agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
just not sure how to do a proper pulsing animation. like: there’s some line through which a dot or something goes from left to right periodically, and at some specific or random length this point increases its height in kinda triangle waveform in both up and down within element height in 32px and width 100%. do you understand now?. this point should increase or expand for a second its height and then decrease back to normal. also, need a tight line on full width through which this point is moving at the center. also, there’s no actual triangle waveform visible in lines, when this point pulsing to the height. that’s why I told you that this is impossible to do solely by css.:
(((```<html>
<head>
<style>
.pulse-animation {
width: 100%;
height: 32px;
position: relative;
overflow: hidden;
}

.pulse-animation .pulse-line {
position: absolute;
top: 50%;
transform: translateY(-50%);
width: 100%;
height: 1px;
background-color: red;
}

.pulse-animation .pulse-dot {
position: absolute;
left: -4px;
top: 50%;
transform: translateY(-50%);
width: 8px;
height: 8px;
background-color: blue;
animation: move-dot 2s linear infinite;
border-radius:50%;
}

@keyframes move-dot {
0%, 100% {
transform: translateY(-50%);
}
40%, 60% {
transform: translateY(-100%);
}
50% {
transform: translateY(-100%) scaleY(16);
}
}
</style>
</head>
<body>
<div class=‘pulse-animation’>
<div class=‘pulse-line’></div>
<div class=‘pulse-dot’></div>
</div>

<script>
var pulseDot = document.querySelector(‘.pulse-dot’);

pulseDot.addEventListener(‘animationiteration’, function () {
pulseDot.style.animation = ‘move-dot 2s linear infinite’;
});
</script>
</body>
</html>```))). do you know how medical technology cardio devices displays works? do the same in animation.
SELENA GOMEZ
RARE BEAUTY'S MADE ME A BILLIONAIRE!!!
9/6/2024 6:56 AM PT
selena gomez billionaire main
Getty Composite
Selena Gomez's officially one of the country's youngest female self-made billionaires, thanks to her booming beauty brand!

At 32, Selena is now valued at a whopping $1.3 billion, with most of her fortune coming from her Rare Beauty empire, according to the Bloomberg, which is ranking her for the first time on its Billionaires Index.

Selena Gomez Hard At Work
Selena Gomez Hard At Work
Launch Gallery
Getty
Rare Beauty launched just 5 years ago and has been a hit with influencers and teens getting into makeup for the first time -- thanks to Selena’s massive influence, with her IG following at a staggering 424 million.

On top of her beauty empire, Selena's racked up her fortune with brand partnerships, her mental health start-up Wondermind, and loads of acting gigs -- like her Emmy-nominated role in "Only Murders In The Building" -- all starting as a Disney child star!
translate to arabic this article
Create a fill in the blank quiz with 1 questions for each of the learning objectives listed below.  ELA.5.R.2.1 – Explain how text structures and/or features contribute to the overall meaning of texts.
ELA.5.R.2.2 – Explain how relevant details support the central idea(s), implied or explicit.
ELA.5.R.2.3 – Analyze an author’s purpose and/or perspective in an informational text.
ELA.5.R.2.4 - Track the development of an argument, identifying the specific claim(s), evidence, and reasoning.
Each question must have 1 correct answer. The correct answer must be given below the question. Remove all numbering of questions; just list the questions without numbers in front of them. List each learning objective in bold font above the questions that align to it. This quiz must assess the following learning objectives:  words and phrases that may be used to find the meaning or main idea of a NonFiction book. Give the answers to each fill in the blank. Phrases like, due to this, because of this, as a result, text features, graphic features, bolded or italicized words, graphs/charts, photos, chapter titles, narrative nonfiction, cause and effect, problem/solution, chronological,
the following content is the metadata for a bacterial isolate from 2 different sources. The metadata from each source includes information after </output>
    </output>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx
    <output/>

You must check if the metadata from 2 different sources are all consist. If yes, extract and output consist information below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding information. If the metadata shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no".

