├── .gitignore ├── requirements.txt ├── pyproject.toml ├── .github └── workflows │ └── publish.yml ├── __init__.py ├── README.md ├── utils.py ├── nodes.py └── LICENSE /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__/ 2 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | python-dotenv 2 | argon2-cffi 3 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "comfyui_naidgenerator" 3 | description = "This extension helps generate images through NAI." 4 | version = "1.0.9" 5 | license = { file = "LICENSE" } 6 | dependencies = ["python-dotenv", "argon2-cffi"] 7 | 8 | [project.urls] 9 | Repository = "https://github.com/bedovyy/ComfyUI_NAIDGenerator" 10 | # Used by Comfy Registry https://comfyregistry.org 11 | 12 | [tool.comfy] 13 | PublisherId = "bedovyy" 14 | DisplayName = "ComfyUI_NAIDGenerator" 15 | Icon = "" 16 | -------------------------------------------------------------------------------- /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to Comfy registry 2 | on: 3 | workflow_dispatch: 4 | push: 5 | branches: 6 | - main 7 | - master 8 | paths: 9 | - "pyproject.toml" 10 | 11 | permissions: 12 | issues: write 13 | 14 | jobs: 15 | publish-node: 16 | name: Publish Custom Node to registry 17 | runs-on: ubuntu-latest 18 | if: ${{ github.repository_owner == 'bedovyy' }} 19 | steps: 20 | - name: Check out code 21 | uses: actions/checkout@v4 22 | - name: Publish Custom Node 23 | uses: Comfy-Org/publish-node-action@main 24 | with: 25 | ## Add your own personal access token to your Github Repository secrets and reference it here. 26 | personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} 27 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import subprocess 3 | import importlib 4 | 5 | def ensure_package(package, install_package_name=None): 6 | # Try to import the package 7 | try: 8 | importlib.import_module(package) 9 | except ImportError: 10 | print(f"Package {package} is not installed. Installing now...") 11 | 12 | if "python_embeded" in sys.executable or "python_embedded" in sys.executable: 13 | pip_install = [sys.executable, "-s", "-m", "pip", "install"] 14 | else: 15 | pip_install = [sys.executable, "-m", "pip", "install"] 16 | 17 | subprocess.check_call(pip_install + [install_package_name or package]) 18 | # else: 19 | # print(f"Package {package} is already installed.") 20 | 21 | ensure_package("dotenv", "python-dotenv") 22 | ensure_package("argon2", "argon2-cffi") 23 | 24 | 25 | from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS 26 | __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] 27 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ComfyUI_NAIDGenerator 2 | 3 | A [ComfyUI](https://github.com/comfyanonymous/ComfyUI) extension for generating images via the NovelAI API. 4 | 5 | ## Installation 6 | 7 | - `git clone https://github.com/bedovyy/ComfyUI_NAIDGenerator` into the `custom_nodes` directory. 8 | - or 'Install via Git URL' from [Comfyui Manager](https://github.com/ltdrdata/ComfyUI-Manager) 9 | 10 | ## Setting up NAI account 11 | 12 | Before using the nodes, you should set `NAI_ACCESS_TOKEN` in a `.env` file located in your main `ComfyUI` directory. 13 | 14 | `ComfyUI/.env` 15 | ``` 16 | NAI_ACCESS_TOKEN= 17 | ``` 18 | 19 | You can get a persistent API token by navigating to **User Settings > Account > Get Persistent API Token** on the NovelAI website. 20 | 21 | Otherwise, you can get an access token which is valid for 30 days using [novelai-api](https://github.com/Aedial/novelai-api). 22 | 23 | ## Usage 24 | 25 | The nodes are located in the `NovelAI` category. 26 | 27 | ![image](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/8ab1ecc0-2ba8-4e38-8810-727e50a20923) 28 | 29 | ### Txt2img 30 | 31 | Simply connect the `GenerateNAID` node to a `SaveImage` node. 32 | 33 | ![generate](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/1328896d-7d4b-4d47-8ec2-d1c4e8e2561c) 34 | 35 | **Note:** All generated images via the `GenerateNAID` node are automatically saved to `output/NAI_autosave/NAI_autosave_#####_.png` to preserve their original metadata. 36 | 37 | ### Img2img 38 | 39 | Connect an `Img2ImgOptionNAID` node to the `option` input of the `GenerateNAID` node and provide a source image. 40 | 41 | ![image](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/15ff8961-4f6b-4f23-86bf-34b86ace45c0) 42 | 43 | **Note:** The width and height of the source image will be resized to the generation size. 44 | 45 | ### Inpainting 46 | 47 | Connect an `InpaintingOptionNAID` node to the `GenerateNAID` node and provide a source image and a mask. 48 | 49 | ![image](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/5ed1ad77-b90e-46be-8c37-9a5ee0935a3d) 50 | 51 | **Note:** Both the source image and mask will be automatically resized to fit the generation size. 52 | 53 | ### Vibe Transfer 54 | 55 | Connect a `VibeTransferOptionNAID` node to the `GenerateNAID` node and provide a reference image to transfer its style and feel. 56 | 57 | ![Comfy_workflow](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/8c6c1c2e-f29d-42a1-b615-439155cb3164) 58 | 59 | You can also chain it with other options, like Img2Img. 60 | 61 | ![image](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/acf0496c-8c7c-48f4-9530-18e6a23669d5) 62 | 63 | #### Multiple Vibe Transfer 64 | 65 | Connect multiple `VibeTransferOptionNAID` nodes to combine their influences. 66 | 67 | ![preview_vibe_2](https://github.com/user-attachments/assets/2d56c0f7-bcd5-48ff-b436-012ea43604fe) 68 | 69 | ### Character Reference 70 | 71 | Use the `CharacterReferenceOptionNAID` node to guide the generation using a single reference image for character identity and/or style. 