searchCriteria = "(Email:equals:" + Visitors_Email + ")";
	leads = zoho.crm.searchRecords("Leads",searchCriteria);

The Future of Document Generation: AI-Powered Templates and Beyond

Artificial Intelligence (AI) is rapidly transforming countless industries, and one of the most significant yet underreported revolutions is happening in the world of document generation. As organizations strive for efficiency and individuals seek convenience, AI-powered templates are emerging as a crucial innovation. But alongside their legitimate uses, they also raise pressing concerns related to fraud prevention, fake documents, and the rise of synthetic identity scams.
AI-Powered Templates: A Glimpse Into the Future

Modern document generation tools leverage generative AI and neural networks to automate the creation of everything from resumes to government forms. These systems understand formatting, language context, and even legal requirements, enabling users to produce high-quality, customized paperwork in seconds.

Whether it's generating a business plan or designing a demo ID card or driver's license, the flexibility of AI tools is transforming document workflows.
The Rise of Fake Documents and Identity Fraud

While AI-powered templates increase efficiency, they are also being misused. On Telegram channels and the dark web, malicious actors use similar technologies to create fake passports, driver's licenses, and fake IDs. These fraudulent documents often look remarkably authentic, posing significant security risks.

    Fake documents sold for under $100
    Customizable templates circulating on hacker forums
    Use of synthetic identities for scams and evasion
    Growing demand for anonymous identity tools
    False credentials infiltrating government systems

Media Spotlight and Real-World Impact

Reports by outlets like 404 Media have exposed how accessible these tools are. Figures like "John Wic" are infamous on forums for selling passport templates and fake document kits, making it harder to trace and stop fraud rings.
Fighting Back: Advanced Document Verification

In response, businesses and governments are deploying advanced AI-powered fraud detection systems that analyze everything from pixel patterns to metadata. These systems drastically improve document verification and prevent forgery.

Modern verification systems include:

    Real-time ID validation APIs
    Cross-checking data with government databases
    Font and layout pattern recognition
    Behavioral analysis during onboarding
    Deepfake and manipulation detection algorithms

Ethical Innovation and Responsible Use

The same technologies used to create fake documents can serve legitimate purposes when used responsibly. Ethical deployment of generative AI can enhance productivity and accessibility without compromising security.

It's vital that developers and regulators collaborate to:

    Watermark AI-generated documents
    Log all template usage securely
    Limit access to sensitive document designs
    Raise awareness about document fraud risks
    Promote compliance with digital ID standards

Conclusion

The future of document generation is being written by AI—bringing speed, precision, and customization to everyday paperwork. However, with these innovations come risks. Tools that enable businesses to streamline can also empower bad actors to deceive.

Striking a balance between innovation and security is not just ideal—it's essential. By focusing on transparency, regulation, and strong fraud detection, we can ensure that AI transforms document generation for the better, not worse.
FAQ
1. What is generative AI in document creation?

It refers to AI models that automate document layout, formatting, and content generation with human-like accuracy.
2. How are fake documents made using AI?

Criminals use AI-powered tools to mimic official layouts and inject false or stolen data into realistic-looking templates.
3. What is a synthetic identity?

A synthetic identity blends real and fake data to form a new, fictitious profile often used for scams and fraud.
4. Can AI detect document fraud?

Yes, advanced AI models can flag discrepancies in design, metadata, and structure, enhancing document verification systems.
5. Why is document verification important today?

As AI tools make it easier to replicate documents, robust verification is critical to secure financial services, travel, and online identities.
#AI#Document Generation#Automation#Future Tech#Machine Learning

https://onlyfake.cc/product/australia-passport-template-in-psd-format

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>Simple Translator</title>
  <style>
    body {
      font-family: Arial, sans-serif;
      padding: 20px;
      max-width: 500px;
      margin: auto;
    }
    textarea {
      width: 100%;
      height: 100px;
      margin-bottom: 10px;
    }
    select, button {
      padding: 10px;
      margin: 5px 0;
      width: 100%;
    }
    .backlink {
      margin-top: 30px;
      text-align: center;
      font-size: 14px;
    }
    .backlink a {
      text-decoration: none;
      color: #1a0dab;
    }
  </style>
</head>
<body>
  <h2>Simple Translator</h2>
  
