This guide explains the Chat completion endpoint which can be thought of as having a conversation with our LLM.

This endpoint facilitates engaging and dynamic conversations between a user and an AI-assisted chat model. It’s designed to handle both multi-turn and single-turn interactions effectively. This guide will walk you through making requests to the endpoint and understanding its responses.

Your API key can be generated using these steps.

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Endpoint overview

This endpoint is designed for generating chat responses based on a conversation history provided in the request. It supports complex, contextual interactions that can simulate a conversational partner. The responses will contain the following variables:

  1. id: A unique identifier for the conversation.
  2. choices: Contains objects describing the completion, including the role (user or assistant) and content.
  3. finish_reason: Indicates why the response was concluded (stop, length, function_call, content_filter, null).

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Usage example

Here’s how you can use the endpoint in a practical scenario:

1

Create a request

Use your preferred HTTP client to send a POST request to api.writer.com/v1/chat with the JSON payload.

2

Handle the response

For the response parse the JSON to access the generated text.

3

Error handling

Ensure to handle potential errors such as timeouts or model errors gracefully.

4

Rate limiting

Be mindful of any rate limits that might apply to avoid service disruptions.

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Best practices

This guide should equip you with the knowledge to integrate and utilize the Chat completion endpoint effectively, enhancing your applications with robust, conversational AI capabilities.

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