72 | 73 | ![image](https://github.com/user-attachments/assets/9f21eff1-163e-49f4-9e4a-85ea25b29988) 74 | 75 | - **style_aware:** If enabled, it attempts to copy both the character's features and the artistic style. 76 | - **fidelity:** Controls how strictly the generation should adhere to the reference image. The developers state that `primary_strength` is always kept at `1.0`, while `secondary_strength` is calculated as $1.0 - \text{fidelity}$. 77 | 78 | **Note:** The reference image will be automatically letterboxed to an accepted NAI canvas size to preserve its aspect ratio. 79 | 80 | ### ModelOption 81 | 82 | The default model of the `GenerateNAID` node is `nai-diffusion-4-5-full`. To change the model, connect a `ModelOptionNAID` node. 83 | 84 | Available V4+ models include: 85 | - `nai-diffusion-4-curated-preview` 86 | - `nai-diffusion-4-full` 87 | - `nai-diffusion-4-5-curated` 88 | - `nai-diffusion-4-5-full` 89 | 90 | ![ModelOption](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/0b484edb-bcb5-428a-b2af-1372a9d7a34f) 91 | 92 | ### NetworkOption 93 | 94 | You can set timeout and retry options using the `NetworkOption` node. You can also set `ignore_errors` to prevent the queue from stopping on an API error; if an error occurs, a blank 1x1 image will be output. 95 | 96 | ![preview_network](https://github.com/user-attachments/assets/d82b0ff2-c57c-4870-9024-8d78261a8fea) 97 | 98 | **Note:** If you set the timeout too short, you may not receive an image but could still be charged Anlas. 99 | 100 | ### Anlas Tracker 101 | 102 | This extension now includes Anlas tracking to monitor your usage. 103 | 104 | **1. Console Output (Automatic)** 105 | All generation and director tool nodes will automatically print your Anlas balance before and after the operation in the console where you launched ComfyUI. 106 | ``` 107 | [NovelAI] Anlas (pre-gen): 10000 108 | [NovelAI] Generation cost: 20 Anlas 109 | [NovelAI] Anlas (post-gen): 9980 110 | ``` 111 | 112 | **2. Visual Node** 113 | A new node, **`Anlas Tracker ✒️🅝🅐🅘`**, is available in the `NovelAI/utils` category. You can use it to display your current Anlas balance directly in your workflow. 114 | 115 | Connect its `anlas_string` output to a display node (e.g., "Show Text" from the [WAS Node Suite](https://github.com/WASasquatch/was-node-suite-comfyui)) to see the value. Use the `trigger` input to control when the balance is checked. 116 | 117 | ![image](https://github.com/user-attachments/assets/387799cd-36bd-4b5d-9746-bfd74db09f74) 118 | 119 | ### PromptToNAID 120 | 121 | ComfyUI uses `()` or `(word:weight)` for emphasis, while NovelAI uses `{}` and `[]`. This node, found in `NovelAI/utils`, converts ComfyUI's prompt syntax to NovelAI's. 122 | 123 | ![image](https://github.com/bedovyy/ComfyUI_NAIDGenerator/assets/137917911/25c48350-7268-4d6f-81fe-9eb080fc6e5a) 124 | 125 | ### Director Tools 126 | 127 | ![image](https://github.com/user-attachments/assets/e205a51e-59dc-4d5a-94c8-29715ed98739) 128 | 129 | You can find director tools like `LineArtNAID`, `EmotionNAID`, and `RemoveBGNAID` in the `NovelAI/director_tools` category. 130 | 131 | ![augment_example](https://github.com/user-attachments/assets/5833e9fb-f92e-4d53-9069-58ca8503a3e7) 132 | 133 | ### V4 / V4.5 Support 134 | 135 | The nodes fully support NAI's V4 and V4.5 model architecture. 136 | 137 | #### V4 Prompt Handling 138 | 139 | Two new nodes have been added in `NovelAI/v4` for V4/V4.5 prompt handling: 140 | 141 | - **`V4BasePrompt`**: Handles the positive prompt. 142 | - **`V4NegativePrompt`**: Handles the negative prompt. 143 | 144 | #### Example V4 / V4.5 Workflow 145 | 146 | Here's a basic setup for a V4/V4.5 model: 147 | 148 | ``` 149 | V4BasePrompt -----> positive 150 | GenerateNAID 151 | V4NegativePrompt -> negative 152 | ``` 153 | 154 | **Note:** Basic `img2img`, `vibe transfer` and `inpainting` functionality works with V4/V4.5. 155 | -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | from hashlib import blake2b 2 | import argon2 3 | 4 | import base64 5 | import dotenv 6 | from os import environ as env 7 | import io 8 | import re 9 | import requests 10 | from requests.adapters import HTTPAdapter, Retry 11 | import comfy.utils 12 | 13 | import torch 14 | import numpy as np 15 | from PIL import Image, ImageOps 16 | 17 | # cherry-picked from novelai_api.utils 18 | def argon_hash(email: str, password: str, size: int, domain: str) -> str: 19 | pre_salt = f"{password[:6]}{email}{domain}" 20 | blake = blake2b(digest_size=16) 21 | blake.update(pre_salt.encode()) 22 | salt = blake.digest() 23 | raw = argon2.low_level.hash_secret_raw(password.encode(), salt, 2, int(2000000 / 1024), 1, size, argon2.low_level.Type.ID,) 24 | hashed = base64.urlsafe_b64encode(raw).decode() 25 | return hashed 26 | 27 | def get_access_key(email: str, password: str) -> str: 28 | return argon_hash(email, password, 64, "novelai_data_access_key")[:64] 29 | 30 | 31 | def login(key) -> str: 32 | response = requests.post(f"https://api.novelai.net/user/login", json={ "key": key }) 33 | response.raise_for_status() 34 | return response.json()["accessToken"] 35 | 36 | def get_access_token(): 37 | dotenv.load_dotenv() 38 | if "NAI_ACCESS_TOKEN" in env: 39 | access_token = env["NAI_ACCESS_TOKEN"] 40 | elif "NAI_ACCESS_KEY" in env: 41 | print("ComfyUI_NAIDGenerator: NAI_ACCESS_KEY is deprecated. use NAI_ACCESS_TOKEN instead.") 42 | access_key = env["NAI_ACCESS_KEY"] 43 | elif "NAI_USERNAME" in env and "NAI_PASSWORD" in env: 44 | print("ComfyUI_NAIDGenerator: NAI_USERNAME is deprecated. use NAI_ACCESS_TOKEN instead.") 