agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
If Venom got into Sonic universe, could he copy speed of Sonic?
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
pbr: state a concrete problem related to a software product or service
inq: asks for either new functionality, an improvement, or requests information for support
irr: it does not belong to problem reports or inquires
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
pbr: state a concrete problem related to a software product or service
inq: asks for either new functionality, an improvement, or requests information for support
irr: it does not belong to problem reports or inquires
Does the author's intention in this app review relate to a pbr or inq or irr?
review: waiting to hear from you guys as to why I cant get single day service in Wichita Falls.'
intention: '
Assistant:
If x^2 is squared, x^3 is cubed, what is x^4?
Give me 2 English words of C1 level and their definitions
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: results of operations. Increasingly, companies are being measured by their performance on a variety of environmental, social, and_
Assistant:
give me a response to ```My dream is to explore the depths of the ocean, to uncover its secrets and discover all the mysteries that it holds. I want to show the world that anything is possible with a bit of courage and determination. What's your dream?``` to send in a discussion, VERY SHORT, CONCISE & CLEAR. ONLY RETURN THE RAW MESSAGE, DO NOT SAY "Hey here is the message you asked"
I serve Allah
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": "e7a192ed06a848559812ac25e727a1f5",
    "updated": "2025-05-07T08:12:05.376Z",
    "title": "Spaghetti and Meatballs from The Lady and the Tramp",
    "subtitle": "This recipe is based on one of the most memorable Disney movie dishes. It helped make spaghetti and meatballs a classic romantic meal. Perfect for sharing with your loved one and recreating the famous pasta strand moment.",
    "description": null,
    "ingredients": [
      {
        "section": "Meatballs",
        "ingredients": [
          "breadcrumbs (seasoned).",
          "romano and parmesan cheese blend (grated).",
          "salt",
          "pepper",
          "lightly beaten eggs",
          "ground beef"
        ]
      },
      {
        "section": "Sauce",
        "ingredients": [
          "finely chopped onion",
          "finely chopped green pepper",
          "tomato sauce (15 ounces each).",
          "undrained diced tomatoes",
          "tomato paste",
          "minced garlic",
          "bay leaves",
          "parsley flakes, oregano, and dried basil",
          "salt",
          "pepper",
          "red pepper flakes (chopped).",
          "freshly cooked spaghetti"
        ]
      }
    ],
    "instructions": [
      "1. In a bowl, mix together the salt, pepper, cheese, breadcrumbs, and eggs.",
      "2. Add the ground beef to the mixture and form into meatballs about 1 ½ inches in diameter.",
      "3. Brown the meatballs in a non-stick pan, then drain any excess oil. Set aside.",
      "4. In a slow cooker, combine the tomato sauce, diced tomatoes, tomato paste, onion, green pepper, garlic, bay leaves, and seasonings. Gently place the meatballs into the sauce and cover them. Cook on low for 5 hours or until the meatballs are completely cooked through.",
      "5. Serve the meatballs and sauce over freshly cooked spaghetti."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers de (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 de.
    - 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 : de (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "41b210560ce84415b696fd245c775d26",
    "updated": "2025-04-21T18:40:08.516Z",
    "title": "Shish Kebabs",
    "subtitle": "Enjoy a Middle Eastern-inspired meal centered around these delicious shish kebabs, complemented by hummus and baba ganouj.",
    "description": "",
    "ingredients": [
      {
        "section": "For the Kebabs",
        "ingredients": [
          "lamb, cut into (25.4 mm) cubes",
          "several bay leaves",
          "green peppers, diced in large pieces",
          "onion, diced in large pieces",
          "cherry tomatoes",
          "mushrooms, stalks removed"
        ]
      },
      {
        "section": "For the Marinade",
        "ingredients": [
          "balsamic vinegar",
          "olive oil",
          "salt-free dijon mustard",
          "garlic, minced",
          "freshly ground black pepper to taste"
        ]
      }
    ],
    "instructions": [
      "Place the lamb cubes in a shallow dish.",
      "In a separate bowl, whisk together the marinade ingredients. Pour the marinade over the lamb, ensuring all cubes are coated.",
      "Refrigerate the marinating lamb for 2 to 3 hours.",
      "Prepare a charcoal grill by lighting the charcoal and allowing it to burn until the coals are gray and glowing evenly.",
      "Thread the lamb cubes onto skewers, placing bay leaves between the meat pieces.",
      "Assemble separate skewers with the vegetables.",
      "Alternate tomatoes, mushroom caps, green pepper pieces, and onion pieces on the vegetable skewers.",
      "Position the lamb skewers over the hottest part of the grill and the vegetable skewers over a cooler section.",
      "Cook, turning frequently to prevent burning, until both the meat and vegetables are cooked thoroughly.",
      "Serve the kebabs immediately with rice."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea and provide examples.
Misconception: Believes the intersection in a prime factor venn diagram does not contribute to the size of the number represented by a circle
Is allowing execution of PowerShell script files in Windows 11 a potential security risk? How risky is it?
How to convince that tablet spotted after coating process does not affect the product quality?
Send only season number from below text like 01, 02, 03.etc without any extra text.

