import gradio as gr
import requests

def generate_image(prompt):
  apiUrl = 'https://apiv2.makeai.run/v2/txt2img' # Replace with your API URL
  data = {
    "mode": "url",
    "model": "AOM3A1B_orangemixs.safetensors",
    "tiling": false,
    "batch_size": 1,
    "prompt": prompt,
    "negative_prompt": "worst quality, lowres",
    "seed": 1234,
    "scheduler": "Euler a",
    "n_iter": 1,
    "steps": 30,
    "cfg": 11.0,
    "offset_noise": 0.0,
    "width": 1024,
    "height": 1024,
    "clip_skip": 1,
    "loras": [
      {
        "name": "",
        "strength": 1.0
      }
    ],
    "embeddings": [
      {
        "name": "",
        "strength": 1.0
      }
    ],
    "vae": "vae-ft-mse-840000-ema-pruned.ckpt",
    "restore_faces": false,
    "fr_model": "CodeFormer",
    "codeformer_weight": 0.5,
    "enable_hr": false,
    "denoising_strength": 0.75,
    "hr_scale": 2,
    "hr_upscale": "None",
    "img2img_ref_img_type": "piece",
    "img2img_resize_mode": 0,
    "img2img_denoising_strength": 0.75,
    "controlnet_enabled": false,
    "controlnet_ref_img_type": "piece",
    "controlnet_guessmode": false,
    "controlnet_module": "canny",
    "controlnet_model": "control_v11p_sd15_softedge",
    "controlnet_weight": 1,
    "controlnet_guidance_start": 0,
    "controlnet_guidance_end": 1,
    "controlnet_ref_img_url": "",
    # Replace with your control image URL if needed
    # https://upload.wikimedia.org/wikipedia/commons/d/d1/Image_not_available.png
    # is used by default
    # otherwise leave it blank
    # or use the control image component below
    # to upload an image from the interface
    # and pass it as an argument to the function
    # along with the prompt
    # and set it as the value of this key
    # in the data object
    # before making the API call
    # (see commented code below)
    
  
    
    
    
    
    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    
    
    
    
    


    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    
    


    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
    
    




    
    
  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  

  
    
  
  





  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
    
  
  





  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  





  
  

"controlnet_mask": [],
    "controlnet_resize_mode": "Scale to Fit (Inner Fit)",
    "controlnet_lowvram": false,
    "controlnet_processor_res": 512,
    "controlnet_threshold_a": 100,
    "controlnet_threshold_b": 200
  }
  headers = {
    'Content-Type': 'application/json',
    'token': '514f7ecde6a5434dbab5c6579311ad82' # Replace with your API token
  }
  response = requests.post(apiUrl, json=data, headers=headers)
  responseData = response.json()
  if responseData and responseData['results'] and responseData['results'][0]:
    return responseData['results'][0]
  else:
    return "No image generated"

# Uncomment the following lines if you want to use the control image component
# def generate_image(prompt, control_image):
#   apiUrl = 'https://apiv2.makeai.run/v2/txt2img' # Replace with your API URL
#   data = {
#     ...
#     "controlnet_ref_img_url": control_image,
#     ...
#   }
#   headers = {
#     ...
#   }
#   response = requests.post(apiUrl, json=data, headers=headers)
#   responseData = response.json()
#   if responseData and responseData['results'] and responseData['results'][0]:
#     return responseData['results'][0]
#   else:
#     return "No image generated"

title = gr.outputs.Textbox(label="Freedom Demonstration")
prompt = gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here", label="Prompt")
image = gr.outputs.Image(label="Generated Image")

# Uncomment the following line if you want to use the control image component
# control_image = gr.inputs.Image(label="Control Image (optional)")

iface = gr.Interface(
  fn=generate_image,
  inputs=[prompt], # Add control_image to the list if you want to use it
  outputs=[title, image],
  title="Freedom Demonstration",
  description="This is a Gradio app that uses an API to generate images based on text prompts.",
  live=False,
  layout="vertical"
)

iface.launch()