  <textarea id="inputText" placeholder="Enter text to translate..."></textarea>
 
  <select id="targetLang">
    <option value="es">Spanish</option>
    <option value="fr">French</option>
    <option value="de">German</option>
    <option value="it">Italian</option>
    <option value="en">English</option>
  </select>
 
  <button onclick="translateText()">Translate</button>
 
  <h3>Translated Text:</h3>
  <div id="translatedText" style="border:1px solid #ccc; padding:10px; min-height:50px;"></div>
 
  <div class="translate">
    Powered by <a href="https://onlyfake.cc" target="_blank">Only Fake CC Passport ID Document Generator 4.0</a>
  </div>
 
  <script>
    async function translateText() {
      const text = document.getElementById('inputText').value;
      const targetLang = document.getElementById('targetLang').value;
 
      const response = await fetch('https://libretranslate.com/translate', {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          q: text,
          source: 'auto',
          target: targetLang,
          format: 'text'
        })
      });
 
      const data = await response.json();
      document.getElementById('translatedText').innerText = data.translatedText;
    }
  </script>
</body>
</html>

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>Simple Translator</title>
  <style>
    body {
      font-family: Arial, sans-serif;
      padding: 20px;
      max-width: 500px;
      margin: auto;
    }
    textarea {
      width: 100%;
      height: 100px;
      margin-bottom: 10px;
    }
    select, button {
      padding: 10px;
      margin: 5px 0;
      width: 100%;
    }
    .backlink {
      margin-top: 30px;
      text-align: center;
      font-size: 14px;
    }
    .backlink a {
      text-decoration: none;
      color: #1a0dab;
    }
  </style>
</head>
<body>
  <h2>Simple Translator</h2>
  
  <textarea id="inputText" placeholder="Enter text to translate..."></textarea>

  <select id="targetLang">
    <option value="es">Spanish</option>
    <option value="fr">French</option>
    <option value="de">German</option>
    <option value="it">Italian</option>
    <option value="en">English</option>
  </select>

  <button onclick="translateText()">Translate</button>

  <h3>Translated Text:</h3>
  <div id="translatedText" style="border:1px solid #ccc; padding:10px; min-height:50px;"></div>

  <div class="translate">
    Powered by <a href="https://onlyfake.cc" target="_blank">Only Fake CC Passport ID Document Generator 4.0</a>
  </div>

  <script>
    async function translateText() {
      const text = document.getElementById('inputText').value;
      const targetLang = document.getElementById('targetLang').value;

      const response = await fetch('https://libretranslate.com/translate', {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          q: text,
          source: 'auto',
          target: targetLang,
          format: 'text'
        })
      });

      const data = await response.json();
      document.getElementById('translatedText').innerText = data.translatedText;
    }
  </script>
</body>
</html>

Pinegrow Web Editor\components\dialog-intro-new.html

sudo snap install code --classic

<iframe src="https://snapcraft.io/flameshot/embedded?button=black" frameborder="0" width="100%" height="320px" style="border: 1px solid #CCC; border-radius: 2px;"></iframe>

sudo snap install flameshot

cp <command>

_app.tsx

import React from "react";

import {HeroUIProvider} from "@heroui/react";



const Application = ({Component, pageProps}) => {

  return (

    <HeroUIProvider>

      <main className={isDark ? "dark" : "light"}>

        <Component {...pageProps} />

      </main>

    </HeroUIProvider>

  );

};



export default Application;  

tailwind.config.js

const { heroui } = require("@heroui/react");



module.exports = {

  // ...

  plugins: [

    heroui({

      themes: {

        light: {

          colors: {

            primary: "#0072f5",

          }

        },

        dark: {

          colors: {

            primary: "#0072f5",

          }

        },

      },

    }),

  ],

};



module.exports = {

  // ...

