> For the complete documentation index, see [llms.txt](https://docs.advantys.com/workflowgen-administration-module-reference-guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.advantys.com/workflowgen-administration-module-reference-guide/workflow-applications/openai/openaichat.md). # OPENAICHAT ## Overview The **OPENAICHAT** workflow application lets you interact with an OpenAI chat model. ## How it works * The application allows you to interact with OpenAI completion models. * Application logs are available. These can be specified by setting the value of the `OpenAIChatLogLevel` parameter in the `web.config` file to `0` to deactivate logs, `1` for error logs, `2` for information logs, or `3` for debug logs; the default value is `0`. ## Required parameters

Parameter	Type	Direction	Description
`MODEL`	TEXT	IN	ID of the model to use You can find available models at the following link: https://platform.openai.com/docs/models/model-endpoint-compatibility; the endpoint used by default is `/v1/chat/completions`.

You can use either of the following configurations: with system/user messages, with a message number, or with a JSON message array. ### With system/developer/user messages

Parameter	Type	Direction	Description
`SYSTEM_MESSAGE`	TEXT	IN	The system message content
`DEVELOPER_MESSAGE`	TEXT	IN	The developer message content
`USER_MESSAGE`	TEXT	IN	The user message content

### With a message number

Parameter	Type	Direction	Description
`MESSAGE_ROLEx`	TEXT	IN	The type of the message, where `x` corresponds to the message number; the value should be `assistant`, `system`, `user`, or `developer`
`MESSAGE_CONTENTx`	TEXT	IN	The user message content, where `x` corresponds to the message number

### With a JSON message array

Parameter Type Direction Description

Parameter	Type	Direction	Description
`MESSAGE_JSON`	TEXT	IN	The JSON array message object; the structure should match the following example: `[ { "role": "assistant", "content": "First message content" }, { "role": "system", "content": "Second message content" } ]`

MESSAGE_JSON

TEXT

The JSON array message object; the structure should match the following example:

[
    {
        "role": "assistant",
        "content": "First message content"
    },
    {
        "role": "system",
        "content": "Second message content"
    }
]

## Optional parameters

Parameters	Type	Direction	Description
`API_KEY`	TEXT	IN	OpenAI API key By default, this value comes from the `OpenAIApiKey` parameter in the `web.config` file.
`URL`	TEXT	IN	API endpoint; defaults to `https://api.openai.com/v1/audio/transcriptions`
`TEMPERATURE`	NUMERIC	IN	Sampling temperature, between `0` and `1`; defaults to `1` Higher values (e.g. `0.8`) will make the output more random, while lower values (e.g. `0.2`) will make it more focused and deterministic.
`TOP_P`	NUMERIC	IN	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with `top_p` probability mass. Therefore, `0.1` means only the tokens comprising the top 10% probability mass are considered. Defaults to `1`
`FREQUENCY_PENALTY`	NUMERIC	IN	Number between `-2.0` and `2.0`. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. Defaults to `0`
`MAX_TOKENS`	NUMERIC	IN	Maximum number of tokens that can be generated in the chat completion; defaults to `256`
`PRESENCE_PENALTY`	NUMERIC	IN	Number between `-2.0` and `2.0`; defaults to `0` Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
`RESPONSE_FORMAT`	TEXT	IN	Format of the response: `json_object`, `text`, `or json_schema` When the value is `json_object`, the system prompt should contain the JSON keyword. When the value is `json_schema`, the expected schema must be provided in the `RESPONSE_FORMAT_JSON_SCHEMA` parameter.
`RESPONSE_FORMAT_JSON_SCHEMA`	TEXT	IN	The JSON schema that will be used by the model to respond. See the `RESPONSE_FORMAT_JSON_SCHEMA` section below for an example.
`APP_RESPONSE_IGNORE_ERROR`	TEXT	IN	Specifies (`Y` or `N`) if error should be ignored; defaults to `N` In case of error, if the parameter has `Y` as its value, the error will be ignored and defined OUT parameters (`APP_RESPONSE_STATUS` or `APP_RESPONSE_CONTENT`) will be mapped. Otherwise, an exception will be thrown.
`TOOLS`	TEXT	IN	List of tools available to the model, formatted in JSON and compliant with OpenAI's format: https://platform.openai.com/docs/api-reference/chat/create#chat-create-tools. See the `TOOLS` section below for an example.
`TOOL_CHOICE_REQUIRED`	TEXT	IN	Specifies whether the model must necessarily choose a tool. Values: `Y` or `N` (default).
`PARALLEL_TOOL`	TEXT	IN	Specifies whether the model can choose multiple tools. Values: `Y` (default) or `N`.
`MESSAGE_HISTORY`	TEXT	INOUT	The message history in JSON format. The reference structure follows OpenAI's documentation for the `messages` object: https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages.
`SELECTED_TOOL`	TEXT	OUT	The list of selected tool names, separated by commas
`SELECTED_TOOL_PARAM`	TEXT	OUT	A JSON array representing the list of selected tools along with their parameters. See the `SELECTED_TOOLS_PARAMS` section below for an example output.
`SELECTED_TOOLS_COUNT`	TEXT	OUT	The number of selected tools
`RESULT`	TEXT	OUT	Chat result call
`RESULT_CONTENT`	TEXT	OUT	Content of the assistant message
`RESULT_TOTAL_TOKENS`	NUMERIC	OUT	Total of tokens used for generation
`RESULT_COMPLETION_TOKENS`	NUMERIC	OUT	Total of tokens used for generation
`RESULT_PROMPT_TOKENS`	NUMERIC	OUT	Total of token used for the prompt
`APP_RESPONSE_STATUS`	TEXT	OUT	Response status code
`APP_RESPONSE_CONTENT`	TEXT	OUT	Response payload or error message
`TRIM_SIZE`	NUMERIC	IN	Number of messages from the end of the conversation history to be kept
`TRIM_SKIP`	NUMERIC	IN	Number messages from the beginning of the conversation history to be kept

