import pycomfyapi

# Create a node and configure it
sampler = pycomfyapi.create_node("KSampler")
sampler.name = "My Sampler"
sampler.set("steps", 25)
sampler.set("cfg", 7.0)

# Inspect it
print(sampler.type, sampler.id)
print([p.name for p in sampler.inputs])

# Queue the workflow
pycomfyapi.queue()

import pycomfyapi

pycomfyapi.clear()

ckpt = pycomfyapi.create_node("CheckpointLoaderSimple")
ckpt.set("ckpt_name", "dreamshaper_8.safetensors")

pos = pycomfyapi.create_node("CLIPTextEncode")
pos.set("text", "a photo of an astronaut riding a horse")

neg = pycomfyapi.create_node("CLIPTextEncode")
neg.set("text", "blurry, low quality")

latent = pycomfyapi.create_node("EmptyLatentImage")
latent.set("width", 512)
latent.set("height", 512)

sampler = pycomfyapi.create_node("KSampler")
sampler.set("steps", 25)

vae = pycomfyapi.create_node("VAEDecode")
save = pycomfyapi.create_node("SaveImage")

# Connect the pipeline
sampler.input("model").connect_to(ckpt.output("MODEL"))
pos.input("clip").connect_to(ckpt.output("CLIP"))
neg.input("clip").connect_to(ckpt.output("CLIP"))
sampler.input("positive").connect_to(pos.output("CONDITIONING"))
sampler.input("negative").connect_to(neg.output("CONDITIONING"))
sampler.input("latent_image").connect_to(latent.output("LATENT"))
vae.input("samples").connect_to(sampler.output("LATENT"))
vae.input("vae").connect_to(ckpt.output("VAE"))
save.input("images").connect_to(vae.output("IMAGE"))

pycomfyapi.queue()

import pycomfyapi

pycomfyapi.set_server(port=8188)

sampler = pycomfyapi.create_node("KSampler")
# ... build your graph ...
pycomfyapi.queue(wait=True)
pycomfyapi.save_graph_to_file("output.json")

import pycomfyapi

session = pycomfyapi.get_session()

sampler = session.create_node("KSampler")
sampler.set("steps", 30)

clip = session.create_node("CLIPTextEncode")
clip.set("text", "a sunset over mountains")

clip.output("CONDITIONING").connect_to(sampler.input("positive"))

session.queue(wait=True)
session.save_graph_to_file("my_workflow.json")

import pycomfyapi

@pycomfyapi.app(
    name="Quick Upscale",
    params={"upscale_model": str, "save_prefix": str},
    description="Upscale the output of the current workflow.",
)
def quick_upscale(upscale_model="RealESRGAN_x4plus.pth", save_prefix="upscaled"):
    loader = pycomfyapi.create_node("UpscaleModelLoader")
    loader.set("model_name", upscale_model)
    # ... build the rest of the pipeline ...
    pycomfyapi.queue(wait=True)

# Or run it programmatically
pycomfyapi.run_app("Quick Upscale", save_prefix="my_output")

import pycomfyapi

# Nodes
pycomfyapi.create_node(class_type, **defaults) -> Node
pycomfyapi.delete_node(node_or_id)
pycomfyapi.get_node_by_id(node_id) -> Node
pycomfyapi.get_node_by_name(name) -> Node
pycomfyapi.get_nodes() -> list[Node]
pycomfyapi.clone_node(node_or_id) -> Node
pycomfyapi.clear()

# Connections
pycomfyapi.connect(output_slot, input_slot)

# Selection
pycomfyapi.select(node_or_ids)
pycomfyapi.deselect(node_or_ids)
pycomfyapi.select_all()
pycomfyapi.get_selected_nodes() -> list[Node]

# Clipboard
pycomfyapi.copy_nodes(ids)
pycomfyapi.cut_nodes(ids)
pycomfyapi.paste_nodes()

# Execution
pycomfyapi.queue(wait=False)
pycomfyapi.interrupt()

# Graph I/O
pycomfyapi.get_graph() -> dict
pycomfyapi.set_graph(json_data)
pycomfyapi.load_graph_from_file(filepath)
pycomfyapi.save_graph_to_file(filepath)

# Workflows
pycomfyapi.create_workflow(name) -> Workflow
pycomfyapi.get_workflows() -> list[Workflow]
pycomfyapi.get_active_workflow() -> Workflow
pycomfyapi.set_active_workflow(workflow_or_name)
pycomfyapi.save_workflow(workflow)
pycomfyapi.save_workflow_as(name, workflow)
pycomfyapi.close_workflow(workflow_id)

# Subgraphs
pycomfyapi.create_subgraph(name, nodes) -> Subgraph
pycomfyapi.get_subgraphs() -> list[Subgraph]
pycomfyapi.open_subgraph(subgraph)

# Groups
pycomfyapi.create_group(name, x, y, width, height) -> Group
pycomfyapi.get_groups() -> list[Group]

# Node info
pycomfyapi.node_types() -> list[str]
pycomfyapi.node_info(class_type) -> dict

# Server
pycomfyapi.set_server(host, port)

node.id             # int — ComfyUI node ID
node.type           # str — node class type
node.name           # str — display title (read/write)
node.x, node.y      # float — canvas position
node.color          # str — node color
node.inputs         # list[Slot]
node.outputs        # list[Slot]
node.widget_names   # list[str]

node.get(widget)    # get a widget value
node.set(widget, v) # set a widget value
node.move(x, y)     # reposition on canvas
node.input(name)    # get input slot by name
node.output(name)   # get output slot by name