Please add a minimal python script for accessing your API

[RomanPlusPlus]

Sorry if it's not the right place for this suggestion.

The problem: your API documentation is missing a minimal python script. Something you just run and it works, without installing third-party software etc.

After some experimentation, I've managed to write it myself. Please feel free to add it to the docs (I release it into Public Domain).

import requests
import time
import json
import os

# API endpoint URLs
BASE_URL = "https://api.bfl.ml" 
GENERATE_URL = f"{BASE_URL}/v1/flux-pro-1.1"
RESULT_URL = f"{BASE_URL}/v1/get_result"

# Your API key
API_KEY = "your_key"  # Replace with your actual API key

prompt = "A beautiful landscape with mountains and a lake."


# Headers for authentication
headers = {
    "x-key": API_KEY,
    "Content-Type": "application/json"
}

# Image generation parameters
payload = {
    "prompt": prompt,
    "width": 1024,
    "height": 768,
    "prompt_upsampling": True,
    "safety_tolerance": 2
}

def generate_image():
    # Submit the image generation request
    response = requests.post(GENERATE_URL, json=payload, headers=headers)
    response.raise_for_status()
    task_id = response.json()["id"]
    print(f"Image generation task submitted. Task ID: {task_id}")
    return task_id

def check_result(task_id):
    while True:
        response = requests.get(f"{RESULT_URL}?id={task_id}", headers=headers)
        response.raise_for_status()
        result = response.json()
        
        if result["status"] == "Ready":
            print("Image generation completed!")
            return result["result"]
        elif result["status"] in ["Request Moderated", "Content Moderated", "Error"]:
            print(f"Task failed. Status: {result['status']}")
            return None
        else:
            print(f"Status: {result['status']}. Waiting...")
            time.sleep(5)  # Wait for 5 seconds before checking again

def process_result(result):
    if result is None:
        print("No result to process.")
        return

    print("Result structure:")
    print(json.dumps(result, indent=2))

    if "sample" in result:
        result_img_url = result['sample']
        print(f"Generated image URL: {result_img_url}")
        print(f"Prompt used: {result['prompt']}")
    else:
        print("Image URL not found in the result. Please check the result structure.")
    return result_img_url

def download_image(url):
    response = requests.get(url)
    response.raise_for_status()
    
    filename = f"generated_image_{int(time.time())}.png"

    with open(filename, "wb") as file:
        file.write(response.content)
    
    print(f"Image downloaded successfully as {filename}")
    return filename

def main():
    task_id = generate_image()
    result = check_result(task_id)
    result_img_url = process_result(result)
    
    if result_img_url:
        download_image(result_img_url)

if __name__ == "__main__":
    main()

[emyasnikov]

I had similar Python script for the finetuning task to simplify the process for my needs:

import requests
import base64
import json

API_KEY = ""
CAPTIONING = True
FINETUNE_COMMENT = ""
FINETUNE_TYPE = "lora" # full, lora
ITERATIONS = 150
LORA_RANK = 16 # 16 (lora), 32 (full)
LEARNING_RATE = 0.0001 # 0.0001 (lora), 0.00001 (full)
MODE = "general" # character, general, product, style
PRIORITY = "quality" # high_res_only, quality, speed
TRIGGER_WORD = ""
WEBHOOK_URL = "" # @see https://console.hookdeck.com/
WEBHOOK_SECRET = ""
ZIP_FILE_PATH = ""

def encode_zip_file(file_path):
    with open(file_path, "rb") as f:
        file_bytes = f.read()
    return base64.b64encode(file_bytes).decode('utf-8')

def main():
    zip_file_path = ZIP_FILE_PATH
    encoded_file = encode_zip_file(zip_file_path)

    url = "https://api.us1.bfl.ai/v1/finetune"
    headers = {
        "Content-Type": "application/json",
        "X-Key": API_KEY
    }
    payload = {
        "file_data": encoded_file,
        "finetune_comment": FINETUNE_COMMENT,
        "trigger_word": TRIGGER_WORD,
        "mode": MODE,
        "iterations": ITERATIONS,
        "learning_rate": LEARNING_RATE,
        "captioning": CAPTIONING,
        "priority": PRIORITY,
        "finetune_type": FINETUNE_TYPE,
        "lora_rank": LORA_RANK,
        "webhook_url": WEBHOOK_URL,
        "webhook_secret": WEBHOOK_SECRET,
    }

    response = requests.post(url, headers=headers, json=payload)

    if response.status_code == 200:
        print("Successful Response:")
        print(response.json())
    else:
        print(f"Error {response.status_code}:")
        try:
            print(response.json())
        except json.decoder.JSONDecodeError:
            print(response.text)

if __name__ == "__main__":
    main()