first commit

__init__.py

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+from .onethingai import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+
+__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] 

onethingai.py

@@ -0,0 +1,122 @@
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+import json
+from PIL import Image
+import io
+import base64
+import numpy as np
+import torch
+
+class OneThingAILoader:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "api_key": ("STRING", {"default": "", "multiline": False}),
+                "prompt": ("STRING", {"default": "", "multiline": True}),
+                "model": ("STRING", {"default": "gpt4o"}),
+                "num_images": ("INT", {"default": 1, "min": 1, "max": 10}),
+                "width": ("INT", {"default": 1024, "min": 512, "max": 2048, "step": 64}),
+                "height": ("INT", {"default": 1024, "min": 512, "max": 2048, "step": 64}),
+                "retries": ("INT", {"default": 3, "min": 0, "max": 5}),
+                "timeout": ("INT", {"default": 20, "min": 5, "max": 100}),
+            },
+        }
+    
+    RETURN_TYPES = ("IMAGE", )
+    FUNCTION = "generate"
+    CATEGORY = "image generation"
+
+    def generate(self, api_key, prompt, model="gpt4o", num_images=1, width=1024, height=1024, retries=3, timeout=8):
+        # API endpoint
+        url = "https://api-model.onethingai.com/v1/images/generations"
+        
+        # Setup retry strategy
+        retry_strategy = Retry(
+            total=retries,
+            backoff_factor=1,
+            status_forcelist=[429, 500, 502, 503, 504],
+        )
+        
+        # Create session with retry strategy
+        session = requests.Session()
+        adapter = HTTPAdapter(max_retries=retry_strategy)
+        session.mount("https://", adapter)
+        
+        # Request headers
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+        
+        # Request payload
+        payload = {
+            "model": model,
+            "prompt": prompt,
+            "n": num_images,
+            "size": f"{width}x{height}",
+        }
+            
+        try:
+            # Make API request with timeout
+            response = session.post(
+                url, 
+                headers=headers, 
+                json=payload,
+                timeout=timeout
+            )
+            response.raise_for_status()
+            
+            # Parse response
+            result = response.json()
+            
+            if "data" not in result:
+                raise ValueError(f"Unexpected API response: {result}")
+            
+            # Process images
+            images = []
+            for img_data in result["data"]:
+                if "b64_json" in img_data:
+                    # Decode base64 image
+                    image_bytes = base64.b64decode(img_data["b64_json"])
+                    image = Image.open(io.BytesIO(image_bytes))
+                    
+                    # Convert to RGB if necessary
+                    if image.mode != "RGB":
+                        image = image.convert("RGB")
+
+                    # Convert to numpy array
+                    image_array = np.array(image)
+                    images.append(image_array)
+                    
+            # Stack images if multiple were generated
+            if len(images) > 1:
+                final_image = np.stack(images)
+            else:
+                final_image = images[0]
+            
+            # Convert numpy array to torch tensor
+            final_image = torch.from_numpy(final_image).float()/255.0
+            final_image = final_image.unsqueeze(0)
+            
+            return (final_image,)
+            
+        except requests.exceptions.RequestException as e:
+            raise RuntimeError(f"API request failed: {str(e)}")
+        except json.JSONDecodeError:
+            raise RuntimeError("Failed to parse API response")
+        except Exception as e:
+            raise RuntimeError(f"Error generating images: {str(e)}")
+        finally:
+            session.close()
+
+# Register the node class
+NODE_CLASS_MAPPINGS = {
+    "OneThingAILoader": OneThingAILoader
+}
+
+# Add descriptions
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "OneThingAILoader": "OneThingAI Image Generator"
+}