init

.gitignore

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+venv/
+.env

app.py

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+import gradio as gr
+import asyncio
+import fal_client
+from dotenv import load_dotenv
+import os
+from pathlib import Path
+import time
+
+load_dotenv()
+os.environ["FAL_KEY"] = os.getenv("FAL_API_KEY")
+
+async def generate_paris_images(image1_path: str, image2_path: str, woman_prompt: str, man_prompt: str, batch_size: int, progress=gr.Progress()):
+    start_time = time.time()
+    print("Progress: 5% - Starting Paris image generation...")
+    progress(0.05, desc="Starting Paris image generation...")
+    
+    # Upload all images in parallel
+    upload_tasks = [
+        fal_client.upload_file_async(str(image1_path)),
+        fal_client.upload_file_async(str(image2_path)),
+        fal_client.upload_file_async("test_images/woman.png"),
+        fal_client.upload_file_async("test_images/man.png"),
+        fal_client.upload_file_async("test_images/clipspace-mask-4736783.png"),
+        fal_client.upload_file_async("test_images/clipspace-mask-4722992.png")
+    ]
+    
+    [image1_url, image2_url, woman_img, man_img, mask1_img, mask2_img] = await asyncio.gather(*upload_tasks)
+    
+    print("Progress: 40% - Uploaded all images")
+    progress(0.4, desc="Uploaded all images")
+
+    handler = await fal_client.submit_async(
+        "comfy/LVE/paris-couple",
+        arguments={
+            "loadimage_1": image1_url,
+            "loadimage_2": image2_url,
+            "loadimage_3": woman_img,
+            "loadimage_4": mask1_img,
+            "loadimage_5": mask2_img,
+            "loadimage_6": man_img,
+            "woman_prompt": woman_prompt,
+            "man_prompt": man_prompt,
+            "batch_size": batch_size
+        }
+    )
+
+    print("Progress: 60% - Processing images...")
+    progress(0.6, desc="Processing images...")
+    
+    result = await handler.get()
+    print(result)
+
+    end_time = time.time()
+    processing_time = end_time - start_time
+    print(f"Progress: 100% - Generation completed in {processing_time:.2f} seconds")
+    progress(1.0, desc=f"Generation completed in {processing_time:.2f} seconds")
+    
+    # Return all generated image URLs and processing time
+    # Get the first key from outputs dynamically
+    return (
+        [img["url"] for img in result["outputs"][next(iter(result["outputs"]))]["images"]] if "outputs" in result and result["outputs"] else [],
+        f"Processing time: {processing_time:.2f} seconds"
+    )
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        image1_input = gr.Image(label="Upload Woman Image", type="filepath", value="test_images/user3-f.jpg")
+        image2_input = gr.Image(label="Upload Man Image", type="filepath", value="test_images/user3.jpg")
+    
+    with gr.Row():
+        woman_prompt = gr.Textbox(
+            label="Woman Prompt",
+            value="Close-up, portrait photo, a woman, Paris nighttime romance scene, wearing an elegant black dress with a shawl, standing beneath the same canopy of twinkling lights along the Champs-Élysées, the Eiffel Tower glowing bright in the distance, soft mist rising from the street, looking at the camera."
+        )
+        man_prompt = gr.Textbox(
+            label="Man Prompt",
+            value="Close-up, portrait photo, a man, Paris nighttime romance scene, wearing a tailored suit with a crisp white shirt, standing beneath a canopy of twinkling lights along the Champs-Élysées, the Eiffel Tower glowing bright in the distance, soft mist rising from the street, looking at the camera."
+        )
+    
+    batch_size = gr.Slider(minimum=1, maximum=8, value=4, step=1, label="Batch Size")
+    
+    generate_btn = gr.Button("Generate")
+    image_output = gr.Gallery(label="Generated Image")
+    time_output = gr.Textbox(label="Processing Time")
+    
+    generate_btn.click(
+        fn=generate_paris_images,
+        inputs=[image1_input, image2_input, woman_prompt, man_prompt, batch_size],
+        outputs=[image_output, time_output]
+    )
+
+if __name__ == "__main__":
+    print("Starting Gradio interface...")
+    demo.launch()

