> ## 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.

# Using LLMs with Nash API

> A guide to leveraging LLMs for Nash API integration and development

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.

## 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](https://docs.usenash.com/llms-full.txt)
* **Condensed Documentation**: [https://docs.usenash.com/llms.txt](https://docs.usenash.com/llms.txt)

These specially formatted text files contain the Nash API endpoints, schemas, and implementation details in a format that's optimized for LLMs to process.

## Example Prompt

```
I'm working on integrating with Nash's delivery API. Here's the relevant documentation:
https://docs.usenash.com/llms-full.txt

I need to implement [SPECIFIC FUNCTIONALITY]. Can you help me understand how to structure this request?
```

## Best Practices for Using LLMs with Nash API

1. **Provide Clear Context**: Share the relevant Nash API documentation links with the LLM
2. **Be Specific**: Clearly describe your use case and requirements
3. **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

1. **Never share API keys** or sensitive customer data with LLMs
2. **Always review and test** LLM-generated code before deploying to production

For comprehensive integration guidance, refer to our [Plan Your Integration](/reference/plan-your-integration) documentation.