74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
import torch
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import requests
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import io
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from PIL import Image
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import numpy as np
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class TelegramNotificationNode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"bot_token": ("STRING", {"default": "", "multiline": False}),
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"chat_id": ("STRING", {"default": "", "multiline": False}),
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"text": ("STRING", {"default": "ComfyUI notification!", "multiline": True}),
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},
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"optional": {
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"image": ("IMAGE",),
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}
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}
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RETURN_TYPES = ()
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FUNCTION = "send_notification"
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OUTPUT_NODE = True
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CATEGORY = "notifications"
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def send_notification(self, bot_token, chat_id, text, image=None):
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if not bot_token or not chat_id:
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print("Telegram Notification Error: Bot Token and Chat ID are required.")
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return ()
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try:
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if image is not None:
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# ComfyUI image is (Batch, Height, Width, Channels) tensor
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# We'll take the first image in the batch if there are multiple
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img_tensor = image[0]
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img_np = (img_tensor.cpu().numpy() * 255).astype(np.uint8)
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img_pil = Image.fromarray(img_np)
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# Save to memory
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bio = io.BytesIO()
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bio.name = 'image.png'
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img_pil.save(bio, 'PNG')
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bio.seek(0)
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url = f"https://api.telegram.org/bot{bot_token}/sendPhoto"
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files = {'photo': bio}
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data = {'chat_id': chat_id, 'caption': text}
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response = requests.post(url, files=files, data=data)
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else:
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url = f"https://api.telegram.org/bot{bot_token}/sendMessage"
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data = {'chat_id': chat_id, 'text': text}
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response = requests.post(url, data=data)
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if response.status_code != 200:
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print(f"Telegram Notification Error: {response.text}")
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else:
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print("Telegram Notification Sent Successfully!")
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except Exception as e:
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print(f"Telegram Notification Exception: {str(e)}")
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return ()
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NODE_CLASS_MAPPINGS = {
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"TelegramNotificationNode": TelegramNotificationNode
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"TelegramNotificationNode": "Telegram Notification Bot"
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}
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