Documentation Index
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This guide explains how to save flows from the marketplace and customize them according to your specific requirements. 🛠️✨
Saving a Flow
When you find a useful flow in the Marketplace, you can save it locally for customization:
from mira_sdk import MiraClient
# Initialize client
client = MiraClient(config={"API_KEY": "YOUR_API_KEY"})
# Get the flow you want to customize
flow = client.flow.get("author/flow_name")
# Save to local YAML file
flow.save("/path/to/flow.yaml")
Customizing Your Flow
After saving the flow locally, you can modify the YAML file according to your needs. Here are the key areas you can customize:
Update the flow’s basic information to reflect your ownership and purpose:
metadata:
name: "your-customized-flow-name" # Rename flow
description: "Your modified description" # Flow description
author: "your-username" # Your Mira Flows username
tags: [your, custom, tags] # Discovery keywords
private: true # Access control setting (true/false)
Modify input parameters to match your requirements:
inputs:
custom_input:
type: string # Input type
description: "Your custom input description" # Input description
required: true # Required field
example: "Your example value" # Example value
Updating the Prompt
Customize the prompt to achieve your desired output:
prompt: |
Your customized instructions...
You can use {custom_input} as a placeholder
Modifying Model Settings
Change the model configuration if needed:
model:
provider: "provider-name" # AI service provider
name: "your-preferred-model" # Specific model identifier
Testing Your Customized Flow
Before deployment, test your modifications to ensure everything works correctly:
from mira_sdk import Flow
# Load your modified flow
modified_flow = Flow(source="/path/to/flow.yaml")
# Test with sample inputs
test_input = {"custom_input": "test value"}
response = client.flow.test(modified_flow, test_input)
Deploying Your Custom Flow
Once you’re satisfied with the modifications:
# Deploy as your own flow
client.flow.deploy(modified_flow)
For more detailed information about customization options and best practices, please refer to our complete documentation 📖🔗.