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To build models on the Plexe Platform using your own data, you first need to upload it. The API typically provides a mechanism to upload files, often involving pre-signed URLs for direct S3 uploads. Base URL: https://api.plexe.ai
The Plexe Platform uses a secure upload mechanism with pre-signed URLs to protect your data during transfer. This allows you to upload files directly to secure cloud storage without exposing your API key in the process. For more details on the API endpoints, refer to the Data Management API Reference.

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Authentication

Ensure you have your API key included in the x-api-key header. 
import requests
import os
import json

api_key = os.getenv("PLEXE_API_KEY")
if not api_key:
    raise ValueError("Please set the PLEXE_API_KEY environment variable.")

base_url = "https://api.plexe.ai"
headers = {
    "x-api-key": api_key,
    "Content-Type": "application/json" # Usually for control requests
}

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Upload Process (Using Pre-signed URLs)

This is typically a multi-step process:
  1. Request Upload URL: Tell the API you want to upload a file and get a secure, temporary URL to upload directly to storage (usually S3).
  2. Upload File: Use the provided URL to upload your file data.
  3. Confirm Upload: Notify the API that the upload to the storage location is complete.

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Step 1: Request Pre-signed Upload URL

Make a POST request to the upload initiation endpoint (e.g., /uploads). Provide the filename and content type. 
file_path = "path/to/your/training_data.csv" # Replace with your file path
file_name = os.path.basename(file_path)
content_type = "text/csv" # Adjust based on your file type (e.g., 'application/json', 'application/octet-stream')

print(f"Requesting upload URL for: {file_name}")

try:
    init_response = requests.post(
        f"{base_url}/uploads",
        headers=headers,
        json={"filename": file_name, "content_type": content_type}
    )
    init_response.raise_for_status()
    upload_info = init_response.json()

    presigned_url = upload_info.get("presigned_url")
    temp_upload_id = upload_info.get("upload_id")
    s3_key = upload_info.get("key")

    if not presigned_url or not temp_upload_id or not s3_key:
        raise ValueError("Incomplete upload information received from API.")

    print(f"Successfully obtained upload URL. Temporary Upload ID: {temp_upload_id}")

except requests.exceptions.RequestException as e:
    print(f"Error requesting upload URL: {e}")
    if e.response is not None: print(f"Response: {e.response.text}")
    presigned_url, temp_upload_id, s3_key = None, None, None
except (ValueError, json.JSONDecodeError) as e:
     print(f"Error processing API response: {e}")
     presigned_url, temp_upload_id, s3_key = None, None, None

​
Step 2: Upload File to Pre-signed URL

Use the presigned_url obtained in Step 1 to PUT your file data. Note: Do not include your x-api-key header in this request; authentication is handled by the pre-signed URL itself. The Content-Type header must match the one you specified when requesting the URL. 
if presigned_url:
    print(f"Uploading {file_name} to S3...")
    try:
        with open(file_path, 'rb') as f:
            upload_response = requests.put(
                presigned_url,
                data=f,
                headers={'Content-Type': content_type}
            )
            upload_response.raise_for_status()
        print("File successfully uploaded to S3.")
        upload_succeeded = True
    except FileNotFoundError:
        print(f"Error: Local file not found at {file_path}")
        upload_succeeded = False
    except requests.exceptions.RequestException as e:
        print(f"Error uploading file to S3: {e}")
        if e.response is not None: print(f"Response: {e.response.text}")
        upload_succeeded = False
else:
    print("Skipping file upload due to previous error.")
    upload_succeeded = False

​
Step 3: Confirm Upload Completion

Notify the Plexe API that the file upload to the pre-signed URL is complete using the temporary upload_id and s3_key. 
upload_id = None # Final ID will be set here
if upload_succeeded and temp_upload_id and s3_key:
    print("Confirming upload status with Plexe API...")
    try:
        confirm_response = requests.post(
            f"{base_url}/uploads/status",
            headers=headers,
            json={
                "upload_id": temp_upload_id,
                "filename": file_name,
                "s3_key": s3_key
            }
        )
        confirm_response.raise_for_status()
        upload_status = confirm_response.json()
        final_upload_id = upload_status.get("upload_id")
        final_status = upload_status.get("status")

        if final_status == "complete" and final_upload_id:
            upload_id = final_upload_id # Store the final ID for use in model building
            print(f"Upload confirmed successfully! Final Upload ID: {upload_id}")
        else:
            print(f"Upload confirmation failed or status not complete: {upload_status}")

    except requests.exceptions.RequestException as e:
        print(f"Error confirming upload: {e}")
        if e.response is not None: print(f"Response: {e.response.text}")
    except json.JSONDecodeError as e:
         print(f"Error processing confirmation response: {e}")

else:
     print("Skipping upload confirmation due to previous error.")


if upload_id:
    print(f"\nData upload process complete. Use Upload ID '{upload_id}' when building models.")
else:
    print("\nData upload process failed or was skipped.")
You can now use the final upload_id when submitting model build requests that require this dataset. For example: 
# Example of how to use the upload_id in a model build request
if upload_id:
    model_build_data = {
        "upload_id": upload_id,  # Use the upload_id returned from the upload process
        "goal": "Predict customer churn based on usage patterns",  # Natural language description of your model's purpose
        "metric": "f1_score"  # The metric to optimize for
    }
    
    try:
        model_name = "customer_churn_model"
        model_build_response = requests.post(
            f"{base_url}/models/{model_name}",
            headers=headers,
            json=model_build_data
        )
        model_build_response.raise_for_status()
        build_result = model_build_response.json()
        print(f"Model build initiated successfully: {build_result}")
    except requests.exceptions.RequestException as e:
        print(f"Error initiating model build: {e}")
        if e.response is not None: print(f"Response: {e.response.text}")
You can upload multiple files and reference them by their respective upload_ids for different model building tasks.