flyte Configuration and Data Remove any remaining Flyte configuration files and data. This typically includes the Flyte configuration directory and any Docker containers or volumes.

rm -rf ~/.flyte
docker system prune -a --volumes

Step 3: Reinstall Flyte Components Reinstall

flytectl

and other necessary components. Follow the installation instructions for your operating system. For macOS:

brew install flyteorg/homebrew-tap/flytectl

For Linux:

curl -sL https://ctl.flyte.org/install | sudo bash -s -- -b /usr/local/bin

For Windows (using WSL):

curl -sL https://ctl.flyte.org/install | sudo bash -s -- -b /usr/local/bin

Step 4: Start the Demo Cluster Start the demo cluster again using `flytectl`:

flytectl demo start

Full Example 1. Uninstall Flyte Components:

helm uninstall flyte -n flyte
flytectl demo stop

2. Remove Flyte Configuration and Data:

rm -rf ~/.flyte
docker system prune -a --volumes

3. Reinstall Flyte Components: For macOS:

brew install flyteorg/homebrew-tap/flytectl

For Linux:

curl -sL https://ctl.flyte.org/install | sudo bash -s -- -b /usr/local/bin

For Windows (using WSL):

curl -sL https://ctl.flyte.org/install | sudo bash -s -- -b /usr/local/bin

4. Start the Demo Cluster:

flytectl demo start

Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, I still get this error'flytectl/v0.8.20 {"json":{},"level":"error","msg":"Malformed version:'

The error you're encountering suggests that there might be an issue with the version of

flytectl

you have installed. To resolve this, you can try the following steps to completely remove

flytectl

and reinstall a specific version that is known to work. Step 1: Uninstall Flytectl First, remove the existing

flytectl

binary. For macOS (if installed via Homebrew):

brew uninstall flytectl

For Linux and Windows (if installed via curl):

sudo rm /usr/local/bin/flytectl

Step 2: Remove Flyte Configuration and Data Clean up any remaining Flyte configuration files and data.

rm -rf ~/.flyte
docker system prune -a --volumes

Step 3: Reinstall a Specific Version of Flytectl Download and install a specific version of

flytectl

that is known to work. For example, version

v0.6.14

. For macOS:

brew install flyteorg/homebrew-tap/flytectl@0.6.14

For Linux:

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Linux_x86_64.tar.gz | sudo tar -xz -C /usr/local/bin flytectl

For Windows (using WSL):

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Windows_x86_64.zip -o flytectl.zip
unzip flytectl.zip -d /usr/local/bin

Step 4: Verify the Installation Verify that the correct version of

flytectl

is installed.

flytectl version

Step 5: Start the Demo Cluster Start the demo cluster again using `flytectl`:

flytectl demo start

Full Example 1. Uninstall Flytectl: For macOS:

brew uninstall flytectl

For Linux and Windows:

sudo rm /usr/local/bin/flytectl

2. Remove Flyte Configuration and Data:

rm -rf ~/.flyte
docker system prune -a --volumes

3. Reinstall a Specific Version of Flytectl: For macOS:

brew install flyteorg/homebrew-tap/flytectl@0.6.14

For Linux:

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Linux_x86_64.tar.gz | sudo tar -xz -C /usr/local/bin flytectl

For Windows (using WSL):

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Windows_x86_64.zip -o flytectl.zip
unzip flytectl.zip -d /usr/local/bin

4. Verify the Installation:

flytectl version

5. Start the Demo Cluster:

flytectl demo start

Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@RunLLM, I have installed version v0.6.14, but I get this error: INFO[0000] [0] Couldn't find a config file []. Relying on env vars and pflags. 🧑‍🏭 Bootstrapping a brand new flyte cluster... 🔨 🔧 Error: Malformed version: flytectl/v0.8.20 {"json":{},"level":"error","msg":"Malformed version: flytectl/v0.8.20",

The error message indicates that there might be a conflict or residual configuration from a previous installation. To resolve this, you can try the following steps to ensure a clean environment before reinstalling and starting the Flyte demo cluster. Step 1: Uninstall Flytectl and Clean Up 1. Uninstall Flytectl: For macOS (if installed via Homebrew):

brew uninstall flytectl

For Linux and Windows (if installed via curl):

sudo rm /usr/local/bin/flytectl

2. Remove Flyte Configuration and Data:

rm -rf ~/.flyte
docker system prune -a --volumes

3. Clean Up Docker Containers and Images:

docker stop $(docker ps -a -q)
docker rm $(docker ps -a -q)
docker rmi $(docker images -q)

Step 2: Reinstall Flytectl Reinstall a specific version of

flytectl

that is known to work. For example, version

v0.6.14

. For macOS:

brew install flyteorg/homebrew-tap/flytectl@0.6.14

For Linux:

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Linux_x86_64.tar.gz | sudo tar -xz -C /usr/local/bin flytectl

For Windows (using WSL):

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Windows_x86_64.zip -o flytectl.zip
unzip flytectl.zip -d /usr/local/bin

Step 3: Verify the Installation Verify that the correct version of

flytectl

is installed.

flytectl version

Step 4: Start the Demo Cluster Start the demo cluster again using `flytectl`:

flytectl demo start

Full Example 1. Uninstall Flytectl: For macOS:

brew uninstall flytectl

For Linux and Windows:

sudo rm /usr/local/bin/flytectl

2. Remove Flyte Configuration and Data:

rm -rf ~/.flyte
docker system prune -a --volumes

3. Clean Up Docker Containers and Images:

docker stop $(docker ps -a -q)
docker rm $(docker ps -a -q)
docker rmi $(docker images -q)

4. Reinstall a Specific Version of Flytectl: For macOS:

brew install flyteorg/homebrew-tap/flytectl@0.6.14

For Linux:

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Linux_x86_64.tar.gz | sudo tar -xz -C /usr/local/bin flytectl

For Windows (using WSL):

curl -sL https://github.com/flyteorg/flytectl/releases/download/v0.6.14/flytectl_Windows_x86_64.zip -o flytectl.zip
unzip flytectl.zip -d /usr/local/bin

5. Verify the Installation:

flytectl version

6. Start the Demo Cluster:

flytectl demo start

Would you like more detail? Sources: - FlyteRemote API - Flyte Admin API - Flyte Admin API Example 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.