Configure LLM providers and models for Exo agents via ModelConfig.
npx skills add https://github.com/midsphere-ai/exo --skill exo-models
Please help me install this Agent Skill. Skill: exo:models Source: https://github.com/midsphere-ai/exo/tree/main/skills/models Command: npx skills add https://github.com/midsphere-ai/exo --skill exo-models
Configures which LLM provider and model an Exo agent uses, including API keys, endpoints, and custom providers, enabling seamless model swapping.
Create an Agent with model "openai:gpt-4o" and ensure the corresponding API key is available in your environment.
High-intent search queries and answers about installing and using this skill.
To configure LLM provider settings, create an Agent with a model string like "openai:gpt-4o" and ensure the corresponding API key is available in your environment variables for seamless model swapping.
Yes, you can register custom providers and integrate optional context window mappings to tailor provider behavior across OpenAI, Anthropic, Gemini, and Vertex for multimodal tools.
Model string parsing uses the provider:model format to enable lazy provider resolution, allowing the Exo agent to dynamically select the correct LLM provider and model configuration.
Yes, environment variables are required to securely supply API keys and endpoints, which ModelConfig and the provider registry use to authenticate and manage your selected LLM providers.
Handling token counting across multiple providers requires using ModelConfig alongside the model_registry, ensuring accurate context window mappings and provider-specific options for multimodal tools.
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