45 | username = env["NAI_USERNAME"] 46 | password = env["NAI_PASSWORD"] 47 | access_key = get_access_key(username, password) 48 | else: 49 | raise RuntimeError("Please ensure that NAI_API_TOKEN is set in ComfyUI/.env file.") 50 | 51 | if not access_token: 52 | access_token = login(access_key) 53 | return access_token 54 | 55 | 56 | BASE_URL="https://image.novelai.net" 57 | def generate_image(access_token, prompt, model, action, parameters, timeout=None, retry=None): 58 | data = { "input": prompt, "model": model, "action": action, "parameters": parameters } 59 | 60 | request = requests 61 | if retry is not None and retry > 1: 62 | retries = Retry(total=retry, backoff_factor=1, status_forcelist=[429, 500, 502, 503, 504], allowed_methods=["POST"]) 63 | session = requests.Session() 64 | session.mount("https://", HTTPAdapter(max_retries=retries)) 65 | request = session 66 | 67 | response = request.post(f"{BASE_URL}/ai/generate-image", json=data, headers={ "Authorization": f"Bearer {access_token}" }, timeout=timeout) 68 | response.raise_for_status() 69 | return response.content 70 | 71 | def augment_image(access_token, req_type, width, height, image, options={}, timeout=None, retry=None): 72 | data = { "req_type": req_type, "width": width, "height": height, "image": image } 73 | if options: 74 | data.update(options) 75 | 76 | request = requests 77 | if retry is not None and retry > 1: 78 | retries = Retry(total=retry, backoff_factor=1, status_forcelist=[429, 500, 502, 503, 504], allowed_methods=["POST"]) 79 | session = requests.Session() 80 | session.mount("https://", HTTPAdapter(max_retries=retries)) 81 | request = session 82 | 83 | response = request.post(f"{BASE_URL}/ai/augment-image", json=data, headers={ "Authorization": f"Bearer {access_token}" }, timeout=timeout) 84 | response.raise_for_status() 85 | return response.content 86 | 87 | 88 | def image_to_base64(image): 89 | i = 255. * image[0].cpu().numpy() 90 | img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) 91 | image_bytesIO = io.BytesIO() 92 | img.save(image_bytesIO, format="png") 93 | return base64.b64encode(image_bytesIO.getvalue()).decode() 94 | 95 | def naimask_to_base64(image): 96 | i = 255. * image[0].cpu().numpy() 97 | i = np.clip(i, 0, 255).astype(np.uint8) 98 | alpha = np.sum(i, axis=-1) > 0 99 | alpha = np.uint8(alpha * 255) 100 | rgba = np.dstack((i, alpha)) 101 | img = Image.fromarray(rgba) 102 | image_bytesIO = io.BytesIO() 103 | img.save(image_bytesIO, format="png") 104 | return base64.b64encode(image_bytesIO.getvalue()).decode() 105 | 106 | def bytes_to_image(image_bytes, keep_alpha=True): 107 | i = Image.open(io.BytesIO(image_bytes)) 108 | i = ImageOps.exif_transpose(i) 109 | if not keep_alpha: 110 | i = i.convert("RGB") 111 | image = np.array(i).astype(np.float32) / 255.0 112 | return torch.from_numpy(image)[None,] 113 | 114 | def blank_image(): 115 | return torch.tensor([[[0]]]) 116 | 117 | def resize_image(image, size_to): 118 | samples = image.movedim(-1,1) 119 | w, h = size_to 120 | s = comfy.utils.common_upscale(samples, w, h, "bilinear", "disabled") 121 | s = s.movedim(1,-1) 122 | return s 123 | 124 | def resize_to_naimask(mask, image_size=None, is_v4=False): 125 | samples = mask.movedim(-1,1) 126 | w, h = (samples.shape[3], samples.shape[2]) if not image_size else image_size 127 | width = int(np.ceil(w / 64) * 8) 128 | height = int(np.ceil(h / 64) * 8) 129 | s = comfy.utils.common_upscale(samples, width, height, "nearest-exact", "disabled") 130 | if is_v4: 131 | s = comfy.utils.common_upscale(s, width*8, height*8, "nearest-exact", "disabled") 132 | s = s.movedim(1,-1) 133 | return s 134 | 135 | def calculate_resolution(pixel_count, aspect_ratio): 136 | pixel_count = pixel_count / 4096 137 | w, h = aspect_ratio 138 | k = (pixel_count * w / h) ** 0.5 139 | width = int(np.floor(k) * 64) 140 | height = int(np.floor(k * h / w) * 64) 141 | return width, height 142 | 143 | def calculate_skip_cfg_above_sigma(w, h): 144 | # 832 * 1216 145 | return (w * h / 1011712) ** 0.5 * 19 146 | 147 | 148 | def prompt_to_stack(sentence): 149 | result = [] 150 | current_str = "" 151 | stack = [{ "weight": 1.0, "data": result }] 152 | 153 | for i, c in enumerate(sentence): 154 | if c in '()': 155 | # current_str = current_str.strip() 156 | if c == '(': 157 | if current_str: stack[-1]["data"].append(current_str) 158 | stack[-1]["data"].append({ "weight": 1.0, "data": [] }); 159 | stack.append(stack[-1]["data"][-1]) 160 | elif c == ')': 161 | searched = re.search(r"^(.*):(-?[0-9\.]+)$", current_str) 162 | current_str, weight = searched.groups() if searched else (current_str, 1.1) 163 | if current_str: stack[-1]["data"].append(current_str) 164 | stack[-1]["weight"] = float(weight) 165 | if stack[-1]["data"] != result: 166 | stack.pop() 167 | else: # no more to pop 168 | print("error :", sentence); 169 | print(f"col {i:>3}:", " " * i + "^") 170 | # raise Exception('Error durring parsing parentheses', sentence, i, c) 171 | current_str = "" 172 | else: 173 | current_str += c 174 | 175 | if current_str: 176 | stack[-1]["data"].append(current_str) 177 | 178 | return result 179 | 180 | def prompt_stack_to_nai(l, weight_per_brace=0.05, syntax_mode="brace"): 181 | result = "" 182 | for el in l: 183 | if isinstance(el, dict): 184 | weight = el["weight"] 185 | prompt = prompt_stack_to_nai(el["data"], weight_per_brace, syntax_mode) 186 | if weight < 0: 187 | syntax_mode = "numeric" 188 | if syntax_mode == "brace": 189 | brace_count = round((weight - 1.0) / weight_per_brace) 190 | result += "{" * brace_count + "[" * -brace_count + prompt + "}" * brace_count + "]" * -brace_count 191 | elif syntax_mode == "numeric": 192 | result += f"{weight:g}::{prompt} ::" 193 | else: 194 | result += el 195 | return result 196 | 197 | def