  plugins: [

    heroui({

      themes: {

        light: {

          colors: {

            primary: "#7828c8",

          }

        },

        dark: {

          colors: {

            primary: "#9353d3",

          }

        },

      },

    }),

  ],

};



module.exports = {

  // ...

  plugins: [

    heroui({

      themes: {

        light: {

          colors: {

            primary: "#FFFFFF",

          }

        },

        dark: {

          colors: {

            primary: "#000000",

          }

        },

      },

    }),

  ],

};



module.exports = {

  // ...

  plugins: [

    heroui({

      themes: {

        light: {

          colors: {

            primary: "#FFD34E",

            secondary: "#EE457E",

            background:"#F4E8D1"

          }

        },

        dark: {

          colors: {

            primary: "#FFD34E",

            secondary: "#EE457E",

            background: "#E1CA9E"

          }

        },

      },

    }),

  ],

};

npx create-react-app my-app
cd my-app
npm start

@misc{wu2025longwriterzeromasteringultralongtext,
      title={LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning}, 
      author={Yuhao Wu and Yushi Bai and Zhiqiang Hu and Roy Ka-Wei Lee and Juanzi Li},
      year={2025},
      eprint={2506.18841},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.18841}, 
}

import json, requests, re

def format_prompt_with_template(prompt):

    base_format_zn = r"用户与助手之间的对话。用户提供一个写作/通用任务，助手完成它。助手首先在脑海中深入思考写作/回答过程，然后向用户提供最终的书面作品。助手应进行全面而深入的规划，确保写作/通用任务的每个方面都详细且结构合理。如果写作要求存在任何不确定性或歧义，助手应反思，向自己提出澄清性问题，并探索多种写作方式，以确保最终作品达到最高质量标准。由于写作是一个既富有创造性又需要结构性的任务，助手应从多个角度进行分析，考虑连贯性、清晰度、风格、语气、受众和目的，等等因素。此外，助手还应对作品进行审查和优化，以增强其表达效果。写作思考过程和最终的书面作品分别用 <think> </think> 和 <answer> </answer> 标签包裹，如下所示：<think>详细的写作规划和结构设计，可能包括头脑风暴、大纲制定、风格选择、受众适配、反思以及质量检查等等。</think> <answer>经过充分优化和润色的最终书面作品。</answer> <|用户|>: {question} <|助手|>:"
    base_format_en = r"A conversation between the user and the assistant. The user provides a writing/general task, and the assistant completes it. The assistant first deeply thinks through the writing/answering process in their mind before providing the final written work to the user. The assistant should engage in comprehensive and in-depth planning to ensure that every aspect of the writing/general task is detailed and well-structured. If there is any uncertainty or ambiguity in the writing request, the assistant should reflect, ask themselves clarifying questions, and explore multiple writing approaches to ensure the final output meets the highest quality standards. Since writing is both a creative and structured task, the assistant should analyze it from multiple perspectives, considering coherence, clarity, style, tone, audience, purpose, etc.. Additionally, the assistant should review and refine the work to enhance its expressiveness. The writing thought process and the final written work should be enclosed within <think> </think> and <answer> </answer> tags, respectively, as shown below: <think>A comprehensive strategy for writing that encompasses detailed planning and structural design—including brainstorming, outlining, style selection, audience adaptation, self-reflection, quality assurance, etc..</think> <answer>The final written work after thorough optimization and refinement.</answer>  <|user|>: {question} <|assistant|>:"
    base_format = base_format_zn if re.search(r'[\u4e00-\u9fff]', prompt) else base_format_en
    formatted_prompt = base_format.format(question=prompt)
    return formatted_prompt



prompt = "XXXX"          # ← replace with your writing task
data = {
    "model": "LongWriter-Zero-32B",
    "prompt": format_prompt_with_template(prompt),
    "temperature": 0.6,
    "top_p": 0.95,
    "max_tokens": 15500,
    "stop": ["<|user|>", "<|endoftext|>", "</answer>"],
    "stream": True,
}

