Upload Data via API

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
}

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

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

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.")

# 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}")