Building on Mira isn't just about execution; it’s about scalability and interoperability. When you architect a flow using the SDK, you are creating a portable asset.
Encapsulation: The SDK allows you to wrap complex prompts and configurations into a single, callable endpoint. This hides the "sausage-making" from the end-user, providing a clean API for integration.
Version Control: As AI models evolve, you can update individual components of your flow without breaking the entire system.
Marketplace Integration: Once a flow is perfected, it can be deployed to the Mira Marketplace. This enables other developers to discover and utilize your workflow, creating opportunities for collaboration and monetization.
Step-by-Step: From Concept to Execution
The workflow for building with the Mira SDK is designed to be developer-friendly and iterative.
1. Defining the Logic
First, you map out the sequence. For example, a "Content Strategist" flow might involve three steps: researching a topic via a search tool, generating a blog outline with a high-reasoning model, and finally, SEO-optimizing the text with a specialized agent.
2. Configuring the SDK
Using the Mira SDK, you initialize your flow by defining the dependencies. You specify which models are used at each node and how the data "flows" between them. The SDK handles the heavy lifting of API authentication and state management.
3. Testing and Deployment
The SDK provides local testing environments to ensure your logic holds up under different input scenarios. Once validated, a simple deployment command pushes your flow to the Mira Marketplace, making it live and executable.@Mira - Trust Layer of AI