Create app.py

app.py

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+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)
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+"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()