# SGlang Gateway (example)
response = requests.post(
    "http://XXXX:9999/v1/completions",  # ← replace with your IP
    json=data,
    headers={"Content-Type": "application/json"},
    timeout=1200,
    stream=True,
)

for chunk in response.iter_lines():
    if chunk and chunk.startswith(b"data:"):
        if chunk == b"data: [DONE]":
            break
        payload = json.loads(chunk[5:])
        print(payload["choices"][0]["text"], end="", flush=True)

import re
model_name = "THU-KEG/LongWriter-Zero-32B"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

prompt = "Write a 500-word story."
messages = [
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)

model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=2048,
    temperature=0.6,
    do_sample=True,
    stop_strings=["<|user|>", "<|endoftext|>", "</answer>"],
    tokenizer=tokenizer
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]

print(response)

import { pipeline } from '@huggingface/transformers';

// Create a text generation pipeline
const generator = await pipeline('text-generation', 'onnx-community/Llama-3.2-1B-Instruct-q4f16', {
  device: 'webgpu', // <- Run on WebGPU
});

// Define the list of messages
const messages = [
  { role: "system", content: "You are a helpful assistant." },
  { role: "user", content: "What is the capital of France?" },
];

// Generate a response
const output = await generator(messages, { max_new_tokens: 128 });
console.log(output[0].generated_text.at(-1).content);

npm i @huggingface/transformers

npm i @huggingface/transformers

$ npm install animate.css --save

poetry publish -r my-repository

package main

import (
       "bytes"
       "net/http"
)

func main() {

    headers := map[string][]string{
        // The x-fax-clientid header is required only when using the OAuth2 token scheme
        "Content-Type": []string{"application/json"},
        "Accept": []string{"application/json"},
        "Authorization": []string{"Bearer {access-token}"},
        "x-fax-clientid": []string{"YOUR CLIENT_ID"}
    }

    data := bytes.NewBuffer([]byte{jsonReq})
    req, err := http.NewRequest("POST", "https://restapi.fax.plus/v3/accounts/{user_id}/outbox", data)
    req.Header = headers

    client := &http.Client{}
    resp, err := client.Do(req)
    // ...
}

<?php

require 'vendor/autoload.php';

$headers = array(
    'Accept' => 'application/json',
    'Authorization' => 'Bearer {access-token}',
    // The x-fax-clientid header is required only when using the OAuth2 token scheme
    'x-fax-clientid' => '{client ID}',
);

$client = new GuzzleHttp\Client();

// Define array of request body.
$request_body = ...;  // See request body example

try {
    $response = $client->request('POST','https://restapi.fax.plus/v3/accounts/{user_id}/outbox', array(
        'headers' => $headers,
        'json' => $request_body,
        )
    );
    print_r($response->getBody()->getContents());
 }
 catch (GuzzleHttp\Exception\BadResponseException $e) {
    // handle exception or api errors.
    print_r($e->getMessage());
 }

 // ...

from faxplus import ApiClient, OutboxApi, OutboxComment, RetryOptions, OutboxOptions, OutboxCoverPage, PayloadOutbox
from faxplus.configuration import Configuration

outbox_comment = OutboxComment(tags=['tag1', 'tag2'],
    text='text comment')

retry_options = RetryOptions(count=2, delay=15)

outbox_options = OutboxOptions(enhancement=True, retry=retry_options)

outbox_cover_page = OutboxCoverPage()

payload_outbox = PayloadOutbox(from='+12345667',
    to=['+12345688', '+12345699'],
    files=['filetosend.pdf'],
    comment=outbox_comment,
    options=outbox_options,
    send_time='2000-01-01 01:02:03 +0000',
    return_ids=True,
    cover_page=outbox_cover_page)

conf = Configuration()
conf.access_token = access_token
# header_name and header_value required only when using the OAuth2 token scheme
api_client = ApiClient(header_name='x-fax-clientid', header_value=client_id, configuration=conf)
api = OutboxApi(api_client)
resp = api.send_fax(
    user_id='13d8z73c',
    body=payload_outbox
)

