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Register file upload
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Register file upload

Register a completed file upload after using the resumable upload flow.

POSThttps://api.aitronos.com/v1/organizations/{organization_id}/files

Register a file after successfully uploading it to cloud storage using the resumable upload URL. This endpoint validates that the file exists in storage, verifies the file type and size, and creates the database record.

This endpoint is the final step in the resumable upload flow. For simpler uploads under 100MB, use the direct upload endpoint instead.

Path Parameters

organization_id string required

The unique identifier of the organization.

Request Body

filename string required

Original filename (1-255 characters).

gcs_path string required

Cloud storage path where the file was uploaded. This is returned from the generate upload URL endpoint.

file_size integer required

File size in bytes. Must be greater than 0.

mime_type string required

MIME type of the file.

Returns

Returns a File object with complete metadata. The file is now ready to be used in vector stores or AI conversations.

cURL
curl -X POST https://api.aitronos.com/v1/organizations/org_123/files \
  -H "X-API-Key: $FREDDY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filename": "large_video.mp4",
    "gcs_path": "files/org_123/file_abc123xyz789/large_video.mp4",
    "file_size": 524288000,
    "mime_type": "video/mp4"
  }'

Complete Resumable Upload Flow

import os
import requests

api_key = os.environ["FREDDY_API_KEY"]
org_id = "org_123"
file_path = "/path/to/large_video.mp4"

# Step 1: Generate upload URL
upload_url_endpoint = f"https://api.aitronos.com/v1/organizations/{org_id}/files/upload-url"
headers = {"X-API-Key": api_key}

with open(file_path, 'rb') as f:
    file_size = len(f.read())

upload_url_data = {
    "filename": "large_video.mp4",
    "file_size": file_size,
    "mime_type": "video/mp4"
}

response = requests.post(upload_url_endpoint, headers=headers, json=upload_url_data)
session = response.json()

# Step 2: Upload file to GCS
with open(file_path, 'rb') as f:
    upload_headers = {'Content-Type': 'video/mp4'}
    requests.put(session['upload_url'], headers=upload_headers, data=f)

# Step 3: Register the completed upload
register_endpoint = f"https://api.aitronos.com/v1/organizations/{org_id}/files"
register_data = {
    "filename": "large_video.mp4",
    "gcs_path": session['gcs_path'],
    "file_size": file_size,
    "mime_type": "video/mp4"
}

response = requests.post(register_endpoint, headers=headers, json=register_data)
file_obj = response.json()
print(f"Upload complete! File ID: {file_obj['id']}")

Upload Process

  1. Call generate upload URL to get an upload session
  2. Upload file to the returned URL using resumable upload protocol
  3. Call this endpoint to validate and register the completed upload
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