Select and Switch AI Services Dynamically
Runtime AI service selector for Semantic Kernel that enables dynamic switching between multiple AI providers and models during execution.
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Why it matters
Dynamically select and switch between different AI services at runtime. This asset enables flexible integration with multiple AI providers, allowing your application to adapt its AI backend based on specific needs or conditions.
Outcomes
What it gets done
Implement custom logic for AI service selection.
Switch between different AI models or providers seamlessly.
Adapt AI service usage based on runtime requirements.
Integrate multiple AI services within a single application.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/sk-concept-serviceselector | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Semantic Kernel - Service Selector
This skill provides the ability to select and switch between AI services at runtime within Semantic Kernel applications. It includes a Python example (custom_service_selector.py) demonstrating how to implement custom service selection logic that determines which AI provider or model handles each request during execution. Use this when you need to route AI requests to different providers or models based on runtime conditions such as cost optimization, performance requirements, availability, or request characteristics. It's ideal for applications that must remain flexible across multiple AI services without hardcoding provider choices.
What it does
When I need to build flexible AI applications that can adapt to changing requirements or optimize for cost and performance, I want to dynamically select and switch between different AI services at runtime, so that I can route requests to the most appropriate model or provider without redeploying code. This skill demonstrates custom service selection logic through a concrete Python example (custom_service_selector.py) that shows how to implement runtime switching between AI services in Semantic Kernel.
Source README
Selecting and switching between AI services at runtime
Examples (1 files):
custom_service_selector.py
Discussion
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