# API reference **API Reference** Welcome to the KidJig API Reference, your comprehensive guide to all available endpoints for chat completion and related functionalities. This section provides detailed documentation on how to effectively interact with our [chat models](https://kidjig.gitbook.io/kidjig-docs/api-overview/text-models-llm/models), enabling you to integrate AI-driven conversational capabilities into your applications seamlessly. **Overview** The API Reference is structured to help developers understand the various endpoints, request formats, and response structures associated with chat completion. Each endpoint is designed to facilitate specific interactions with the chat model, allowing for a wide range of applications, from customer support to interactive storytelling. **Key Features of the API Reference:** * **Endpoint Documentation**: Each endpoint is thoroughly documented, including the required parameters, request methods, and example requests and responses. * **Error Handling**: Understand the different error codes and messages that may be returned, along with guidance on how to troubleshoot and resolve common issues. * **Best Practices**: Get tips on how to optimize your API calls for performance and reliability, ensuring a smooth integration experience. * **Interactive Examples**: Where applicable, explore interactive examples to see how the API works in real-time, helping you to visualize the integration process. By utilizing this API Reference, you’ll be equipped with the knowledge and tools needed to leverage the full potential of the KidJig API’s chat completion capabilities. Dive in and start building intelligent, conversational applications today! --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://kidjig.gitbook.io/kidjig-docs/api-provider/text-models-llm/api-reference.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.