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Completions

OpenAI Completions

Properties used to connect to OpenAI's legacy Chat Completions API.

completions​

  • Type: true | {
         system_prompt?: string,
         model?: string,
         max_tokens?: number,
         temperature?: number,
         top_p?: number,
         modalities?: ['text', 'audio'],
         audio?: {format: string, voice: string},
         ChatFunctions
    }
  • Default: {model: "gpt-5.4"}

Connect to OpenAI's legacy Completions API. You can set this property to true or configure it using an object:
system_prompt is used to set the "system" message for the conversation context.
model is the name of the model to be used by the API. Check /v1/chat/completions for more.
max_tokens the maximum number of tokens to generate in the chat. Check tokenizer for more info.
temperature is used for sampling; between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused.
top_p is an alternative to sampling with temperature, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
modalities and audio are required to generate responses in audio format. Info here and see autoPlay.
ChatFunctions encompasses properties used for function calling.

Basic Example​

<deep-chat
  directConnection='{
    "openAI": {
      "key": "placeholder key",
      "completions": {"max_tokens": 2000, "system_prompt": "Assist me with anything you can"}
    }
  }'
></deep-chat>
info

Use stream to stream the AI responses.

Files Example​

You can send image and audio files in your conversation. Make sure you are using the correct model for each by checking model modalities.

<deep-chat
  directConnection='{
    "openAI": {
      "key": "placeholder key",
      "completions": {"model": "gpt-4.1"}
  }}'
  images="true"
  camera="true"
></deep-chat>
tip

When sending files we advise you to set maxMessages to 1 to send less data and reduce costs.

note

microphone is not supported for audio chat, instead we recommend using the realtime sts API.

Functions​

Examples for OpenAI's Function Calling features:

Chat Functions​

Configure the completions API to call your functions via the OpenAI Function calling API.
This is particularly useful if you want the model to analyze user's requests, check whether a function should be called, extract the relevant information from their text and return it all in a standardized response for you to act on.
tools defines the functions that the model can signal to call based on the user's text.
tool_choice controls which (if any) function should be called.
function_handler is the actual function that is called with the model's instructions.

// using JavaScript for a simplified example

chatElementRef.directConnection = {
  openAI: {
    completions: {
      tools: [
        {
          type: 'function',
          function: {
            name: 'get_current_weather',
            description: 'Get the current weather in a given location',
            parameters: {
              type: 'object',
              properties: {
                location: {
                  type: 'string',
                  description: 'The city and state, e.g. San Francisco, CA',
                },
                unit: {type: 'string', enum: ['celsius', 'fahrenheit']},
              },
              required: ['location'],
            },
          },
        },
      ],
      function_handler: (functionsDetails) => {
        return functionsDetails.map((functionDetails) => {
          return {
            response: getCurrentWeather(functionDetails.arguments),
          };
        });
      },
    },
    key: 'placeholder-key',
  },
};

Tools​

  • Type: {
         type: "function" | "object",
         function: {name: string, description?: string, parameters: JSONSchema}
    }[]

An array describing tools that the model may call.
name is the name of a function.
description is used by the model to understand what the function does and when it should be called.
parameters are arguments that the function accepts defined in a JSON Schema (see example above).
Checkout the following guide for more about function calling.

tip

If your function accepts arguments - the type property should be set to "function", otherwise use the following object {"type": "object", "properties": {}}.

FunctionHandler​

The actual function that the component will call if the model wants a response from tools functions.
functionsDetails contains information about what tool functions should be called.
This function should either return an array of JSONs containing a response property for each tool function (in the same order as in functionsDetails) which will feed it back into the model to finalise a response, or return a JSON containing text which will immediately display it in the chat and not send any details to the model.