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. ```typescript // 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. ```typescript // 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.