## JSON schema use case Using a JSON schema as a response format enforces the application to respond in a structured manner that aligns with the schema. You can directly extract the returned values to populate specific data; simply specify the name of the property to extract as the parameter name and set the target data in OUT. ## Examples ### `TOOLS`

[
    {
        "name": "GET_STOCK_INFORMATION",
        "description": "Get stock information about a product. If the product is not found, return an error. If the stock is less than 10, return a warning and a purchase order should be done.",      
        "parameters": {
            "type": "object",
            "properties": {
                "product_name": {
                    "type": "string",
                    "description": "The product name"
                },
                "serial_number": {
                    "type": "string",
                    "description": "The product serial number"
                }
            },
            "additionalProperties": false,
            "required": ["serial_number"]
        }
    },
    {
        "name": "PURCHASE_ORDER",
        "description": "Make a purchase order for a product.",    
        "parameters": {
            "type": "object",
            "properties": {
                "product_name": {
                    "type": "string",
                    "description": "The product name"
                },
                "serial_number": {
                    "type": "string",
                    "description": "The product serial number"
                },
                "quantity": {
                    "type": "number",
                    "description": "The quantity of the product to purchase"
                }
            },
            "additionalProperties": false,
            "required": ["serial_number", "quantity"]
        }
    }
]

### `SELECTED_TOOLS_PARAMS` ```json [ { "name": "GET_STOCK_INFORMATION", "id": "call_Vuc2Ga8jP7vUksxG9C0fwpY8", "parameters": { "product_name": "vis", "serial_number": "V45645" } }, { "name": "GET_STOCK_INFORMATION", "id": "call_nq3SCVUk0FjAHCeqOZGNXpC8", "parameters": { "product_name": "boulons", "serial_number": "b456" } } ] ``` ### `RESPONSE_FORMAT_JSON_SCHEMA` ```json { "name": "schema", "schema": { "$schema": "http://json-schema.org/draft-04/schema#", "type": "object", "properties": { "advice": { "type": "string" }, "next_action": { "type": "string", "enum": ["expert","sales","support","logistics",null] }, "confidence_level": { "type": "number" } }, "required": ["advice", "next_action","confidence_level"] } } ```