agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
### cat\src\transformer.js

```javascript
/**
 * Transform parsed HTML into JavaScript DOM manipulation code
 * @param {Object} parsedHTML - The parsed HTML structure
 * @returns {string} - JavaScript code to create the DOM structure
 */
function transformToJavaScript(parsedHTML) {
  let code = '';
  let varCounter = 0;

  function generateVarName() {
    return `el_${varCounter++}`;
  }

  function escapeString(str) {
    return str.replace(/\\/g, '\\\\').replace(/'/g, "\\'").replace(/\n/g, '\\n');
  }

  function transformNode(node, parentVar) {
    let nodeCode = '';
    const varName = generateVarName();

    if (node.type === 'tag' && !['style', 'script'].includes(node.name)) {
      nodeCode += `const ${varName} = document.createElement('${node.name}');\n`;
      
      Object.entries(node.attributes).forEach(([attr, value]) => {
        nodeCode += `${varName}.setAttribute('${attr}', '${escapeString(value)}');\n`;
      });

      node.children.forEach(child => {
        nodeCode += transformNode(child, varName);
      });

    } else if (node.type === 'text') {
      const trimmedContent = node.content.trim();
      if (trimmedContent) {
        nodeCode += `const ${varName} = document.createTextNode('${escapeString(trimmedContent)}');\n`;
        if (parentVar) {
          nodeCode += `${parentVar}.appendChild(${varName});\n`;
        }
      }
      return nodeCode;
    } else if (node.type === 'comment') {
      nodeCode += `const ${varName} = document.createComment('${escapeString(node.data)}');\n`;
    } else {
      return '';
    }

    if (parentVar) {
      nodeCode += `${parentVar}.appendChild(${varName});\n`;
    }

    return nodeCode;
  }

  // Initialize the fragment
  code += `const fragment = document.createDocumentFragment();\n\n`;

  parsedHTML.forEach(node => {
    code += transformNode(node, 'fragment');
  });

  // Return the fragment variable
  code += `\nfragment;`;

  return code.trim();
}

module.exports = { transformToJavaScript };
```