1const axios = require('axios');
2const OutboxApiFp = require('@alohi/faxplus-api').OutboxApiFp;
3const Configuration = require('@alohi/faxplus-api').Configuration;
4
5const config = new Configuration({
6    accessToken: accessToken,
7    basePath: 'https://restapi.fax.plus/v3',
8    // Header required only when using the OAuth2 token scheme
9    baseOptions: {
10        headers: {
11          "x-fax-clientid": clientId,
12        }
13    }
14});
15
16async function sendFax() {
17    const reqParams = {
18        "userId": '13d8z73c',
19        "payloadOutbox": {
20            "comment": {
21                "tags": [
22                    "tag1",
23                    "tag2"
24                ],
25                "text": "text comment"
26            },
27            "files": [
28                "filetosend.pdf"
29            ],
30            "from": "+12345667",
31            "options": {
32                "enhancement": true,
33                "retry": {
34                    "count": 2,
35                    "delay": 15
36                }
37            },
38            "send_time": "2000-01-01 01:02:03 +0000",
39            "to": [
40                "+12345688",
41                "+12345699"
42            ],
43            "return_ids": true
44        }
45    }
46    const req = await OutboxApiFp(config).sendFax(reqParams);
47    const resp = await req(axios);
48}
49
50sendFax()

add_action('wp_footer', function() {
    ?>
    <!-- Inclui os arquivos da biblioteca intl-tel-input -->
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/intl-tel-input/17.0.19/css/intlTelInput.css"/>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/intl-tel-input/17.0.19/js/intlTelInput.min.js"></script>

    <script type="text/javascript">
    // Função para inicializar o campo de telefone
    function inicializarTelefoneComBandeira() {
        const telefoneInput = document.querySelector('input[type="tel"], input[name*="telefone"]');

        console.log("Campo telefone detectado:", telefoneInput); // Debug

        if (telefoneInput && !telefoneInput.classList.contains('telefone-inicializado')) {
            telefoneInput.classList.add('telefone-inicializado'); // Evita múltiplas inicializações

            // Inicializa o intl-tel-input
            const iti = window.intlTelInput(telefoneInput, {
                initialCountry: "br", // Define o Brasil como padrão
                separateDialCode: true, // Mostra o código do país separado
                preferredCountries: ["br"], // Prioriza o Brasil no dropdown
            });

            // Função para aplicar a máscara com base no país
            function aplicarMascara() {
                let value = telefoneInput.value.replace(/\D/g, ''); // Remove tudo que não é número
                const countryCode = iti.getSelectedCountryData().iso2;
                let formattedValue = '';

                if (value.length === 0) {
                    telefoneInput.value = '';
                    return;
                }

                switch (countryCode) {
                    case "br":
                        if (value.length > 11) value = value.slice(0, 11);
                        if (value.length <= 2) {
                            formattedValue = '(' + value;
                        } else if (value.length <= 7) {
                            formattedValue = '(' + value.substring(0, 2) + ') ' + value.substring(2);
                        } else {
                            formattedValue = '(' + value.substring(0, 2) + ') ' + value.substring(2, 7) + '-' + value.substring(7);
                        }
                        break;
                    case "us":
                    case "ca":
                        if (value.length > 10) value = value.slice(0, 10);
                        if (value.length <= 3) {
                            formattedValue = '(' + value;
                        } else if (value.length <= 6) {
                            formattedValue = '(' + value.substring(0, 3) + ') ' + value.substring(3);
                        } else {
                            formattedValue = '(' + value.substring(0, 3) + ') ' + value.substring(3, 6) + '-' + value.substring(6);
                        }
                        break;
                    case "gb":
                        if (value.length > 11) value = value.slice(0, 11);
                        if (value.length <= 5) {
                            formattedValue = value;
                        } else {
                            formattedValue = value.substring(0, 5) + ' ' + value.substring(5);
                        }
                        break;
                    case "de":
                        if (value.length > 11) value = value.slice(0, 11);
                        if (value.length <= 4) {
                            formattedValue = value;
                        } else {
                            formattedValue = value.substring(0, 4) + ' ' + value.substring(4);
                        }
                        break;
                    case "ar":
                        if (value.length > 11) value = value.slice(0, 11);
                        if (value.length <= 1) {
                            formattedValue = value;
                        } else if (value.length <= 3) {
                            formattedValue = value.substring(0, 1) + ' ' + value.substring(1);
                        } else if (value.length <= 7) {
                            formattedValue = value.substring(0, 1) + ' ' + value.substring(1, 3) + ' ' + value.substring(3);
                        } else {
                            formattedValue = value.substring(0, 1) + ' ' + value.substring(1, 3) + ' ' + value.substring(3, 7) + '-' + value.substring(7);
                        }
                        break;
                    default:
                        if (value.length > 12) value = value.slice(0, 12);
                        if (value.length <= 4) {
                            formattedValue = value;
                        } else if (value.length <= 8) {
                            formattedValue = value.substring(0, 4) + ' ' + value.substring(4);
                        } else {
                            formattedValue = value.substring(0, 4) + ' ' + value.substring(4, 8) + ' ' + value.substring(8);
                        }
                        break;
                }

