Uploaded app.py file

app.py

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+import os
+import random
+import sys
+from typing import Sequence, Mapping, Any, Union, Tuple
+import torch
+from PIL import Image
+import spaces
+import gradio as gr
+from huggingface_hub import hf_hub_download
+from comfy import model_management
+
+# Download required models from huggingface
+hf_token = os.environ.get("HF_TOKEN")
+hf_hub_download(
+    repo_id="Comfy-Org/stable-diffusion-v1-5-archive",
+    filename="v1-5-pruned-emaonly-fp16.safetensors",
+    local_dir="models/checkpoints",
+    token=hf_token,
+)
+
+
+def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
+    try:
+        return obj[index]
+    except KeyError:
+        return obj["result"][index]
+
+
+def find_path(name: str, path: str = None) -> str:
+    """
+    Recursively looks at parent folders starting from the given path until it finds the given name.
+    Returns the path as a Path object if found, or None otherwise.
+    """
+    # If no path is given, use the current working directory
+    if path is None:
+        path = os.getcwd()
+
+    # Check if the current directory contains the name
+    if name in os.listdir(path):
+        path_name = os.path.join(path, name)
+        print(f"{name} found: {path_name}")
+        return path_name
+
+    # Get the parent directory
+    parent_directory = os.path.dirname(path)
+
+    # If the parent directory is the same as the current directory, we've reached the root and stop the search
+    if parent_directory == path:
+        return None
+
+    # Recursively call the function with the parent directory
+    return find_path(name, parent_directory)
+
+
+def add_comfyui_directory_to_sys_path() -> None:
+    """
+    Add 'ComfyUI' to the sys.path
+    """
+    comfyui_path = find_path("ComfyUI")
+    if comfyui_path is not None and os.path.isdir(comfyui_path):
+        sys.path.append(comfyui_path)
+        print(f"'{comfyui_path}' added to sys.path")
+
+
+def add_extra_model_paths() -> None:
+    try:
+        from main import load_extra_path_config
+    except ImportError:
+        print(
+            "Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead."
+        )
+        from utils.extra_config import load_extra_path_config
+
+    extra_model_paths = find_path("extra_model_paths.yaml")
+
+    if extra_model_paths is not None:
+        load_extra_path_config(extra_model_paths)
+    else:
+        print("Could not find the extra_model_paths config file.")
+
+
+add_comfyui_directory_to_sys_path()
+add_extra_model_paths()
+
+
+def import_custom_nodes() -> None:
+    import asyncio
+    import execution
+    from nodes import init_extra_nodes
+    import server
+
+    # Creating a new event loop and setting it as the default loop
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+
+    # Creating an instance of PromptServer with the loop
+    server_instance = server.PromptServer(loop)
+    execution.PromptQueue(server_instance)
+
+    # Initializing custom nodes
+    init_extra_nodes()
+
+
+from nodes import NODE_CLASS_MAPPINGS
+
+import_custom_nodes()
+
+
+checkpointloadersimple = NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"]()
+cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
+vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
+ksampler = NODE_CLASS_MAPPINGS["KSampler"]()
+vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
+framercomfysaveimagenode = NODE_CLASS_MAPPINGS["FramerComfySaveImageNode"]()
+
+
+checkpointloadersimple_14 = checkpointloadersimple.load_checkpoint(
+    ckpt_name="v1-5-pruned-emaonly-fp16.safetensors"
+)
+
+
+model_loaders = [checkpointloadersimple_14]
+
+model_management.load_models_gpu(
+    [
+        loader[0].patcher if hasattr(loader[0], "patcher") else loader[0]
+        for loader in model_loaders
+    ]
+)
+
+
+@spaces.GPU
+def run_workflow(prompt, negative_prompt, image_input) -> Tuple[Any, ...]:
+    with torch.inference_mode():
+        cliptextencode_6 = cliptextencode.encode(
+            text=prompt, clip=get_value_at_index(checkpointloadersimple_14, 1)
+        )
+
+        cliptextencode_7 = cliptextencode.encode(
+            text=negative_prompt, clip=get_value_at_index(checkpointloadersimple_14, 1)
+        )
+
+        vaeencode_12 = vaeencode.encode(
+            pixels=image_input, vae=get_value_at_index(checkpointloadersimple_14, 2)
+        )
+
+        ksampler_3 = ksampler.sample(
+            seed=random.randint(1, 2**64),
+            steps=20,
+            cfg=8,
+            sampler_name="dpmpp_2m",
+            scheduler="normal",
+            denoise=0.8700000000000001,
+            model=get_value_at_index(checkpointloadersimple_14, 0),
+            positive=get_value_at_index(cliptextencode_6, 0),
+            negative=get_value_at_index(cliptextencode_7, 0),
+            latent_image=get_value_at_index(vaeencode_12, 0),
+        )
+
+        vaedecode_8 = vaedecode.decode(
+            samples=get_value_at_index(ksampler_3, 0),
+            vae=get_value_at_index(checkpointloadersimple_14, 2),
+        )
+
+        framercomfysaveimagenode_18 = framercomfysaveimagenode.save_images(
+            filename_prefix="ComfyUI",
+            output_name="result_image",
+            images=get_value_at_index(vaedecode_8, 0),
+        )
+
+    framercomfysaveimagenode_18_path = (
+        "output/" + framercomfysaveimagenode_18["ui"]["images"][0]["filename"]
+    )
+    return framercomfysaveimagenode_18_path
+
+
+# Create Gradio interface
+image18_output = gr.Image(label="Generated Image18")
+
+with gr.Blocks() as app:
+    with gr.Row():
+        with gr.Column():
+            prompt_input = gr.Textbox(
+                label="Prompt",
+                value="None" if "None" else None,
+                placeholder=f"Enter prompt here...",
+            )
+            negative_prompt_input = gr.Textbox(
+                label="Negative_Prompt",
+                value="None" if "None" else None,
+                placeholder=f"Enter negative_prompt here...",
+            )
+            generate_btn = gr.Button("Generate")
+        with gr.Column():
+            image18_output.render()
+    generate_btn.click(
+        fn=run_workflow,
+        inputs=[prompt_input, negative_prompt_input],
+        outputs=[image18_output],
+    )
+
+if __name__ == "__main__":
+    app.launch(share=True)