prompt_to_nai(prompt, weight_per_brace=0.05, syntax_mode="brace"): 198 | return prompt_stack_to_nai(prompt_to_stack(prompt.replace("\(", "（").replace("\)", "）")), weight_per_brace, syntax_mode).replace("（", "(").replace("）",")") 199 | -------------------------------------------------------------------------------- /nodes.py: -------------------------------------------------------------------------------- 1 | import copy 2 | import io 3 | from pathlib import Path 4 | import folder_paths 5 | import zipfile 6 | import json as _json 7 | import copy as _copy 8 | 9 | from .utils import * 10 | import requests 11 | from requests.adapters import HTTPAdapter 12 | from urllib3.util.retry import Retry 13 | import torch 14 | import numpy as np 15 | from PIL import Image as PILImage 16 | 17 | TOOLTIP_LIMIT_OPUS_FREE = "Limit image size and steps for free generation by Opus." 18 | 19 | # ------------------------------------------------------------------ 20 | # Helper utilities 21 | # ------------------------------------------------------------------ 22 | 23 | # Accepted canvas sizes (per CR guidance); we will letterbox/pad to one of these 24 | ACCEPTED_CR_SIZES = [(1024, 1536), (1536, 1024), (1472, 1472)] 25 | 26 | def _get_user_data(access_token, timeout=120, retry=3): 27 | """Fetches user data to check Anlas balance. Now a global helper.""" 28 | USER_API_BASE_URL = "https://api.novelai.net" 29 | 30 | req_mod = requests 31 | if retry is not None and retry > 1: 32 | retries = Retry( 33 | total=retry, 34 | backoff_factor=1, 35 | status_forcelist=[429, 500, 502, 503, 504], 36 | allowed_methods=["GET", "POST"] 37 | ) 38 | session = requests.Session() 39 | session.mount("https://", HTTPAdapter(max_retries=retries)) 40 | req_mod = session 41 | 42 | response = req_mod.get( 43 | f"{USER_API_BASE_URL}/user/data", 44 | headers={"Authorization": f"Bearer {access_token}"}, 45 | timeout=timeout 46 | ) 47 | 48 | response.raise_for_status() 49 | return response.json() 50 | 51 | def _choose_cr_canvas(w, h): 52 | """Select the accepted CR canvas size whose aspect ratio is closest to the source image.""" 53 | aspect = w / h 54 | best = None 55 | best_diff = 9e9 56 | for cw, ch in ACCEPTED_CR_SIZES: 57 | diff = abs((cw / ch) - aspect) 58 | if diff < best_diff: 59 | best_diff = diff 60 | best = (cw, ch) 61 | return best 62 | 63 | def pad_image_to_canvas(tensor_image, target_size): 64 | """ 65 | Letterbox the given tensor image [1,H,W,C] into target_size (W,H) with black padding, 66 | preserving aspect ratio. 67 | """ 68 | _, H, W, C = tensor_image.shape 69 | tw, th = target_size 70 | arr = (tensor_image[0].cpu().numpy() * 255).clip(0, 255).astype(np.uint8) 71 | mode = "RGBA" if (C == 4) else "RGB" 72 | pil = PILImage.fromarray(arr) 73 | 74 | scale = min(tw / W, th / H) 75 | new_w = max(1, int(W * scale)) 76 | new_h = max(1, int(H * scale)) 77 | pil_resized = pil.resize((new_w, new_h), PILImage.LANCZOS) 78 | 79 | if mode == "RGBA": 80 | canvas = PILImage.new("RGBA", (tw, th), (0, 0, 0, 0)) 81 | else: 82 | canvas = PILImage.new("RGB", (tw, th), (0, 0, 0)) 83 | offset = ((tw - new_w) // 2, (th - new_h) // 2) 84 | canvas.paste(pil_resized, offset) 85 | 86 | out = np.array(canvas).astype(np.float32) / 255.0 87 | return torch.from_numpy(out)[None,] 88 | 89 | # ------------------------------------------------- 90 | # Core simple prompt conversion / utility nodes 91 | # ------------------------------------------------- 92 | 93 | class PromptToNAID: 94 | @classmethod 95 | def INPUT_TYPES(s): 96 | return { "required": { 97 | "text": ("STRING", { "forceInput":True, "multiline": True, "dynamicPrompts": False,}), 98 | "weight_per_brace": ("FLOAT", { "default": 0.05, "min": 0.05, "max": 0.10, "step": 0.05 }), 99 | "syntax_mode": (["brace", "numeric"], { "default": "brace" }), 100 | }} 101 | 102 | RETURN_TYPES = ("STRING",) 103 | FUNCTION = "convert" 104 | CATEGORY = "NovelAI/utils" 105 | def convert(self, text, weight_per_brace, syntax_mode): 106 | nai_prompt = prompt_to_nai(text, weight_per_brace, syntax_mode) 107 | return (nai_prompt,) 108 | 109 | class ImageToNAIMask: 110 | @classmethod 111 | def INPUT_TYPES(s): 112 | return { "required": { "image": ("IMAGE",) } } 113 | 114 | RETURN_TYPES = ("IMAGE",) 115 | FUNCTION = "convert" 116 | CATEGORY = "NovelAI/utils" 117 | def convert(self, image): 118 | s = resize_to_naimask(image) 119 | return (s,) 120 | 121 | class ModelOption: 122 | @classmethod 123 | def INPUT_TYPES(s): 124 | return { 125 | "required": { 126 | "model": ([ 127 | "nai-diffusion-2", 128 | "nai-diffusion-furry-3", 129 | "nai-diffusion-3", 130 | "nai-diffusion-4-curated-preview", 131 | "nai-diffusion-4-full", 132 | "nai-diffusion-4-5-curated", 133 | "nai-diffusion-4-5-full" 134 | ], { "default": "nai-diffusion-4-5-full" }), 135 | }, 136 | "optional": { "option": ("NAID_OPTION",) }, 137 | } 138 | 139 | RETURN_TYPES = ("NAID_OPTION",) 140 | FUNCTION = "set_option" 141 | CATEGORY = "NovelAI" 142 | def set_option(self, model, option=None): 143 | option = copy.deepcopy(option) if option else {} 144 | option["model"] = model 145 | return (option,) 146 | 147 | class Img2ImgOption: 148 | @classmethod 149 | def INPUT_TYPES(s): 150 | return { 151 | "required": { 152 | "image": ("IMAGE",), 153 | "strength": ("FLOAT", { "default": 0.70, "min": 0.01, "max": 0.99, "step": 0.01, "display": "number" }), 154 | "noise": ("FLOAT", { "default": 0.00, "min": 0.00, "max": 0.99, "step": 0.02, "display": "number" }), 155 | }, 156 | } 157 | 158 | RETURN_TYPES = ("NAID_OPTION",) 159 | FUNCTION = "set_option" 160 | CATEGORY = "NovelAI" 161 | def set_option(self, image, strength, noise): 162 | option = {} 163 | option["img2img"] = (image, strength, noise) 164 | return (option,) 165 | 166 | class InpaintingOption: 167 | @classmethod 168 | def INPUT_TYPES(s): 169 | return { 170 | "required": { 171 | "image": ("IMAGE",), 172 | "mask": ("IMAGE",), 173 | "add_original_image": ("BOOLEAN", { "default": True }), 174 | }, 175 | } 176 | 177 | RETURN_TYPES = ("NAID_OPTION",) 178 | FUNCTION = "set_option" 179 | CATEGORY = "NovelAI" 180 | def set_option(self, image, mask, add_original_image): 181 | option = {} 182 | option["infill"] = (image, mask, add_original_image) 183 | return (option,) 184 | 185 | class VibeTransferOption: 186 | @classmethod 187 | def INPUT_TYPES(s): 188 | return { 189 | "required": { 190 | "image": ("IMAGE",), 191 | "information_extracted": ("FLOAT", { "default": 1.0, "min": 0.01, "max": 1.0, "step": 0.01, "display": "number" }), 192 | "strength": ("FLOAT", { "default": 0.6, "min": 0.01, "max": 1.0, "step": 0.01, "display": "number" }), 193 | }, 194 | "optional": { "option": ("NAID_OPTION",) }, 195 | } 196 | RETURN_TYPES = ("NAID_OPTION",) 197 | FUNCTION = "set_option" 198 | CATEGORY = "NovelAI" 199 | def set_option(self, image, information_extracted, strength, option=None): 200 | option = copy.deepcopy(option) if option else {} 201 | if "vibe" not in option: 202 | option["vibe"] = [] 203 | option["vibe"].append((image, information_extracted, strength)) 204 | return (option,) 205 | 206 | class NetworkOption: 207 | @classmethod 208 | def INPUT_TYPES(s): 209 | return { 210 | "required": { 211 | "ignore_errors": ("BOOLEAN", { "default": True }), 212 | "timeout_sec": ("INT", { "default": 120, "min": 30, "max": 3000, "step": 1, "display": "number" }), 213 | "retry": ("INT", { "default": 3, "min": 1, "max": 100, "step": 1, "display": "number" }), 214 | }, 215 | "optional": { "option": ("NAID_OPTION",) }, 216 | } 217 | RETURN_TYPES = ("NAID_OPTION",) 218 | FUNCTION = "set_option" 219 | CATEGORY = "NovelAI" 220 | def set_option(self, ignore_errors, timeout_sec, retry, option=None): 221 | option = copy.deepcopy(option) if option else {} 222 | option["ignore_errors"] = ignore_errors 223 | option["timeout"] = timeout_sec 224 | option["retry"] = retry 225 | return (option,) 226 | 227 | # ------------------------------------------------- 228 | # Character Reference (Single Image) 229 | # ------------------------------------------------- 230 | 231 | class CharacterReferenceOption: 232 | INFO_EXTRACT_DEFAULT = 1.0 233 | @classmethod 234 | def INPUT_TYPES(cls): 235 | return { 236 | "required": { 237 | "image": ("IMAGE",), 238 | "style_aware": ("BOOLEAN", {"default": True, "tooltip": "Copy style along with identity."}), 239 | "fidelity": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "display": "number", "tooltip": "How strictly to match the character (and style if enabled)."}), 240 | }, 241 | "optional": {"option": ("NAID_OPTION",),} 242 | } 243 | RETURN_TYPES = ("NAID_OPTION",) 244 | FUNCTION = "set_option" 245 | CATEGORY = "NovelAI" 246 | def set_option(self, image, style_aware, fidelity, option=None): 247 | option = copy.deepcopy(option) if option else {} 248 | fidelity = max(0.0, min(1.0, fidelity)) 249 | option["character_reference_single"] = { 250 | "image": image, 251 | "style_aware": style_aware, 252 | "fidelity": fidelity, 253 | "info_extracted": self.INFO_EXTRACT_DEFAULT, 254 | } 255 | return (option,) 256 | 257 | # ------------------------------------------------- 258 | # Generation Node 259 | # ------------------------------------------------- 260 | 261 | class GenerateNAID: 262 | def __init__(self): 263 | self.access_token = get_access_token() 264 | self.output_dir = folder_paths.get_output_directory() 265 | 266 | @classmethod 267 | def INPUT_TYPES(s): 268 | return { 269 | "required": { 270 | "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), 271 | "width": ("INT", { "default": 832, "min": 64, "max": 1600, "step": 64, "display": "number" }), 272 | "height": ("INT", { "default": 1216, "min": 64, "max": 1600, "step": 64, "display": "number" }), 273 | "positive": ("STRING", { "default": ", best quality, amazing quality, very aesthetic, absurdres", "multiline": True, "dynamicPrompts": False }), 274 | "negative": ("STRING", { "default": "lowres", "multiline": True, "dynamicPrompts": False }), 275 | "steps": ("INT", { "default": 28, "min": 0, "max": 50, "step": 1, "display": "number" }), 276 | "cfg": ("FLOAT", { "default": 5.0, "min": 0.0, "max": 10.0, "step": 0.1, "display": "number" }), 277 | "variety" : ("BOOLEAN", { "default": False }), 278 | "decrisper": ("BOOLEAN", { "default": False }), 279 | "smea": (["none", "SMEA", "SMEA+DYN"], { "default": "none" }), 280 | "sampler": (["k_euler", "k_euler_ancestral", "k_dpmpp_2s_ancestral", "k_dpmpp_2m_sde", "k_dpmpp_2m", "k_dpmpp_sde", "ddim"], { "default": "k_euler" }), 281 | "scheduler": (["native", "karras", "exponential", "polyexponential"], { "default": "native" }), 282 | "seed": ("INT", { "default": 0, "min": 0, "max": 9999999999, "step": 1, "display": "number" }), 283 | "uncond_scale": ("FLOAT", { "default": 1.0, "min": 0.0, "max": 1.5, "step": 0.05, "display": "number" }), 284 | "cfg_rescale": ("FLOAT", { "default": 0.0, "min": 0.0, "max": 1.0, "step": 0.02, "display": "number" }), 285 | "keep_alpha": ("BOOLEAN", { "default": True, "tooltip": "Disable to further process output images locally" }), 286 | }, 287 | "optional": { "option": ("NAID_OPTION",) }, 288 | } 289 | 290 | RETURN_TYPES = ("IMAGE",) 291 | FUNCTION = "generate" 292 | CATEGORY = "NovelAI" 293 | 294 | @staticmethod 295 | def _post_image(access_token, prompt, model, action, parameters, timeout=None, retry=None): 296 | data = {"input": prompt, "model": model, "action": action, "parameters": parameters} 297 | 298 | req_mod = requests 299 | if retry is not None and retry > 1: 300 | retries = Retry(total=retry, backoff_factor=1, status_forcelist=[429, 500, 502, 503, 504], allowed_methods=["POST"]) 301 | session = requests.Session() 302 | session.mount("https://", HTTPAdapter(max_retries=retries)) 303 | req_mod = session 304 | 305 | response = req_mod.post(f"{BASE_URL}/ai/generate-image", json=data, headers={"Authorization": f"Bearer {access_token}"}, timeout=timeout) 306 | 307 | if response.status_code >= 400: 308 | print("RAW ERROR STATUS:", response.status_code) 309 | print("RAW ERROR BODY:", response.text) 310 | try: 311 | dbg = _copy.deepcopy(data) 312 | p = dbg.get("parameters", {}) 313 | if "director_reference_images" in p: p["director_reference_images"] = [i[:60] + "...