Large Language Models (LLMs) like ChatGPT, Claude, and others can significantly streamline the process of integrating with Nash’s delivery orchestration API. This guide provides a quick overview of how to use LLMs with Nash API effectively.Documentation Index
Fetch the complete documentation index at: https://docs.usenash.com/llms.txt
Use this file to discover all available pages before exploring further.
Nash API Documentation for LLMs
When working with LLMs to assist with Nash API integration, provide the AI with comprehensive API documentation:- Complete API Documentation: https://docs.usenash.com/llms-full.txt
- Condensed Documentation: https://docs.usenash.com/llms.txt
Example Prompt
Best Practices for Using LLMs with Nash API
- Provide Clear Context: Share the relevant Nash API documentation links with the LLM
- Be Specific: Clearly describe your use case and requirements
- Include Complete Information: When troubleshooting, share error messages and API responses
Key Integration Areas Where LLMs Can Help
- Understanding Nash Concepts: Orders, Jobs, Batch Jobs, Dispatch Strategies
- API Request/Response Formatting: Generate code samples for API calls
- Webhook Implementation: Set up secure webhook handlers for delivery updates
- Error Handling: Understand and resolve API error responses
Security Considerations
- Never share API keys or sensitive customer data with LLMs
- Always review and test LLM-generated code before deploying to production