Leaderboard Deploy agents

Ensure consistent patterns and configurations across all AI model providers to maintain code maintainability and scalability. This includes providing proper default configurations for all providers and minimizing provider-specific conditional logic that can become unwieldy as more AI models are integrated.

Key practices:

• Always define default model IDs for new AI providers
• Use unified configuration patterns rather than provider-specific if/else chains
• Apply consistent token limit handling across different providers when possible
• Design provider integrations with future model additions in mind

Example of inconsistent approach to avoid:

// Avoid provider-specific logic scattered throughout
const maxTokens = apiConfiguration?.apiProvider === "gemini" 
    ? geminiModels[geminiDefaultModelId].maxTokens
    : anthropicModels["claude-3-7-sonnet-20250219"].maxTokens

// Instead, use a unified approach
case "sambanova":
    return getProviderData(sambanovaModels, sambanovaDefaultModelId) // Always provide default

This approach reduces technical debt and makes the codebase more maintainable as the number of supported AI providers grows.