fal_test.py

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+import asyncio
+import fal_client
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+os.environ["FAL_KEY"] = os.getenv("FAL_API_KEY")
+
+async def subscribe():
+    handler = await fal_client.submit_async(
+        "comfy/LVE/fal-favourite",
+        arguments={
+            "loadimage_1": "https://v3.fal.media/files/tiger/jn66x0N2Xu_zxX8_GKXP7_A4%20-%202.png",
+            "loadimage_2": "https://fal.media/files/elephant/UX-Etn4FZUSbUqxLKihR1.png",
+            "loadimage_3": "https://fal.media/files/lion/CjubwDK_JC9TSy6E_Ck2O.png",
+            "loadimage_4": "https://fal.media/files/koala/4-4xrKSOZFxInqt0r-clj.png",
+            "loadimage_5": "https://fal.media/files/koala/xz9aEtyqSb9jhLIgvZfdr.png",
+            "loadimage_6": "https://fal.media/files/monkey/6703hkTCUCzXo7d43E4mQ.png",
+            "loadimage_7": "https://fal.media/files/zebra/c3lO_fvrSreL3ebz2xfFA.png",
+            "loadimage_8": "https://fal.media/files/lion/UgFgxIjafvBFlu78Pj8ZP.png",
+            "loadimage_9": "https://fal.media/files/monkey/UQqjW4UU1-FJLiTd8l_QH.png",
+            "loadimage_10": "https://fal.media/files/monkey/mGciMw0tNFVyLKEUrapWO.png",
+            "title": "our favourite things",
+            "text_1-1": "cat",
+            "text_1-2": "motorcycle",
+            "text_1-3": "cocktail",
+            "text_2-1": "book",
+            "text_2-2": "money",
+            "text_2-3": "mountain",
+            "text_3-1": "computer",
+            "text_3-2": "console",
+            "text_3-3": "rose",
+            "couple_name": "ELLS & MILLS"
+        },
+    )
+
+    async for event in handler.iter_events(with_logs=True):
+        print(event)
+
+    result = await handler.get()
+
+    print(result)
+
+
+if __name__ == "__main__":
+    asyncio.run(subscribe())

img2img.py

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+import asyncio
+import fal_client
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+os.environ["FAL_KEY"] = os.getenv("FAL_API_KEY")
+
+async def subscribe():
+    handler = await fal_client.submit_async(
+        "comfy/fal-ai/image-to-image",
+        arguments={
+            "loadimage_1": "https://fal.media/files/elephant/UX-Etn4FZUSbUqxLKihR1.png",
+            "prompt": "photograph of cat"
+        },
+    )
+
+    async for event in handler.iter_events(with_logs=True):
+        print(event)
+
+    result = await handler.get()
+
+    print(result)
+
+
+if __name__ == "__main__":
+    asyncio.run(subscribe())

requirements.txt

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+fal-client
+python-dotenv
+gradio

schnell_test.py

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+import asyncio
+import fal_client
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+os.environ["FAL_KEY"] = os.getenv("FAL_API_KEY")
+
+async def subscribe(keyword: str):
+    handler = await fal_client.submit_async(
+        "fal-ai/flux/schnell",
+        arguments={
+            "prompt": f"{keyword}, illustration style, white background, centered layout",
+            "image_size": "square_hd"
+        },
+    )
+
+    async for event in handler.iter_events(with_logs=True):
+        print(event)
+
+    result = await handler.get()
+
+    print(result["images"][0]["url"])
+
+if __name__ == "__main__":
+    asyncio.run(subscribe("dog"))

upload_test.py

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+from dotenv import load_dotenv
+import fal_client
+import os
+
+# Load environment variables from .env file
+load_dotenv()
+
+# The key in your .env file is FAL_API_KEY but fal_client expects FAL_KEY
+os.environ["FAL_KEY"] = os.getenv("FAL_API_KEY")
+
+url = fal_client.upload_file("A4 - 2.png")
+print(url)