(trunc)" for i in p["director_reference_images"]] 314 | if "reference_image_multiple" in p: p["reference_image_multiple"] = [i[:60] + "...(trunc)" for i in p["reference_image_multiple"]] 315 | dbg["parameters"] = p 316 | print("OUTGOING PAYLOAD (sanitized):", _json.dumps(dbg)[:2000]) 317 | except Exception as e: 318 | print("Payload debug failed:", e) 319 | 320 | response.raise_for_status() 321 | return response.content 322 | 323 | def generate(self, limit_opus_free, width, height, positive, negative, 324 | steps, cfg, decrisper, variety, smea, sampler, scheduler, 325 | seed, uncond_scale, cfg_rescale, keep_alpha, option=None): 326 | 327 | width, height = calculate_resolution(width * height, (width, height)) 328 | 329 | params = { 330 | "params_version": 1, "width": width, "height": height, "scale": cfg, "sampler": sampler, "steps": steps, 331 | "seed": seed, "n_samples": 1, "ucPreset": 3, "qualityToggle": False, 332 | "sm": (smea == "SMEA" or smea == "SMEA+DYN") and sampler != "ddim", 333 | "sm_dyn": (smea == "SMEA+DYN") and sampler != "ddim", 334 | "dynamic_thresholding": decrisper, "controlnet_strength": 1.0, "legacy": False, "add_original_image": False, 335 | "cfg_rescale": cfg_rescale, "noise_schedule": scheduler, "legacy_v3_extend": False, 336 | "uncond_scale": uncond_scale, "negative_prompt": negative, "prompt": positive, 337 | "reference_image_multiple": [], "reference_information_extracted_multiple": [], "reference_strength_multiple": [], 338 | "extra_noise_seed": seed, 339 | "v4_prompt": {"use_coords": False, "use_order": False, "caption": {"base_caption": positive, "char_captions": []}}, 340 | "v4_negative_prompt": {"use_coords": False, "use_order": False, "caption": {"base_caption": negative, "char_captions": []}} 341 | } 342 | 343 | model = "nai-diffusion-4-5-full" 344 | action = "generate" 345 | 346 | if sampler == "k_euler_ancestral" and scheduler != "native": 347 | params["deliberate_euler_ancestral_bug"] = False 348 | params["prefer_brownian"] = True 349 | 350 | if option: 351 | if "img2img" in option: 352 | action = "img2img" 353 | image, strength, noise = option["img2img"] 354 | params["image"] = image_to_base64(resize_image(image, (width, height))) 355 | params["strength"] = strength 356 | params["noise"] = noise 357 | elif "infill" in option: 358 | action = "infill" 359 | image, mask, add_original_image = option["infill"] 360 | params["image"] = image_to_base64(resize_image(image, (width, height))) 361 | params["mask"] = naimask_to_base64(resize_to_naimask(mask, (width, height), "4" in model)) 362 | params["add_original_image"] = add_original_image 363 | 364 | if "vibe" in option: 365 | for vibe in option["vibe"]: 366 | vimg, information_extracted, strength = vibe 367 | params["reference_image_multiple"].append(image_to_base64(resize_image(vimg, (width, height)))) 368 | params["reference_information_extracted_multiple"].append(information_extracted) 369 | params["reference_strength_multiple"].append(strength) 370 | 371 | if "model" in option: model = option["model"] 372 | if "v4_prompt" in option: params["v4_prompt"].update(option["v4_prompt"]) 373 | 374 | if "character_reference_single" in option: 375 | ref = option["character_reference_single"] 376 | base_caption = "character&style" if ref["style_aware"] else "character" 377 | ref_img = ref["image"] 378 | _, h_raw, w_raw, _ = ref_img.shape 379 | canvas_w, canvas_h = _choose_cr_canvas(w_raw, h_raw) 380 | padded = pad_image_to_canvas(ref_img, (canvas_w, canvas_h)) 381 | params["director_reference_images"] = [image_to_base64(padded)] 382 | params["director_reference_descriptions"] = [{"use_coords": False, "use_order": False, "legacy_uc": False, "caption": {"base_caption": base_caption, "char_captions": []}}] 383 | params["director_reference_strength_values"] = [1.0] 384 | params["director_reference_secondary_strength_values"] = [1.0 - ref["fidelity"]] 385 | params["director_reference_information_extracted"] = [1.0] 386 | 387 | timeout = option.get("timeout", 120) if option else 120 388 | retry = option.get("retry", 3) if option else 3 389 | 390 | if limit_opus_free: 391 | pixel_limit = 1024 * 1024 392 | if width * height > pixel_limit: 393 | params["width"], params["height"] = calculate_resolution(pixel_limit, (width, height)) 394 | if steps > 28: params["steps"] = 28 395 | 396 | if variety: params["skip_cfg_above_sigma"] = calculate_skip_cfg_above_sigma(params["width"], params["height"]) 397 | if sampler == "ddim" and "nai-diffusion-2" not in model: params["sampler"] = "ddim_v3" 398 | if action == "infill" and "nai-diffusion-2" not in model: model = f"{model}-inpainting" 399 | 400 | start_anlas = None 401 | try: 402 | user_data = _get_user_data(self.access_token, timeout, retry) 403 | start_anlas = user_data.get("subscription", {}).get("trainingStepsLeft") 404 | if start_anlas is not None: print(f"[NovelAI] Anlas (pre-gen): {start_anlas}") 405 | except