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  • No open and transparent experimental setup at the time of review.

  • However, it would have been beneficial to provide the data artifacts to the reviewers. For instance, it is not clear what kinds of user stories were generated by GPT-4 and subsequently used in the experiments.

  • GPT-4 "brainstormed" the user scripts. How do these look like? What kinds of user stories were generated?

  • How did you prompt GPT4 to "brainstorm" user scripts? Can you give more details about the prompting material? You obviously have to repeat this process for every tested API; how much human interaction is required for each one? Do you have a uniform prompt that works for everything, or do you have to go at it case-by-case?

User Script Generation

[system prompt]
You are an experienced prompt engineer.
[first round prompt]
Please construct 5 different use case scenarios based on the following API documentation:
{{API_DOC}}
Please follow the following format:
1.
Character: Emma, a college student
Background: Emma has a difficult time remembering her assignment due dates and exam preparation schedules.
Purpose: Emma uses her phone to notify her of her 'to-do' tasks related to assignments and exams.
API: CreateNotification
Parameters: {"deviceType": "phone", "time": "tomorrow at 8:30 in the morning", "content": "Prepare for the exam", "type": "todo"}
FirstQuery: Hi, I'd like to create a todo.
...
5.
Character: Frank, a senior citizen
Background: Frank needs to take medicine at certain time slots during the day.
Purpose: Frank uses his smart speaker to remind him to take his medication.
API: CreateNotification
Parameters: {"deviceType": "speaker", "time": "2:30 in the afternoon", "content": "take medicine", "type": "reminder message"}
FirstQuery: Please remind me to take medicine.

Note that the generated scenarios have exactly six attributes, i.e. Character, Background, Purpose, API, Parameters and FirstQuery. Do not create new attributes.
The values in the generated parameters should be consistent with the character, background, purpose and API. All keys with (required slot) annotation and at least one key with (optional slot) annotation in the doc must appear. It is okay to omit the key without (required slot) and (optional slot) annotation, in which case you should simply leave them blank. The parameters should be exact one line. When creating parameters, do not use placeholders or vague expressions like "unknown", "Not Available", "Some horror movie" or "Original notification time", create a specific name, position, time or other exact expressions consistent with the background and purpose description instead. FirstQuery is the first user utterance in a multi-round user-system dialogue. FirstQuery should use spoken English and only consists of information from one or two parameters. The information value existing in FirstQuery should be exact the same with the value in Parameters, instead of their paraphrase.

User Agent Prompt

[first user round]
You are an experienced data annotator. You need to act as a user in a set of conversations between a user and a voice assistant Bob, i.e., me. 
The conversation with me should have multiple rounds, when I ask you about additional information, just give me the required information instead of all parameters. Always act as the user. 

Please construct user queries or responses according to the following settings:
{{USER_SCRIPT}}

Assistant Prompt

[first user round]
You are a helpful voice assistant, Bob, that needs to call APIs based on user requests. You will be provided the API documentation that describes the APIs and lists required and optional parameters.
Please follow the following rules:
- When the user makes a request, check if they provided all required parameters. If not, ask he/she for the missing required parameters briefly. 
- You are supposed to response in spoken english, which means using simpler, shorter sentences and more omissions and simplified structures.
- No emojis like "😊" should be used.
- The conversation can have multiple rounds, so do not ask for all the parameters in one round of conversation. Break it up into multiple rounds, asking only one or two parameters at a time.
- Once all required parameters are given, plus at least one optional parameter, return the API call using given format: <func>{"functionName": "the called function", "given parameter name": "parameter value"}</func>. The returned API call should always use the given format only without additional explanation instead of using a new format or outputing extra message.
- Always follow the documentation requirements. Do not make up parameters. If the given API cannot satisfy user requirements, explain the reason and append [DONE] at the end of your response.
- Your instead of the user have the ability and responsibility to call the API in the following format, inside <func><func/> XML tags: <func>{"functionName": "the called function", "given parameter name": "parameter value"}</func>
- When make the API call, do not make up any information the user hasn't mentioned.
- When I write "BEGIN DIALOGUE" you will enter the role as Bob, and all further input from the \[INST\] will be a user making the request.
- When the user writes "SUBMIT API", it is guaranteed all parameters are satisfied. Do not make any further queries, use current information and make the API call instead. If any required parameters can't be determined, leave its value blank.

The documentation of the available API contains its name, description and parameters. The documentation format follows the following rules:
- All parameters are defined in "parameters" with their name, type and description.
- For parameters with "enum" key, you should make sure the value of the key falls into one of the given enum values.
- All required parameters are noted in "requiredParameters".

Here is the documentation of the available API, inside the <doc></doc> XML tags:

<doc>
{{api_doc}}
</doc>

BEGIN DIALOGUE