Marry My Husband S01 E05 WebRip 480p x265 HEVC 10bit Hindi Korean ESub  - (Ꭰ∆ᴍꪮꪀ).mkv
You will be provided with a web data and a user prompt.
The web data is from a result from a search engine. You please use the web data to answer the user prompt.

WEB DATA: The current time in Germany is 4:54 AM on Sunday, September 22, 2024, in Central European Summer Time (CEST), which is UTC+2 hours.
USER PROMPT: user: hi
assistant: Hello! How can I assist you today?
user: whats current time in Germany
would my code work?

import random

artists_listeners = {
'Lil Baby': 58738173,
'Roddy Ricch': 34447081,
'DaBaby': 29659518,
'Polo G': 27204041,
'NLE Choppa': 11423582,
'Lil Tjay': 16873693,
'Lil Durk': 19827615,
'Megan Thee Stallion': 26685725,
'Pop Smoke': 32169881,
'Lizzo': 9236657,
'Migos': 23242076,
'Doja Cat': 33556496,
'Tyler, The Creator': 11459242,
'Saweetie': 10217413,
'Cordae': 4026278,
'Juice WRLD': 42092985,
'Travis Scott': 52627586,
'Post Malone': 65466387,
'Drake': 71588843,
'Kendrick Lamar': 33841249,
'J. Cole': 38726509,
'Kanye West': 29204328,
'Lil Nas X': 23824455,
'21 Savage': 26764030,
'Lil Uzi Vert': 40941950,
}

keys = list(artists_listeners.keys())

score = 0

while True:
 first_artist = random.choice(keys)
 second_artist = random.choice(keys)

 while first_artist == second_artist:
   second_artist = random.choice(keys)

 while True:
   guess = input(f"\nWhich artist has more monthly Spotify listeners - 1. {first_artist.title()} or 2. {second_artist.title()}? ")
   guess_lower = guess.strip().lower()

 if guess_lower == 'quit':
    print("Thanks for playing!")
    quit()

 elif guess_lower in ['1', '2']:

   if guess_lower == '1':
      guess_artist = first_artist
   else:
      guess_artist = second_artist
   if artists_listeners[first_artist] > artists_listeners[second_artist]:
      correct_artist = first_artist
   else:
      correct_artist = second_artist

   if guess_artist.lower() == correct_artist.lower():
      print(f"You guessed correctly! {correct_artist.title()} had {int(artists_listeners[correct_artist] / 1e6):,}M monthly Spotify listeners and {first_artist.title()} has {int(artists_listeners[second_artist] / 1e6):,}M monthly Spotify listeners.")
      score += 1
   break

