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POST
https://api.keywordsai.co
/
api
/
files
import requests

url = "https://api.keywordsai.co/api/files/"
headers = {
    "Authorization": "Bearer YOUR_API_KEY"
}

with open("batch_input.jsonl", "rb") as f:
    files = {"file": f}
    data = {"purpose": "batch"}
    response = requests.post(url, headers=headers, files=files, data=data)

print(response.json())

{
  "id": "file-abc123",
  "object": "file",
  "bytes": 1024,
  "created_at": 1677610602,
  "filename": "batch_input.jsonl",
  "purpose": "batch"
}
Upload a file for use with OpenAI Batch API. The uploaded file is stored on OpenAI’s servers and can be used to create batch jobs for asynchronous LLM request processing.
Customer credentials required: This endpoint requires your own OpenAI API key configured in Keywords AI dashboard (Settings → Providers). Keywords AI passes the request through to OpenAI’s infrastructure.

​
Request body

The request must use multipart/form-data encoding.
​
file
file
required
The file to upload. Must be a valid JSONL (JSON Lines) file for batch processing.
{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-4", "messages": [{"role": "user", "content": "Hello!"}]}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "How are you?"}]}}
​
purpose
string
required
The intended purpose of the file. For batch jobs, use "batch".Supported values:
  • "batch" - For use with the Batch API

​
Response

Returns a file object with metadata about the uploaded file. 
{
  "id": "file-abc123",
  "object": "file",
  "bytes": 1024,
  "created_at": 1677610602,
  "filename": "batch_input.jsonl",
  "purpose": "batch"
}

import requests

url = "https://api.keywordsai.co/api/files/"
headers = {
    "Authorization": "Bearer YOUR_API_KEY"
}

with open("batch_input.jsonl", "rb") as f:
    files = {"file": f}
    data = {"purpose": "batch"}
    response = requests.post(url, headers=headers, files=files, data=data)

print(response.json())