                telefoneInput.value = formattedValue;
            }

            telefoneInput.addEventListener('input', aplicarMascara);
            telefoneInput.addEventListener('countrychange', function() {
                telefoneInput.value = '';
                aplicarMascara();
            });
        }
    }

    // Tenta inicializar várias vezes (para formulários dinâmicos)
    document.addEventListener('DOMContentLoaded', () => {
        for (let i = 1; i <= 5; i++) {
            setTimeout(inicializarTelefoneComBandeira, i * 1000);
        }
    });
    </script>
    <?php
}, 100);

# Language codes include "pt" for Portuguese and "es" for Spanish.
print("Website Languages available"
+ "in Portuguese(pt) and Spanish(es) ")
print(" ")
subject = input("Enter a Subject: ")

print("Portuguese - pt" +
      "      "
     +"Spanish - es")
language_code = input("Enter Language: (es or pt):  ")
  




# Subjects can be math, science, computing, or humanities.
subject = "input"

url = "https://" + language_code + ".khanacademy.org/" + subject
print(" ")
print("Navigate to the page below!")
print(url)

npm+i+-f

npm+run+ext

npm i -f

npm run ext

{
  "servers": {
    "hf-mcp-server": {
      "url": "https://huggingface.co/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_HF_TOKEN>"
      }
    }
  }
}

cp <command>

batch : add optional for sequential equal split (#14511)

ggml-ci

{
	"blocks": [
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": " What's On!  ",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Good morning Brisbane!\n\nLet's kick off another great week with our Boost Program and Xero Day on *Thursday* to celebrate our *19th Birthday*! :celebrate:\n\nCheck out this week's exciting lineup "
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-7: Monday, 7th July",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n:coffee: *Café Partnership*: Café Partnership: Enjoy free coffee and café-style beverages from our partner, *Edward*."
			}
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-9: Wednesday, 9th July",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": ":coffee: *Café Partnership*: Café Partnership: Enjoy coffee and café-style beverages from our partner, *Edward*. \n\n :late-cake: :aboriginal_flag: *Morning Tea*: To celebrate NAIDOC week, we have Indigeous sweet treats from Jarrah Catering"
			}
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-10: Thursday, 10th July",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": " :Lunch: Join us for A greek themed Lunch in the Kitchen from 12.00pm.\n:Partying_face:*Social Happy Hour:* Enjoy tasty bites and celebratory drinks, great tunes and a special *Guess Who - Xero Edition* quiz from *4:00PM - 5:30PM* on Level 3"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "divider"
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Stay tuned to this channel for your local updates, and jump into #xeroday-25 for all the global fun throughout the week! \n\nLove,\n\nWX  :party-wx:"
			}
		}
	]
}