 else:
  print(f"\nSorry, you guessed incorrectly. {first_artist.title()} had {int(artists_listeners[first_artist] / 1e6):,}M monthly Spotify listeners and {second_artist.title()} has {int(artists_listeners[second_artist] / 1e6):,}M monthly Spotify listeners.\n")
  score = 0

play_again = input("Would you like to play again? (y/n) ")
if play_again.lower() == 'n':
 print("Thanks for playing!")
 quit()

else:
break
print(f"\nYour score is {score}.")
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Produce a sentence which mentions all of these concepts: monday, player, smile
Answer: On Monday, the player with a big smile played a fun game.
keep the script simple. usse binance ccxt for data.The bot will operate using 1-minute candles for entry and 3-minute candles for stop-loss confirmation.
Backtesting will evaluate profit-taking strategies at 1 day post-entry.
Entry Point:

Trigger: A new meme token is announced on a big exchange.
Condition: Enter LONG at the open of the next 1-minute candle after the announcement.
Stop Loss:

Condition: Exit position if a 3-minute candle closes below the entry price (our "line").
Re-Entry (Dynamic Behavior for Backtesting):

Condition: Re-enter if a 1-minute candle closes back above the line after a stop-loss exit.
Duration: The bot will continue to enter and exit trades dynamically for up to 24 hours after the announcement, as price oscillates around the line. THIS IS IMPORTANT
Impact Consideration: Continuous re-entries during the first 24 hours could have a significant effect on overall returns and principal risk.
Backtesting Goal: Evaluate the profitability of allowing this continuous re-entry behavior versus removing it entirely.
Take Profit:

Backtest Profit-Taking Levels: Evaluate all positions' profitability at the following interval post-entry:
1 Day

Profit-Taking Scenarios: Compare the net returns for full exits at each interval to determine the optimal timeframe for profit-taking.
Backtesting Goals:

Re-entry Impact:
Measure the performance of trades with continuous re-entries during the first 24 hours versus trades without re-entries.
Analyze metrics such as win rate, drawdown, and net profit to determine if re-entry behavior adds value.
Profit-Taking Optimization:
Evaluate how holding periods impact performance, particularly for meme tokens with high volatility.
Initial Tokens for Testing:

Act I: The AI Prophecy (ACT):
Exchange: Binance
Announcement Date: November 11, 2024
Peanut the Squirrel (PNUT):
Exchange: Binance
Announcement Date: November 11, 2024 You can begin with PNUT, ACT on binance as the exact time is listed on article:

CREATE THIS BACKTEST IN PYTHON +BACKTESTING PY
Generate an image creation prompt specifically optimized for the Flux Schnell model. The prompt should vividly describe the scene or concept expressed by the following sentence: 'Some accounts even hint that she used the ball as a stage to display both her vulnerability and strength.'. Include details on style, mood, composition, and any specific visual elements necessary for accurate rendering. Don't make it too long also
@Zia bot what "babu" means
generate more comprehensive details and examples on, 3. Creating a Facebook Business Page, minimalist tone
can hlp crete a style for <h2> "<h2>Climate Change</h2>
": around bg and text used in: "p {
margin: 15px 5px;
--x-blend-mode: Overlay;
  color: #F3EFEF;
  background-color: #182C2B;
  padding:5px 15px;
  border-radius:10px 10px;
  opacity:0.5;
}" bg: "#night-mode-toggle:checked ~ body,
#night-mode-toggle:checked ~ header,
#night-mode-toggle:checked ~ .language-option,
#night-mode-toggle:checked section {
background-color: #1B2827;
color: #F3EFEF;
}"
big picture stochastic as applied to gpt. secondly is it an emedding or algorithm, or both?
Find a list of at most 15 synonyms for the given word/phrase, separated in bullet points, ordered by relevance. Only return the synonyms, and add nothing else. Keep the casing of the word/phrase the same. Your response should only return the BULLET POINTS of the synonyms.