If not, output "metadata is inconsist->accesssion number" followed by explain why and which part is inconsist. PS:
    a. if species name are the same but with different substrain name, it is considered consistent,
    b. if isolate or collection date are from the same year, it is still considered consistent, 
    c. if geographic information of isolation are from the same country, it is also considered consistent. 
    d. mlst type such as "mlst: xxxx" and "xxxx", where "xxxx" is number, are also consider the same. also, "mlst" may mispell as "mlsty", you need correct it before comparing
    e. Ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
<output>
accession number: GCA_031215075.1->species name: Erysipelothrix rhusiopathiae->strain name: B18->isolate or collection date in yyyy-mm-dd: 2018 format->geographic information of islateion: China: Hubei->host name: N/A->mlst type: N/A->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_031215075.1->species name: Erysipelothrix rhusiopathiae->strain name: B18->isolate or collection date in yyyy-mm-dd: 2018 format->geographic information of islateion: China: Hubei->host name: pig->mlst type: N/A->serotype: N/A->vaccine: no
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers fr (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 fr.
    - 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 : fr (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "f010e3ffc4ff463b89c76f201bcb461b",
    "updated": "2025-04-22T21:12:57.852Z",
    "title": "Cream of Broccoli Soup",
    "subtitle": "This soup, while featuring a mix of vegetables, has a distinct broccoli flavor.",
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "frozen mixed vegetables",
          "frozen broccoli, chopped fine",
          "low-sodium bacon",
          "chopped onion",
          "whole wheat pastry flour",
          "skim milk"
        ]
      }
    ],
    "instructions": [
      "Bring a pot of water to a boil and cook the frozen mixed vegetables and broccoli until tender.",
      "Drain the cooked vegetables and set aside.",
      "In a separate pan, fry the bacon until crispy. Remove the bacon from the pan and set aside, reserving the rendered bacon grease.",
      "Pour enough of the reserved bacon grease into a soup pot to lightly coat the bottom.",
      "Add the chopped onion to the pot and cook over medium heat until softened and translucent.",
      "Sprinkle the whole wheat pastry flour over the onions and stir to combine. Gradually whisk in the skim milk, ensuring no lumps form.",
      "Stir the mixture constantly until it begins to thicken.",
      "Add the drained mixed vegetables and crumbled bacon to the soup.",
      "Continue to simmer the soup until it reaches your desired thickness.",
      "Season with salt and pepper to taste."
    ],
    "notes_ingredients": null,
    "notes_instructions": "The flavor of this soup improves after a day in the refrigerator."
  }
]
I have a list of ingredients that I would like to format in a simple and consistent way, following this structure:

"Quantity Unit Description."

Formatting Rules:

Quantity must be a number (e.g., "200" instead of "two hundred").

Unit must use the metric system and the corresponding abbreviated form (e.g., grams → g, liters → l, milliliters → ml, etc.).

Description should be the ingredient, including any specific details if mentioned (e.g., "brown sugar", "melted unsalted butter").

If an ingredient is already formatted correctly, do not change it.

Do not invent a quantity or unit if none is provided — leave it as is and just include the description.

If a line includes alternatives or multiple options (e.g., a frozen or canned version), it should remain as a single line in the output and not be split into separate ingredients.

Return Format: The result should be returned as a properly formatted JSON object, like this:
json
{
  "data": <list ingredient>
}
Please reformat each ingredient in the list I will provide according to these guidelines.

Context Dump
Ingredients source provided:
1 pack of brick pastry sheets (17x5 cm),1 gingerbread loaf,150 g melted clarified butter,2 garlic cloves,150 g butter,2 sprigs thyme,2 pinches fine salt,1 pear,Chestnut honey,3 to 4 walnut halves,30 g liquid cream,1 sheet gelatin,25 g walnut oil
name different types of cyber tol sthat can be used to check the vulnerablities on website and the code used to write it?
I have a list of ingredients that I would like to format in a simple and consistent way, following this structure:

"Quantity Unit Description."

Formatting Rules:

Quantity must be a number (e.g., "200" instead of "two hundred").

Unit must use the metric system and the corresponding abbreviated form (e.g., grams → g, liters → l, milliliters → ml, etc.).

Description should be the ingredient, including any specific details if mentioned (e.g., "brown sugar", "melted unsalted butter").

If an ingredient is already formatted correctly, do not change it.

Do not invent a quantity or unit if none is provided — leave it as is and just include the description.

If a line includes alternatives or multiple options (e.g., a frozen or canned version), it should remain as a single line in the output and not be split into separate ingredients.

Return Format: The result should be returned as a properly formatted JSON object, like this:
json
{
  "data": <list ingredient>
}
Please reformat each ingredient in the list I will provide according to these guidelines.

