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Using Marketplace Flows

Mira Flows offers a marketplace where you can explore and use a variety of pre-built flows. There are two primary ways to utilize these flows:

  1. Using the Mira Flows SDK
  2. Direct API calls (without the SDK)

Exploring the Marketplace

To discover available flows:

  1. Navigate to the Marketplace
  2. Browse or search for flows that fit your needs

Mira Flows offers a marketplace where you can explore and use a variety of pre-built flows. There are two primary ways to utilize these flows:

  1. Using the Mira Flows SDK
  2. Direct API calls (without the SDK)

Using flows via the SDK

python
from mira_sdk import MiraClient, Flow

# Initialize the client
client = MiraClient(config={"API_KEY": "YOUR_API_KEY"})

version = "1.0.0"
input_data = {"key": "value"}

# If no version is provided, latest version is used by default
if version:
	flow_name = f"author/your-flow-name/{version}"
else:
	flow_name = "author/your-flow-name"

result = client.flow.execute(flow_name, input_data)
print(result)

Flow Management via SDK

python
from mira_sdk import MiraClient, Flow

# Get a flow
flow = client.flow.get("author/flow_name")

# Get flows by author
flows = client.flow.get_by_author("author")

# Get flows by tag
flows = client.flow.get_by_tag("tag")

# Search for flow
flows = client.flow.search("abcd")

Direct API Calls (Without SDK)

For those who prefer not to use the SDK or are working in other programming languages, you can interact with flows directly via API calls:

  1. Find the flow you want to use in the marketplace and view its API documentation.
  2. Use the flow's API endpoint in your HTTP requests
curl --request POST \
  --url https://console-bff.stg.arohalabs.dev/v1/flows/flows/{author}/{flow_name} \
  --header 'MiraAuthorization: YOUR_API_KEY' \
  --data '{
	"input_param": "value"
}'

Replace YOUR_API_KEY, author and flow_name with your actual API key, author name and flow_name and adjust the endpoint and payload structure according to the specific flow's requirements.

Response:

json
{
  "result": "LLM output"
}