init

__init__.py

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

keys/nokey.txt

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+00000000-00000-0000-0000-000000000000:00000000000000000000000000000000

nodes.py

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+import fal_client
+import torch
+import requests
+import numpy as np
+from PIL import Image
+import io
+import os
+
+class FluxAPI:
+    @classmethod
+    def INPUT_TYPES(cls):
+        current_dir = os.path.dirname(os.path.abspath(__file__))
+        api_keys = [f for f in os.listdir(os.path.join(current_dir, "keys")) if f.endswith('.txt')]
+        return {
+            "required": {
+                "prompt": ("STRING", {"multiline": True}),
+                "endpoint": (["schnell (4+ steps)", "dev (25 steps)"],),
+                "resolution": (["1024x1024 (1:1)", "512x512 (1:1)", "768x1024 (4:3)", "576x1024 (9:16)", "1024x720 (3:4)", "1024x576 (16:9)"],),
+                "steps": ("INT", {"default": 4, "min": 1, "max": 50}),
+                "enable_safety_checker": ("BOOLEAN", {"default": False}),
+                "api_key": (api_keys,),
+                "seed": ("INT", {"default": 1337, "min": 1, "max": 16777215})
+            },
+        }
+    
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "generate_image"
+    CATEGORY = "FalAPI"
+
+    def generate_image(self, prompt, endpoint, resolution, steps, enable_safety_checker, api_key, seed,):
+        #set endpoint
+        if endpoint == "schnell (4+ steps)":
+            endpoint = "fal-ai/flux/schnell"
+        else:
+            endpoint = "fal-ai/flux/dev"
+        #convert dimensions
+        AR = {
+        "1024x1024 (1:1)": "square_hd",
+        "512x512 (1:1)": "square",
+        "768x1024 (4:3)": "portrait_4_3",
+        "576x1024 (9:16)": "portrait_16_9",
+        "1024x720 (3:4)": "landscape_4_3",
+        "1024x576 (16:9)": "landscape_16_9",
+        }
+        image_size = AR.get(resolution)
+        #Set api key
+        current_dir = os.path.dirname(os.path.abspath(__file__))
+        with open(os.path.join(os.path.join(current_dir, "keys"), api_key), 'r', encoding='utf-8') as file:
+            key = file.read()
+        os.environ["FAL_KEY"] = key
+        handler = fal_client.submit(
+        endpoint,
+        arguments={
+            "prompt": prompt,
+            "seed": seed,
+            "image_size": image_size,
+            "num_inference_steps": steps,
+            "num_images": 1,  #Hardcoded to 1 for now
+            "enable_safety_checker": enable_safety_checker},
+        )
+        result = handler.get()
+        image_url = result['images'][0]['url']
+        #Download the image
+        response = requests.get(image_url)
+        image = Image.open(io.BytesIO(response.content))
+        #make image more comfy
+        image = np.array(image).astype(np.float32) / 255.0
+        output_image = torch.from_numpy(image)[None,]
+        return (output_image,)
+
+NODE_CLASS_MAPPINGS = {
+    "FluxAPI": FluxAPI,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "FluxAPI": "FluxAPI",
+}

requirements.txt

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+fal-client
+requests
+numpy