Implement provider-specific logic when integrating different AI services, as each provider has unique requirements for message formatting, API endpoints, validation rules, and optimization strategies.
Different AI providers require distinct handling approaches:
Message Role Handling: Transform message roles based on provider requirements. For example, Baidu requires system messages to be converted to assistant/user roles and maintains strict alternating patterns, while Google converts system roles to user roles.
// Provider-specific message role transformation
const messages = options.messages.map((v) => ({
role: v.role === "system" ? "assistant" : v.role, // Baidu-specific
content: getMessageTextContent(v),
}));
// vs Google-specific transformation
role: v.role.replace("assistant", "model").replace("system", "user"),
API Path Construction: Use provider-specific URL patterns and model handling. Azure requires deployment names in URLs, while Gemini needs dynamic model injection into paths.
// Provider-specific path handling
if (modelConfig.providerName == ServiceProvider.Azure) {
chatPath = this.path(`/deployments/${deploymentName}/chat/completions`);
} else {
chatPath = this.path(OpenaiPath.ChatPath);
}
Model-Specific Optimization: Apply provider-specific models for different operations like summarization, using each provider’s most suitable and cost-effective options rather than defaulting to a single model across all providers.
This approach ensures compatibility, optimal performance, and proper functionality across different AI service providers while maintaining clean, maintainable code.
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