Box Developer Documentation

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Ask question

post
https://api.box.com/2.0
/ai/ask

Sends an AI request to supported LLMs and returns an answer specifically focused on the user's question given the provided context.

Request

bearer [ACCESS_TOKEN]
application/json

Request Body

The AI agent used to handle queries.

object arrayin bodyoptional

The history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response.

stringin bodyoptional
"Here is the first draft of your professional email about public APIs."

The answer previously provided by the LLM.

string (date-time)in bodyoptional
"2012-12-12T10:53:43-08:00"

The ISO date formatted timestamp of when the previous answer to the prompt was created.

stringin bodyoptional
"Make my email about public APIs sound more professional."

The prompt previously provided by the client and answered by the LLM.

booleanin bodyoptional
true

A flag to indicate whether citations should be returned.

object arrayin bodyrequired

The items to be processed by the LLM, often files.

Note: Box AI handles documents with text representations up to 1MB in size, or a maximum of 25 files, whichever comes first. If the file size exceeds 1MB, the first 1MB of text representation will be processed. If you set mode parameter to single_item_qa, the items array can have one element only.

stringin bodyrequired
"123"

The ID of the file.

stringin bodyrequired
"file"

The type of the item. Currently the value can be file only.

Value is always file

stringin bodyoptional
"This is file content."

The content of the item, often the text representation.

stringin bodyrequired
"multiple_item_qa"

The mode specifies if this request is for a single or multiple items. If you select single_item_qa the items array can have one element only. Selecting multiple_item_qa allows you to provide up to 25 items.

Value is one of multiple_item_qa,single_item_qa

stringin bodyrequired
"What is the value provided by public APIs based on this document?"

The prompt provided by the client to be answered by the LLM. The prompt's length is limited to 10000 characters.

Response

application/jsonAI response (Full)

A successful response including the answer from the LLM.

application/jsonClient error

An unexpected server error.

application/jsonClient error

An unexpected error.

post
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Request Example

cURL
curl -i -L POST "https://api.box.com/2.0/ai/ask" \
     -H "content-type: application/json" \
     -H "authorization: Bearer <ACCESS_TOKEN>" \
     -d '{
         "mode": "single_item_qa",
         "prompt": "What is the value provided by public APIs based on this document?",
         "items": [
            {
            "type": "file",
            "id": "9842787262"
            }
         ],
         "dialogue_history": [
              {
              "prompt": "Make my email about public APIs sound more professional",
              "answer": "Here is the first draft of your professional email about public APIs",
              "created_at": "2013-12-12T10:53:43-08:00"
              }
          ],
          "include_citations": true,
          "ai_agent": {
            "type": "ai_agent_ask",
            "long_text": {
              "model": "azure__openai__gpt_4o_mini",
              "prompt_template": "It is `{current_date}`, and I have $8000 and want to spend a week in the Azores. What should I see?",
            },
            "basic_text": {
              "model": "azure__openai__gpt_4o_mini",
           }
         }
      }'
TypeScript Gen
await client.ai.createAiAsk({
  mode: 'multiple_item_qa' as AiAskModeField,
  prompt: 'Which direction sun rises?',
  items: [
    new AiItemBase({
      id: fileToAsk1.id,
      type: 'file' as AiItemBaseTypeField,
      content: 'Earth goes around the sun',
    }),
    new AiItemBase({
      id: fileToAsk2.id,
      type: 'file' as AiItemBaseTypeField,
      content: 'Sun rises in the East in the morning',
    }),
  ],
} satisfies AiAsk);
Python Gen
client.ai.create_ai_ask(
    CreateAiAskMode.MULTIPLE_ITEM_QA.value,
    "Which direction sun rises?",
    [
        AiItemBase(
            id=file_to_ask_1.id,
            type=AiItemBaseTypeField.FILE.value,
            content="Earth goes around the sun",
        ),
        AiItemBase(
            id=file_to_ask_2.id,
            type=AiItemBaseTypeField.FILE.value,
            content="Sun rises in the East in the morning",
        ),
    ],
)
.NET Gen
await client.Ai.CreateAiAskAsync(requestBody: new AiAsk(mode: AiAskModeField.MultipleItemQa, prompt: "Which direction sun rises?", items: Array.AsReadOnly(new [] {new AiItemBase(id: fileToAsk1.Id, type: AiItemBaseTypeField.File) { Content = "Earth goes around the sun" },new AiItemBase(id: fileToAsk2.Id, type: AiItemBaseTypeField.File) { Content = "Sun rises in the East in the morning" }})));
Swift Gen (Beta)
try await client.ai.createAiAsk(requestBody: AiAsk(mode: AiAskModeField.multipleItemQa, prompt: "Which direction sun rises?", items: [AiItemBase(id: fileToAsk1.id, type: AiItemBaseTypeField.file, content: "Earth goes around the sun"), AiItemBase(id: fileToAsk2.id, type: AiItemBaseTypeField.file, content: "Sun rises in the East in the morning")]))
Java
BoxAIResponse response = BoxAI.sendAIRequest(
    api,
    "What is the content of the file?",
    Collections.singletonList("123456", BoxAIItem.Type.FILE),
    BoxAI.Mode.SINGLE_ITEM_QA
);
Python
items = [{
    "id": "1582915952443",
    "type": "file",
    "content": "More information about public APIs"
}]
ai_agent = {
    'type': 'ai_agent_ask',
    'basic_text_multi': {
        'model': 'openai__gpt_3_5_turbo'
    }
}
answer = client.send_ai_question(
    items=items, 
    prompt="What is this file?",
    mode="single_item_qa",
    ai_agent=ai_agent
)
print(answer)
.NET
BoxAIResponse response = await client.BoxAIManager.SendAIQuestionAsync(
    new BoxAIAskRequest
    {
        Prompt = "What is the name of the file?",
        Items = new List<BoxAIAskItem>() { new BoxAIAskItem() { Id = "12345" } },
        Mode = AiAskMode.single_item_qa
    };
);
Node
client.ai.ask(
    {
        prompt: 'What is the capital of France?',
        items: [
            {
                type: 'file',
                id: '12345'
            }
        ],
        mode: 'single_item_qa'
    })
    .then(response => {
        /* response -> {
            "answer": "Paris",
            "created_at": "2021-10-01T00:00:00Z",
            "completion_reason": "done"
        } */
    });

Response Example

{
  "answer": "Public APIs are important because of key and important reasons.",
  "citations": [
    {
      "content": "Public APIs are key drivers of innovation and growth.",
      "id": "123",
      "type": "file",
      "name": "The importance of public APIs.pdf"
    }
  ],
  "completion_reason": "done",
  "created_at": "2012-12-12T10:53:43-08:00"
}