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/user messages

Parameter	Type	Direction	Description
SYSTEM_MESSAGE	TEXT	IN	The system 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, or user
MESSAGE_CONTENTx	TEXT	IN	The user message content, where x corresponds to the message number

With a JSON message array

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

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

[
    {
        "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

{
  "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"]
  }
}