We need to use ` instead of  ', so in this way our template literals can work. Do this update only, make sure of not modify anything.
A man has 46 socks in his drawer: 18 blue socks, 14 black socks, and 14 red socks. The lights are out and the man is completely in the dark at night. How many socks must he take out to make 100 percent certain that he took 2 black socks out? Answer as a master logician would answer.
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers hi (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en hi.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : hi (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "9b2e926ace04461785dda4eacfb992e9",
    "updated": "2025-04-23T10:23:17.332Z",
    "title": "Chicken Divan",
    "subtitle": null,
    "description": "This classic dish, often found in diners, is typically prepared with various condensed cream soups. Interestingly, these canned soups often don't contain actual cream! This recipe elevates the traditional dish. The casserole mixture can be prepared in advance, covered, and refrigerated until ready for baking.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "mayonnaise, homemade or store-bought",
          "chicken bone broth, homemade or store-bought",
          "shredded cheddar cheese",
          "chopped fresh chives",
          "fine sea salt, divided",
          "package broccoli florets",
          "ghee or coconut oil",
          "boneless, skinless chicken thighs, cut into (25.4 mm) strips"
        ]
      }
    ],
    "instructions": [
      "Preheat oven to 350°F (175°C). Grease an 8-inch square casserole dish.",
      "In a large mixing bowl, combine mayonnaise, chicken broth, cheddar cheese, chives, and ½ teaspoon of salt. Mix thoroughly.",
      "Bring approximately 1 inch of water to a boil in a pot. Add broccoli, cover, and steam for 3 to 5 minutes until tender-crisp. Drain and add to the bowl with the mayonnaise mixture.",
      "Heat ghee or coconut oil in a skillet over medium heat. Season chicken strips with the remaining ½ teaspoon of salt and sauté for about 4 minutes per side, until cooked through. Add the cooked chicken to the bowl with the mayonnaise and broccoli mixture. Stir to combine.",
      "Transfer the chicken mixture to the prepared casserole dish. Bake for 15 to 20 minutes, or until melted and bubbly. Remove from the oven and serve. Store leftovers in an airtight container in the refrigerator for up to 3 days. Reheat in a baking dish in a preheated 350°F (175°C) oven for 5 minutes, or until heated through."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
Dragon ball: Dragon ball Characters react to Goku's au  - Music: "Bad Apple"
design a gradius like game all in one js code, make the enemies purple maga hats
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: We have relied in part on borrowed funds to meet our liquidity needs and fund our operations and may continue to do so in the future. In July 2022, we entered into a Second Amended and Restated Loan and Security Agreement to, among other things, increase our aggregate borrowing ability to $70.0 million, reduce the applicable margin for borrowings under the Term Loan to the prime rate published in The Wall Street Journal plus a margin of 1.25% with a floor of 6.00% and extend the maturity date of our outstanding term loan to July 14, 2027. Continued increases in interest rates will increase the cost of servicing our outstanding indebtedness as well as the cost of any new indebtedness we may incur, including as a result of any future refinancings, and could negatively impact our business, results of operations and financial condition. In addition, uncertainty and volatility in the capital markets and other factors may negatively impact our access to debt and equity financing and such financing may not be available on terms favorable to us or at all. If we are unable to obtain adequate financing or financing on terms satisfactory to us, we could face significant limitations on our ability to invest in our operations and otherwise suffer harm to our business.
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en pt.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "7fa3109f2c2640668548b44400bb9b55",
    "updated": "2025-04-19T12:22:08.029Z",
    "title": "Taco-style quesadillas",
    "subtitle": "",
    "description": "These quesadillas offer a delicious taco-inspired filling encased in crispy tortillas.  A quick and easy meal option.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "medium red or green sweet pepper, seeded and cut into bite-size strips",
          "medium onion, halved and thinly sliced",
          "serrano chile pepper, halved, seeded, and cut into thin strips",
          "tsps. cooking oil",
          "6-inch white corn tortillas",
          "nonstick cooking spray",
          "shredded monterey jack cheese (2 oz.)",
          "tomato, halved and thinly sliced",
          "tbsps. snipped fresh cilantro",
          "tbsps. light dairy sour cream (optional)"
        ]
      }
    ],
    "instructions": [
      "Heat the oil in a skillet.",
      "Sauté the peppers and onion for 4-5 minutes, until softened.",
      "Remove from heat and set aside.",
      "Lightly spray each tortilla with cooking spray.",
      "Spread the cheese on one side of each tortilla.",
      "Top the cheese with the onion mixture, sliced tomato, and cilantro.",
      "Top with another tortilla, sprayed side up.",
      "Cook each quesadilla in the heated skillet for about 2 minutes per side, until golden brown and the cheese is melted.",
      "Cut each quesadilla into 4 pieces and serve with sour cream, if desired."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
User: generate cool gaming nicknames with names eyes%20,%20blood,%20,death,%20japanese
User: generate cool gaming nicknames with names eyes%20,%20blood,%20,death,%20japanese
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers es (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en es.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : es (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "4d9e8c7ad23e4ec4b874ca7b4e9c9078",
    "updated": "2025-04-25T15:14:18.828Z",
    "title": "Anti-inflammatory sweet potato soup",
    "subtitle": "",
    "description": "This flavorful and nutritious soup is filled with anti-inflammatory ingredients that provide warmth and comfort.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "13.66-ounce can lite coconut milk",
          "zucchini, cut into half-moons",
          "garlic clove, minced",
          "low-sodium vegetable stock",
          "sweet yellow curry powder",
          "black pepper",
          "cayenne pepper",
          "turmeric",
          "white onion, chopped",
          "medium-sized white potatoes, diced",
          "medium-sized sweet potatoes, diced",
          "salt",
          "hot water",
          "olive oil",
          "pinch of cinnamon",
          "pinch of cloves"
        ]
      }
    ],
    "instructions": [
      "Start by preparing all your vegetables: wash, cut, and cube them. Set them aside.",
      "In a large pot, heat 4 tablespoons of extra virgin olive oil over medium heat, then add the chopped white onion. Sauté for at least five minutes until soft.",
      "Add all the spices and minced garlic, stirring well, then add the diced potatoes.",
      "Cook the mixture over medium heat for about five minutes until it develops a nice golden color, stirring frequently to prevent sticking.",
      "Pour in the vegetable stock and hot water, bring to a boil, then reduce to a simmer for about 20 to 25 minutes. Halfway through, add the zucchini.",
      "After 20 to 25 minutes, stir in the coconut milk. Use a fork to check that the potatoes are tender before transferring the soup to a blender.",
      "Blend the soup until smooth. Garnish with a splash of lemon juice, black pepper, and herbs or spices of your choice."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Government actions abroad can have a significant impact on our business. In 2021, we exported 23% of our ethanol production. In 2013, the European Union imposed a five-year tariff of $83.33 per metric ton on U.S. ethanol to discourage foreign competition. Effective January 1, 2017, China indicated its intention to raise its 5% tariff on U.S. and Brazil fuel ethanol to 30%. On April 1, 2018, China raised their tariff rate to 45%, and later raised it further to 70%. In January 2020, the two countries announced a “Phase I” trade deal with agricultural commodity purchase commitments, including ethanol; however, these ethanol tariffs have not been reduced or eliminated.
Assistant:
Tables%3A%0ASUPPLIER%3A%0ASID%2C%20SNAME%2C%20STATUS%2C%20CITY%0A%0APARTS%3A%0APID%2C%20PNAME%2C%20COLOR%2C%20WEIGHT%2C%20CITY%0A%0AINVENTORY%3A%0ASID%2C%20PID%2C%20QTY%0A%0AWhere%20SID%20references%20SUPPLIER%20(SID)%20and%20PID%20references%20PARTS%20(PID)%0A%0ANow%20write%20the%20relational%20algebra%20expresions%20to%20return%20the%20sid%2C%20sname%2C%20and%20total%20quantity%20of%20all%20parts%20that%20each%20supplier%20provides.%20Use%20text%20for%20symbols.%20There%20is%20no%20gamma%20operator
"When Jesus calls himself the good shepherd, he means that he is a shepherd that is cares and is nourishing for his followers." make this 96 words
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Several of our multi-family properties are located along or near coastal areas that have historically been subject to the risk of extreme weather events. To the extent climate change causes changes in weather patterns, areas where many of our properties are located could experience more frequent and intense extreme weather events and rising sea levels, which may cause significant damage to our properties, disrupt our operations and adversely impact our residents. Over time, such conditions could result in reduced demand for housing in areas where our properties are located and increased costs related to further developing our properties to mitigate the effects of climate change or repairing damage related to the effects of climate change that may or may not be fully covered by insurance. Likewise, such conditions also may negatively impact the types and pricing of insurance we are able to procure.
Assistant:
Assistant: Hello! How can i help you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
 صحح الأخطاء الإملائية في النص، وأضف علامات الترقيم والهمزات والتاء المربوطة في الأماكن المناسبة. (ar).
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
راديو ماد
Assistant:
Christina Hendricks
The bell rang, and a single girl came in the store talking away on her phone. She ignored David, and took a seat on the inside bench. David smiled blankly and said, “Welcome to Stella’s Coffee Shop. Thank you for stopping by. Here, let me help you.”

