Join BoxWorks 2024 to discover what's possible with content and AI!
Register now!Sends an AI request to supported Large Language Models (LLMs) and extracts metadata in form of key-value pairs. Freeform metadata extraction does not require any metadata template setup before sending the request.
The AI agent to be used for extraction.
The items that LLM will process. Currently, you can use files only.
"123"
The ID of the file.
"file"
The type of the item. Currently the value can be file
only.
Value is always file
"This is file content."
The content of the item, often the text representation.
"\"fields\":[{\"type\":\"string\",\"key\":\"name\",\"displayName\":\"Name\",\"description\":\"The customer name\",\"prompt\":\"Name is always the first word in the document\"},{\"type\":\"date\",\"key\":\"last_contacted_at\",\"displayName\":\"Last Contacted At\",\"description\":\"When this customer was last contacted at\"}]"
The prompt provided to a Large Language Model (LLM) in the request. The prompt can be up to 10000 characters long and it can be an XML or a JSON schema.
A response including the answer from the LLM.
An unexpected client error.
An unexpected server error.
curl -i -L 'https://api.box.com/2.0/ai/extract' \
-H 'content-type: application/json' \
-H 'authorization: Bearer <ACCESS_TOKEN>' \
-d '{
"prompt": "Extract data related to contract conditions",
"items": [
{
"type": "file",
"id": "1497741268097"
}
],
"ai_agent": {
"type": "ai_agent_extract",
"long_text": {
"model": "azure__openai__gpt_3_5_turbo_16k",
"system_message": "You are a helpful travel assistant specialized in budget travel",
"prompt_template": "It is `{current_date}`, and I have $8000 and want to spend a week in the Azores. What should I see?",
"num_tokens_for_completion": 8400,
"llm_endpoint_params": {
"type": "openai_params",
"temperature": 0,
"top_p": 1,
"frequency_penalty": 1.5,
"presence_penalty": 1.5,
"stop": "<|im_end|>"
},
"embeddings": {
"model": "openai__text_embedding_ada_002",
"strategy": {
"id": "basic",
"num_tokens_per_chunk": 64
}
}
},
"basic_text": {
"model": "azure__openai__gpt_3_5_turbo_16k",
"system_message": "You are a helpful travel assistant specialized in budget travel",
"prompt_template": "It is `{current_date}`, and I have $8000 and want to spend a week in the Azores. What should I see?",
"num_tokens_for_completion": 8400,
"llm_endpoint_params": {
"type": "openai_params",
"temperature": 0,
"top_p": 1,
"frequency_penalty": 1.5,
"presence_penalty": 1.5,
"stop": "<|im_end|>"
}
}
}
}'
await client.ai.createAiExtract({
prompt: 'firstName, lastName, location, yearOfBirth, company',
items: [new AiItemBase({ id: file.id })],
} satisfies AiExtract);
client.ai.create_ai_extract(
"firstName, lastName, location, yearOfBirth, company",
[AiItemBase(id=file.id)],
ai_agent=ai_extract_agent_config,
)
await client.Ai.CreateAiExtractAsync(requestBody: new AiExtract(prompt: "firstName, lastName, location, yearOfBirth, company", items: Array.AsReadOnly(new [] {new AiItemBase(id: file.Id)})));
try await client.ai.createAiExtract(requestBody: AiExtract(prompt: "firstName, lastName, location, yearOfBirth, company", items: [AiItemBase(id: file.id)]))
BoxAIResponse response = BoxAI.extractMetadataFreeform(
api,
"firstName, lastName, location, yearOfBirth, company",
Collections.singletonList(new BoxAIItem("123456", BoxAIItem.Type.FILE))
);
{
"answer": "Public APIs are important because of key and important reasons.",
"completion_reason": "done",
"created_at": "2012-12-12T10:53:43-08:00"
}