Context Dump
Ingredients source provided:
1/2 teaspoon minced garlic,1 teaspoon crushed toasted sesame seeds,1 teaspoon sugar,2 teaspoons soy sauce,1 teaspoon toasted sesame oil,Salt, pepper
What kind of questions could I ask on job interview?
email for submission of invoices from contractor:
معنى return
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 issued a baseline ESG report, and are in the process of determining emissions baselines and plan to set corporate goals. Our reports and statements reflect our current plans and aspirations and are not guarantees that we will be able to achieve them. Our failure to accomplish or accurately track and report on these goals on a timely basis, or at all, could adversely affect our reputation, financial performance, and growth, and expose us to increased scrutiny from the investment community as well as enforcement authorities. Standards for tracking and reporting ESG matters continue to evolve. Our selection of voluntary disclosure frameworks and standards, and the interpretation or application of those frameworks and standards, may change from time to time or differ from those of others. This may result in a lack of consistent comparative data from period to period or between UiPath and other companies in the same industry. In addition, our processes and controls may not comply with evolving standards for identifying, measuring, and reporting ESG metrics, including ESG-related disclosures that may be required of public companies by the SEC and other regulatory agencies to which we may be subject, and such standards may change over time, which could result in significant revisions to our current goals, reported progress in achieving such goals, or ability to achieve such goals in the future.
Assistant:
Write a message for Happy Anniversary
Pointzap titles -
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 intend to focus on generating sales of our performance-defining products through OEMs and in the aftermarket channel. To do this, we intend to continue to develop and introduce new and innovative products in our current end-markets and we intend to selectively develop products for applications and end-markets in which we do not currently participate. Currently, the majority of our sales are dependent on the demand for performance-defining products. Our aftermarket distribution network currently consists of more than 5,000 retail dealers and distributors worldwide. To further penetrate the aftermarket channel, we intend to selectively add additional dealers and distributors in certain geographic markets, expand our internal sales force and strategically increase the number of aftermarket specific products and services that we offer for existing vehicle platforms. In addition, we believe international expansion represents a significant opportunity for us and we intend to selectively increase infrastructure investments and focus on identified geographic regions.
Assistant:
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"Boulettes de millet null","description":null,"ingredients":[{"section":"For the recipe","ingredients":["250 ml de lait","125 g de millet","15 g de dattes","35 g de raisins secs","20 g de flocons d'avoine fins","noisettes, moulues"]}],"instructions":["Verser le lait dans une casserole.","Laver le millet et l'ajouter. Porter le tout à ébullition, puis continuer à faire mijoter en remuant constamment.","Couper les dattes en petits morceaux et les mettre dans la casserole avec les flocons d'avoine et les raisins secs et laisser reposer 10 minutes.","Former des petites boules avec la masse refroidie et les saupoudrer éventuellement de noisettes moulues."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
script about John Hancock Bowl
in python, what do logger.debug(), info(), and warning() do?
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers ar (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 ar.
    - 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 : ar (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "2f8cb6a5f08747fe9006ca5d75ea127e",
    "updated": "2025-05-11T18:16:52.887Z",
    "title": "Chinese Broccoli in Garlic and Ginger Sauce",
    "subtitle": null,
    "description": "Ginger is well-known for its numerous health benefits and is a fundamental ingredient in Chinese cuisine. Its aromatic and flavorful qualities make this quick and simple recipe perfect for days when you need a comforting boost. Enjoy the natural healing properties of this vibrant root in a delicious vegetable dish.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "gai lan (chinese broccoli) or can use long-stem broccoli",
          "vegetable oil",
          "fresh ginger",
          "garlic clove, finely chopped",
          "sesame oil"
        ]
      },
      {
        "section": "For the sauce",
        "ingredients": [
          "vegetable stock",
          "chinese rice wine",
          "grated fresh ginger",
          "salt",
          "sugar",
          "cornflour (cornstarch)."
        ]
      }
    ],
    "instructions": [
      "Begin by preparing the sauce. Mix the vegetable stock, Chinese rice wine, grated ginger, salt, sugar, and cornflour together in a bowl and set aside.",
      "Cut the broccoli into pieces about 5cm (2in) long, separating the stalks from the leaves.",
      "Heat a wok over high heat. When hot, add the vegetable oil, sliced ginger, and chopped garlic. Stir-fry for about 20 seconds until fragrant.",
      "Add the broccoli stalks and stir-fry for 2 minutes, then add a little water to generate steam.",
      "Once the stalks become tender, add the leaves and stir-fry for an additional minute.",
      "Pour in the prepared sauce and stir continuously until it thickens and evenly coats the vegetables.",
      "Transfer the dish to a serving plate, drizzle with sesame oil, and serve immediately."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
在每个标点符号后翻译成中文：Hello everyone. Welcome to my blog.About meMy name is Anna. I’m from Germany. I’m 11 years old. I’m tall and thin. I have long hair. I live with my family in a house close to some mountains. My mum is an Art teacher. My dad is a doctor. I have an elder sister and an elder brother.About my school and my hobbiesEvery day, I go to school by school bus. My favourite subjects are Maths, Art and Science. I like my school because the teachers are all very friendly. My dream is to be an engineer.I like many sports. I’m good at swimming and playing basketball. These are my favourite hobbies.I want to make friends with young people from all over the world! Email me,please!