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API Wrapper

This document outlines the core functionalities provided by the RunPod API, including how to interact with Endpoints, manage Templates, and list available GPUs. These operations let you dynamically manage computational resources within the RunPod environment.

Get Endpoints​

To retrieve a comprehensive list of all available endpoint configurations within RunPod, you can use the get_endpoints() function. This function returns a list of endpoint configurations, allowing you to understand what's available for use in your projects.


import runpod
import os
runpod.api_key = os.getenv("RUNPOD_API_KEY")
# Fetching all available endpoints
endpoints = runpod.get_endpoints()
# Displaying the list of endpoints
print(endpoints)

Create Template​

Templates in RunPod serve as predefined configurations for setting up environments efficiently. The create_template() function facilitates the creation of new templates by specifying a name and a Docker image.


import runpod
import os
runpod.api_key = os.getenv("RUNPOD_API_KEY")
try:
# Creating a new template with a specified name and Docker image
new_template = runpod.create_template(name="test", image_name="runpod/base:0.1.0")
# Output the created template details
print(new_template)
except runpod.error.QueryError as err:
# Handling potential errors during template creation
print(err)
print(err.query)

Create Endpoint​

Creating a new endpoint with the create_endpoint() function. This function requires you to specify a name and a template_id. Additional configurations such as GPUs, number of Workers, and more can also be specified depending your requirements.


import runpod
import os
runpod.api_key = os.getenv("RUNPOD_API_KEY")
try:
# Creating a template to use with the new endpoint
new_template = runpod.create_template(
name="test", image_name="runpod/base:0.4.4", is_serverless=True
)
# Output the created template details
print(new_template)
# Creating a new endpoint using the previously created template
new_endpoint = runpod.create_endpoint(
name="test",
template_id=new_template["id"],
gpu_ids="AMPERE_16",
workers_min=0,
workers_max=1,
)
# Output the created endpoint details
print(new_endpoint)
except runpod.error.QueryError as err:
# Handling potential errors during endpoint creation
print(err)
print(err.query)

Get GPUs​

For understanding the computational resources available, the get_gpus() function lists all GPUs that can be allocated to endpoints in RunPod. This enables optimal resource selection based on your computational needs.


import runpod
import json
import os
runpod.api_key = os.getenv("RUNPOD_API_KEY")
# Fetching all available GPUs
gpus = runpod.get_gpus()
# Displaying the GPUs in a formatted manner
print(json.dumps(gpus, indent=2))

Get GPU by Id​

Use get_gpu() and pass in a GPU Id to retrieve details about a specific GPU model by its ID. This is useful when understanding the capabilities and costs associated with various GPU models.


import runpod
import json
import os
runpod.api_key = os.getenv("RUNPOD_API_KEY")
gpus = runpod.get_gpu("NVIDIA A100 80GB PCIe")
print(json.dumps(gpus, indent=2))

Through these functionalities, the RunPod API enables efficient and flexible management of computational resources, catering to a wide range of project requirements.