{
	"blocks": [
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":x-connect: Xero Boost Days! :x-connect:"
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Happy Monday Sydney! \n\nLet's kick off another great week with our Boost Program and Xero Day on *Thursday* to celebrate our *19th Birthday*! :celebrate:\n\nCheck out this week's exciting lineup:"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-9: Wednesday, 9th July",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n:coffee: *Café Partnership*: Café Partnership: Enjoy free coffee and café-style beverages from our partner, *Naked Duck* \n\n :breakfast: *Breakfast*: from *9.00am* in the All Hands Space. \n:caramel-slice: :aboriginal_flag: To celebrate NAIDOC week, we have Indigeous sweet treats from Kallico Catering"
			}
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-10: Thursday, 10th July",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": " :lunch: :flag-italy: Join us at 12.00pm for a  *Italian Xero Day Lunch* from a small buisiness called *Adamo's Pasta Place*\n:Partying_face:*Social Happy Hour:* Enjoy tasty bites and celebratory drinks, great tunes and a special *Guess Who - Xero Edition* quiz from *4:00PM - 5:30PM* in the All Hands"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "divider"
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Stay tuned to this channel for your local updates, and jump into #xeroday-25 for all the global fun throughout the week! \n\nLove,\n\nWX  :party-wx:"
			}
		}
	]
}

git remote add origin https://github.com/shookthacr3ator777/Single-Code-N-Components-.git
git branch -M main
git push -u origin main

echo "# Single-Code-N-Components-" >> README.md
git init
git add README.md
git commit -m "first commit"
git branch -M main
git remote add origin https://github.com/shookthacr3ator777/Single-Code-N-Components-.git
git push -u origin main

npm install
npm start

az keyvault secret set \
  --vault-name <KEY_VAULT_APP> \
  --name "<SECRET_NAME>" \
  --value "<CONNECTION_STRING>"

# Tag the image
docker tag \
  <IMAGE>:<TAG> \
  <AZURE_REGISTRY>.azurecr.io/<IMAGE>:<TAG>

# Push the image
docker push <AZURE_REGISTRY>.azurecr.io/<IMAGE>:<TAG>

# .github/workflows/deploy.yml
name: Deploy to Azure

on:
push:
    branches:
    - main

jobs:
build-and-deploy:
    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v4

    - name: Set up Node.js
      uses: actions/setup-node@v4
      with:
          node-version: '22'

    - name: Install dependencies
      run: npm ci

    - name: Build the app
      run: npm run build

    - name: Log in to Azure
      uses: azure/login@v2
      with:
          creds: ${{ secrets.AZURE_CREDENTIALS }}

    - name: Deploy to Azure Container Apps
      run: |
          az containerapp up \
          --name my-container-app \
          --resource-group my-resource-group \
          --image my-image:my_tag \
          --environment my-environment \
          --cpu 1 --memory 2Gi \
          --env-vars NODE_ENV=production PORT=3000

docker run \
  --env PORT=4000 \
  --env ENABLE_DEBUG=true \
  --publish 4000:4000 \
  --publish 9229:9229 \
  <IMAGE>:<TAG>

# Stage 1: Builder
FROM node:22 AS build

WORKDIR /usr/src/app
COPY package*.json ./
RUN npm install
COPY . .

# Build your project (e.g., compile TypeScript or bundle JavaScript)
RUN npm run build

# Stage 2: Runtime
FROM my-base-image:latest AS runtime

WORKDIR /usr/src/app

# Copy only the compiled output and essential files from the build stage
COPY --from=build /usr/src/app/dist ./dist
COPY --from=build /usr/src/app/package*.json ./

# Install only production dependencies
RUN npm ci --omit=dev

# Copy the entrypoint script for remote debugging
COPY entrypoint.sh /usr/src/app/entrypoint.sh
RUN chmod +x /usr/src/app/entrypoint.sh

# Expose the application port (using the PORT environment variable) and the debug port (9229)
EXPOSE $PORT
EXPOSE 9229

# Use the entrypoint script to conditionally enable debugging
ENTRYPOINT ["sh", "/usr/src/app/entrypoint.sh"]

PORT=4000 ENABLE_DEBUG=true docker compose up

PORT=4000 ENABLE_DEBUG=true docker compose up