Exception as e: print(f"[NovelAI] Anlas tracking failed (pre-gen): {e}") 406 | 407 | image = blank_image() 408 | try: 409 | zipped_bytes = self._post_image(self.access_token, positive, model, action, params, timeout, retry) 410 | with zipfile.ZipFile(io.BytesIO(zipped_bytes)) as zipped: 411 | image_bytes = zipped.read(zipped.infolist()[0]) 412 | 413 | full_output_folder, filename, counter, _, _ = folder_paths.get_save_image_path("NAI_autosave", self.output_dir) 414 | file = f"{filename}_{counter:05}_.png" 415 | d = Path(full_output_folder) 416 | d.mkdir(exist_ok=True) 417 | (d / file).write_bytes(image_bytes) 418 | 419 | if start_anlas is not None: 420 | try: 421 | user_data_final = _get_user_data(self.access_token, timeout, retry) 422 | final_anlas = user_data_final.get("subscription", {}).get("trainingStepsLeft") 423 | if final_anlas is not None: 424 | print(f"[NovelAI] Generation cost: {start_anlas - final_anlas} Anlas") 425 | print(f"[NovelAI] Anlas (post-gen): {final_anlas}") 426 | except Exception as e: print(f"[NovelAI] Anlas tracking failed (post-gen): {e}") 427 | 428 | image = bytes_to_image(image_bytes, keep_alpha) 429 | except Exception as e: 430 | if option and option.get("ignore_errors", False): print("ignore error:", e) 431 | else: raise e 432 | 433 | return (image,) 434 | 435 | # ------------------------------------------------- 436 | # Director Tool Augment Nodes 437 | # ------------------------------------------------- 438 | 439 | def base_augment(access_token, output_dir, limit_opus_free, ignore_errors, req_type, image, options=None): 440 | w, h = image.shape[2], image.shape[1] 441 | if limit_opus_free and w * h > 1024 * 1024: 442 | w, h = calculate_resolution(1024 * 1024, (w, h)) 443 | 444 | start_anlas = None 445 | try: 446 | user_data = _get_user_data(access_token) 447 | start_anlas = user_data.get("subscription", {}).get("trainingStepsLeft") 448 | if start_anlas is not None: print(f"[NovelAI] Anlas (pre-augment): {start_anlas}") 449 | except Exception as e: print(f"[NovelAI] Anlas tracking failed (pre-augment): {e}") 450 | 451 | base64_image = image_to_base64(resize_image(image, (w, h))) 452 | result_image = blank_image() 453 | try: 454 | zipped_bytes = augment_image(access_token, req_type, w, h, base64_image, options=options) 455 | with zipfile.ZipFile(io.BytesIO(zipped_bytes)) as zipped: 456 | image_bytes = zipped.read(zipped.infolist()[0]) 457 | 458 | full_output_folder, filename, counter, _, _ = folder_paths.get_save_image_path("NAI_autosave", output_dir) 459 | file = f"{filename}_{counter:05}_.png" 460 | d = Path(full_output_folder) 461 | d.mkdir(exist_ok=True) 462 | (d / file).write_bytes(image_bytes) 463 | 464 | if start_anlas is not None: 465 | try: 466 | user_data_final = _get_user_data(access_token) 467 | final_anlas = user_data_final.get("subscription", {}).get("trainingStepsLeft") 468 | if final_anlas is not None: 469 | print(f"[NovelAI] Augment cost: {start_anlas - final_anlas} Anlas") 470 | print(f"[NovelAI] Anlas (post-augment): {final_anlas}") 471 | except Exception as e: print(f"[NovelAI] Anlas tracking failed (post-augment): {e}") 472 | 473 | result_image = bytes_to_image(image_bytes) 474 | except Exception as e: 475 | if ignore_errors: print("ignore error:", e) 476 | else: raise e 477 | 478 | return (result_image,) 479 | 480 | class RemoveBGAugment: 481 | def __init__(self): 482 | self.access_token = get_access_token() 483 | self.output_dir = folder_paths.get_output_directory() 484 | @classmethod 485 | def INPUT_TYPES(s): 486 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }),}} 487 | RETURN_TYPES = ("IMAGE",) 488 | FUNCTION = "augment" 489 | CATEGORY = "NovelAI/director_tools" 490 | def augment(self, image, limit_opus_free, ignore_errors): 491 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "bg-removal", image) 492 | 493 | class LineArtAugment: 494 | def __init__(self): 495 | self.access_token = get_access_token() 496 | self.output_dir = folder_paths.get_output_directory() 497 | @classmethod 498 | def INPUT_TYPES(s): 499 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }),}} 500 | RETURN_TYPES = ("IMAGE",) 501 | FUNCTION = "augment" 502 | CATEGORY = "NovelAI/director_tools" 503 | def augment(self, image, limit_opus_free, ignore_errors): 504 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "lineart", image) 505 | 506 | class SketchAugment: 507 | def __init__(self): 508 | self.access_token = get_access_token() 509 | self.output_dir = folder_paths.get_output_directory() 510 | @classmethod 511 | def INPUT_TYPES(s): 512 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }),}} 513 | RETURN_TYPES = ("IMAGE",) 514 | FUNCTION = "augment" 515 | CATEGORY = "NovelAI/director_tools" 516 | def augment(self, image, limit_opus_free, ignore_errors): 517 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "sketch", image) 518 | 519 | class ColorizeAugment: 520 | def __init__(self): 521 | self.access_token = get_access_token() 522 | self.output_dir = folder_paths.get_output_directory() 523 | @classmethod 524 | def INPUT_TYPES(s): 525 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }), "defry": ("INT", { "default": 0, "min": 0, "max": 5, "step": 1, "display": "number" }), "prompt": ("STRING", { "default": "", "multiline": True, "dynamicPrompts": False }),}} 526 | RETURN_TYPES = ("IMAGE",) 527 | FUNCTION = "augment" 528 | CATEGORY = "NovelAI/director_tools" 529 | def augment(self, image, limit_opus_free, ignore_errors, defry, prompt): 530 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "colorize", image, options={ "defry": defry, "prompt": prompt }) 531 | 532 | class EmotionAugment: 533 | def __init__(self): 534 | self.access_token = get_access_token() 535 | self.output_dir = folder_paths.get_output_directory() 536 | strength_list = ["normal", "slightly_weak", "weak", "even_weaker", "very_weak", "weakest"] 537 | @classmethod 538 | def INPUT_TYPES(s): 539 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }), "mood": (["neutral", "happy", "sad", "angry", "scared", "surprised", "tired", "excited", "nervous", "thinking", "confused", "shy", "disgusted", "smug", "bored", "laughing", "irritated", "aroused", "embarrassed", "worried", "love", "determined", "hurt", "playful"], { "default": "neutral" }), "strength": (s.strength_list, { "default": "normal" }), "prompt": ("STRING", { "default": "", "multiline": True, "dynamicPrompts": False }),}} 540 | RETURN_TYPES = ("IMAGE",) 541 | FUNCTION = "augment" 542 | CATEGORY = "NovelAI/director_tools" 543 | def augment(self, image, limit_opus_free, ignore_errors, mood, strength, prompt): 544 | prompt = f"{mood};;{prompt}" 545 | defry = EmotionAugment.strength_list.index(strength) 546 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "emotion", image, options={ "defry": defry, "prompt": prompt }) 547 | 548 | class DeclutterAugment: 549 | def __init__(self): 550 | self.access_token = get_access_token() 551 | self.output_dir = folder_paths.get_output_directory() 552 | @classmethod 553 | def INPUT_TYPES(s): 554 | return {"required": {"image": ("IMAGE",), "limit_opus_free": ("BOOLEAN", { "default": True, "tooltip": TOOLTIP_LIMIT_OPUS_FREE }), "ignore_errors": ("BOOLEAN", { "default": False }),}} 555 | RETURN_TYPES = ("IMAGE",) 556 | FUNCTION = "augment" 557 | CATEGORY = "NovelAI/director_tools" 558 | def augment(self, image, limit_opus_free, ignore_errors): 559 | return base_augment(self.access_token, self.output_dir, limit_opus_free, ignore_errors, "declutter", image) 560 | 561 | # ------------------------------------------------- 562 | # Anlas Tracker (Visual Node) 563 | # ------------------------------------------------- 564 | 565 | class AnlasTrackerNAID: 566 | def __init__(self): 567 | self.access_token = get_access_token() 568 | 569 | @classmethod 570 | def INPUT_TYPES(s): 571 | return { 572 | "required": {}, 573 | "optional": { "trigger": ("*",) } # Allows chaining to control execution order 574 | } 575 | 576 | RETURN_TYPES = ("INT", "STRING",) 577 | RETURN_NAMES = ("anlas_int", "anlas_string",) 578 | FUNCTION = "get_anlas" 579 | CATEGORY = "NovelAI/utils" 580 | 581 | def get_anlas(self, trigger=None): 582 | anlas_count = 0 583 | try: 584 | user_data = _get_user_data(self.access_token) 585 | anlas_count = user_data.get("subscription", {}).get("trainingStepsLeft", 0) 586 | print(f"[NovelAI] Current Anlas Balance: {anlas_count}") 587 | except Exception as e: 588 | print(f"[NovelAI] Failed to fetch Anlas balance: {e}") 589 | return (0, "Error fetching Anlas") 590 | 591 | return (anlas_count, f"{anlas_count} Anlas") 592 | 593 | # ------------------------------------------------- 594 | # V4 Base / Negative Prompt nodes 595 | # ------------------------------------------------- 596 | 597 | class V4BasePrompt: 598 | @classmethod 599 | def INPUT_TYPES(s): 600 | return {"required": {"base_caption": ("STRING", { "multiline": True }),}} 601 | RETURN_TYPES = ("STRING",) 602 | FUNCTION = "convert" 603 | CATEGORY = "NovelAI/v4" 604 | def convert(self, base_caption): 605 | return (base_caption,) 606 | 607 | class V4NegativePrompt: 608 | @classmethod 609 | def INPUT_TYPES(s): 610 | return {"required": {"negative_caption": ("STRING", { "multiline": True }),}} 611 | RETURN_TYPES = ("STRING",) 612 | FUNCTION = "convert" 613 | CATEGORY = "NovelAI/v4" 614 | def convert(self, negative_caption): 615 | return (negative_caption,) 616 | 617 | # ------------------------------------------------- 618 | # Registration 619 | # ------------------------------------------------- 620 | 621 | NODE_CLASS_MAPPINGS = { 622 | "GenerateNAID": GenerateNAID, 623 | "ModelOptionNAID": ModelOption, 624 | "Img2ImgOptionNAID": Img2ImgOption, 625 | "InpaintingOptionNAID": InpaintingOption, 626 | "VibeTransferOptionNAID": VibeTransferOption, 627 | "NetworkOptionNAID": NetworkOption, 628 | "CharacterReferenceOptionNAID": CharacterReferenceOption, 629 | "AnlasTrackerNAID": AnlasTrackerNAID, # New node 630 | "MaskImageToNAID": ImageToNAIMask, 631 | "PromptToNAID": PromptToNAID, 632 | "RemoveBGNAID": RemoveBGAugment, 633 | "LineArtNAID": LineArtAugment, 634 | "SketchNAID": SketchAugment, 635 | "ColorizeNAID": ColorizeAugment, 636 | "EmotionNAID": EmotionAugment, 637 | "DeclutterNAID": DeclutterAugment, 638 | "V4BasePrompt": V4BasePrompt, 639 | "V4NegativePrompt": V4NegativePrompt, 640 | } 641 | 642 | NODE_DISPLAY_NAME_MAPPINGS = { 643 | "GenerateNAID": "Generate ✒️🅝🅐🅘", 644 | "ModelOptionNAID": "ModelOption ✒️🅝🅐🅘", 645 | "Img2ImgOptionNAID": "Img2ImgOption ✒️🅝🅐🅘", 646 | "InpaintingOptionNAID": "InpaintingOption ✒️🅝🅐🅘", 647 | "VibeTransferOptionNAID": "VibeTransferOption ✒️🅝🅐🅘", 648 | "NetworkOptionNAID": "NetworkOption ✒️🅝🅐🅘", 649 | "CharacterReferenceOptionNAID": "Character Reference ✒️🅝🅐🅘", 650 | "AnlasTrackerNAID": "Anlas Tracker ✒️🅝🅐🅘", # New node 651 | "MaskImageToNAID": "Convert Mask Image ✒️🅝🅐🅘", 652 | "PromptToNAID": "Convert Prompt ✒️🅝🅐🅘", 653 | "RemoveBGNAID": "Remove BG ✒️🅝🅐🅘", 654 | "LineArtNAID": "LineArt ✒️🅝🅐🅘", 655 | "SketchNAID": "Sketch ✒️🅝🅐🅘", 656 | "ColorizeNAID": "Colorize ✒️🅝🅐🅘", 657 | "EmotionNAID": "Emotion ✒️🅝🅐🅘", 658 | "DeclutterNAID": "Declutter ✒️🅝🅐🅘", 659 | "V4BasePrompt": "V4 Base Prompt ✒️🅝🅐🅘", 660 | "V4NegativePrompt": "V4 Negative Prompt ✒️🅝🅐🅘", 661 | } 662 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | --------------------------------------------------------------------------------