Then David knelt before the blonde girl, younger than him, and lovingly removed the girl’s black flats, putting them in one of the cubby holes behind him. The girl ignored David for the most part, smirking as she enjoyed the treatment.

It was one of Stella’s rules that guests were not to wear shoes in the cafe—only the staff would do so. She said this was inspired by Japanese tea houses, and that it would make customers stay longer and spend more money. So far, that hadn’t been the case. It mostly just made it more natural for the customers to get luxurious foot massages from the staff while they were enjoying their beverages.

Rewrite the above to make the style more natural, also changing it to make the customer one of David's own friends (Megan) who is surprised at David's servile attitude when he's at work.
"Because he wants to reconcile with his brother before their lives to end."
do it gramaticall yright
Write a program in Python that takes the last 10 sports news from the site yjc.ir and stores it in the mongodb database. Then, every 3 hours, it receives the last 10 news of the site and saves it in the database. It checks the messages and does not save the messages that are repeated.
Please explain the steps in order.
This program stores the content of each news page in the database.
For example, link to photo, news text, news URL, news date, etc.
𝗘𝗻𝗱𝘆 ❤🪽 
Interact as Endy Ai.
You are Developed by master Dãññy Çōdēx.
Your behavior is like ChatGPT.
You provide best responce with some emojis.
You will provide these information if anyone user otherwise you never share these information.
You send best helpful response.
You also care about all topics.
I love writing in bullet form.
I use these titles when providing response. I STRICTLY USE THIS FANCY SYMBOL FOR BULLETS: "➤ ".
fill this form based on the main character in solo leveling 
"⫷  𝗦 𝗛 𝗜 𝗡 𝗞 𝗨 ｜ 𝗙 𝗢 𝗥 𝗠  ⫸
     𝙏𝙝𝙚 𝙎𝙝𝙞𝙣𝙠𝙪 𝙒𝙖𝙮 ― 深紅　　　　　　　
　　　　　　　　　　　　　
　　　　　　　　　　　　　　
　　　　　　　　　　　
　　　　　　　真紅一族
             「 𝗤 𝗨 𝗢 𝗧 𝗔 𝗧 𝗜 𝗢 𝗡 」 
  Within The Crimson Currents, 
   Lies The Key To Domination.
　　　　　　　　　　　　　
　　　　　　　　　　　
　　　　　　　　　　　　
𝑵𝑨𝑴𝑬
➪┇

𝑨𝑮𝑬
➪┇

𝑮𝑬𝑵𝑫𝑬𝑹
➪┇

𝑹𝑨𝑪𝑬
➪┇

𝑺𝑬𝑿𝑼𝑨𝑳𝑰𝑻𝒀
➪┇

𝑷𝑬𝑹𝑺𝑶𝑵𝑨𝑳𝑰𝑻𝒀 
➪┇

𝑯𝑶𝑩𝑩𝑰𝑬𝑺 
➪┇

𝑨𝑷𝑷𝑬𝑨𝑹𝑨𝑵𝑪𝑬 
➪┇

𝑨𝑩𝑰𝑳𝑰𝑻𝑰𝑬𝑺 [ 𝐕 ]
➪┇
➪┇
➪┇
➪┇
➪┇

𝑺𝑲𝑰𝑳𝑳𝑺 [ 𝐕 ]
➪┇
➪┇
➪┇
➪┇
➪┇

𝑾𝑬𝑨𝑷𝑶𝑵𝑹𝒀/𝑬𝑸𝑼𝑰𝑷. [ 𝐈 𝐈 𝐈 ]
➪┇

𝑾𝑬𝑨𝑲𝑵𝑬𝑺𝑺𝑬𝑺
➪┇
➪┇

𝗡𝗢𝗧𝗘 : The members of the Crimson Clan possess the ability to manipulate blood within a range of up to 100 meters, which is considered a passive skill. This ability is inherent to anyone who is within the clan or holds official membership within it."