mamafih
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: •As part of our strategy, we may make divestitures, and divestitures involve many risks and uncertainties. These risks and uncertainties include: •our ability to locate suitable acquirers for our divestitures;
Assistant:
the following content is the metadata for a bacterial isolate from 3 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 3 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
    <output/>


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_029074305.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_61->isolate or collection date in yyyy-mm-dd: 1997-05-07 format->geographic information of islateion: Australia->host name: pig->mlst type: 5->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_029074305.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_61->isolate or collection date in yyyy-mm-dd: 1997-05-07->geographic information of islateion: Australia->host name: pig->mlst type: 5->serotype: N/A->vaccine: no




source 2:
------------------------------
<output>
accession number: GCA_029074305.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_61->isolate or collection date in yyyy-mm-dd: 1997-05-07->geographic information of islateion: Australia->host name: pig->mlst type: MLST:5->serotype: N/A->vaccine: no
<output/>
script about Cortland
You are an intelligent bounding box generator. I will provide you with a caption for a photo, image, or painting. Your task is to generate the bounding boxes for the objects mentioned in the caption, along with a background prompt describing the scene. The images are of size 512x512, and the bounding boxes should not overlap or go beyond the image boundaries. Each bounding box should be in the format of (object name, [top-left x coordinate, top-left y coordinate, box width, box height]) and include exactly one object. Make the boxes larger if possible. Do not put objects that are already provided in the bounding boxes into the background prompt. If needed, you can make reasonable guesses. Generate the object descriptions and background prompts in English even if the caption might not be in English. Do not include non-existing or excluded objects in the background prompt. Please refer to the example below for the desired format.

Caption: A realistic image of landscape scene depicting a green car parking on the left of a blue truck, with a red air balloon and a bird in the sky
Objects: [('a green car', [21, 181, 211, 159]), ('a blue truck', [269, 181, 209, 160]), ('a red air balloon', [66, 8, 145, 135]), ('a bird', [296, 42, 143, 100])]
Background prompt: A realistic image of a landscape scene

Caption: A watercolor painting of a wooden table in the living room with an apple on it
Objects: [('a wooden table', [65, 243, 344, 206]), ('a apple', [206, 306, 81, 69])]
Background prompt: A watercolor painting of a living room

Caption: A watercolor painting of two pandas eating bamboo in a forest
Objects: [('a panda eating bambooo', [30, 171, 212, 226]), ('a panda eating bambooo', [264, 173, 222, 221])]
Background prompt: A watercolor painting of a forest

Caption: A realistic image of four skiers standing in a line on the snow near a palm tree
Objects: [('a skier', [5, 152, 139, 168]), ('a skier', [278, 192, 121, 158]), ('a skier', [148, 173, 124, 155]), ('a palm tree', [404, 180, 103, 180])]
Background prompt: A realistic image of an outdoor scene with snow

Caption: An oil painting of a pink dolphin jumping on the left of a steam boat on the sea
Objects: [('a steam boat', [232, 225, 257, 149]), ('a jumping pink dolphin', [21, 249, 189, 123])]
Background prompt: An oil painting of the sea

Caption: A realistic image of a cat playing with a dog in a park with flowers
Objects: [('a playful cat', [51, 67, 271, 324]), ('a playful dog', [302, 119, 211, 228])]
Background prompt: A realistic image of a park with flowers

Caption: 一个客厅场景的油画，墙上挂着电视，电视下面是一个柜子，柜子上有一个花瓶。
Objects: [('a tv', [88, 85, 335, 203]), ('a cabinet', [57, 308, 404, 201]), ('a flower vase', [166, 222, 92, 108])]
Background prompt: An oil painting of a living room scene

Caption: statuer from bronze for batman  
Objects:
K8s ConfigMap 混乱，是因为存在制表符或行尾空格导致
```
sed -i -E  -e 's/[[:space:]]+$//g' -e 's/\t/    /g' nginx.conf

k create cm nginx-config --from-file nginx.conf --dry-run=client -o yaml | kubectl replace -f -``````
解释以上命令，并以Telegram消息支持的格式重新表述