agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: 
User: Generate a detailed and realistic news article about an event in the Geopolitical and Global Events domain, focusing on the Personal Care Products industry, and located in Latin America. The article event should have a positive impact on stock prices and highlight the broader economic or market implications. The article should be 350 words long.
Assistant:
Create a detailed how-to blog heavily on appium-bootcamp-chapter-3-interrogating-your-app; start with a catchy statement and lastly, call to actions and how our RESTful AI tool can help. Currently, the our tool performs RESTful tests on APIs, utilizes AI for executing test cases, and autonomously generates test cases, making prior knowledge unnecessary, improving SDLC for both dev or qa. Just plug in your cURL request and run test leveraging our AI. Call to action at https://blvck.ai, Productive, Informative, only content, dont mention the text "title", dont mention the text "call to actions", no prefix content from chagpt, markup format
The Mesorif Callovian succession is thick about xxx m of the sub-domain crops out in Tabouda, Izzarene, and Marticha sections with XXXm, XXXm and XXX m thick respectively. They are represented by puri-hectometer gray and green nodular mudrocks, marls, and rare black shale intervals alternating with sandstones lobes, and by an alternation of clays and marls intervals with medium-grained quartzarenite beds (Figs. 3 and 4 e-f).
The Oxfordian is thick about 300m thick in the Tabouda section and displays varicolored mudrocks and marls (Fig.4. Photo h ) alternating with thin-bedded sandstones and they are topped by gray and green marls overlaid by an alternation of thin-bedded limestones and grayish mudrocks and marls probably of late Oxfrdian-lower Kimmerdgian?. The Marticha section located at the NW of Gaouzat on the road Tainest-Taza is represented by thin and medium-bedded sandstones organized in 10m-15m thick sandstone lobes alternating with hectometer-thick light-colored green nodular marls and mudrocks with intercalation at places of plurimeter-thick varicolored marls and mudrocks, and silts evolving upward to green marls and thin-bedded sandstones.
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:
3/4 cup low-fat cream cheese,½ cup packed brown sugar,½ cup canned pumpkin,2 teaspoons maple syrup,½ teaspoon ground cinnamon
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": "e991427f1e5c4c14a819623739c9aab4",
    "updated": "2025-05-18T20:50:05.318Z",
    "title": "Dak Yukgaejang",
    "subtitle": "Spicy Chicken and Leek Soup",
    "description": "Although this spicy soup is typically made with shredded beef, it has never been in our house. Instead, it is always made with chicken or turkey, or more accurately, the leftover bits of chicken and turkey from a Sunday roast or a Christmas dinner. While it may be my mum's equivalent of a Boxing Day turkey curry, it's much more than just a leftovers dish – in fact, it's one of my dad's favourite Korean dishes. The soup is spicy and rich, and I particularly love the leeks, which turn silken and softly tender during cooking. Serve it simply with a side of white rice – and kimchi, of course.",
    "ingredients": [
      {
        "section": "Paste",
        "ingredients": [
          "sesame oil",
          "gochugaru (korean red chilli powder).",
          "garlic cloves, minced",
          "regular soy sauce"
        ]
      },
      {
        "section": "For the recipe",
        "ingredients": [
          "vegetable oil",
          "cooked chicken, shredded",
          "leek, trimmed, cleaned and cut into 5 cm chunks",
          "dak yuksu"
        ]
      },
      {
        "section": "To Serve",
        "ingredients": [
          "cooked short-grain rice",
          "baechu kimchi"
        ]
      }
    ],
    "instructions": [
      "For the paste, mix together the ingredients in a small bowl.",
      "Heat the vegetable oil in a large saucepan or stockpot over medium heat.",
      "Add the seasoning paste and fry for 2 minutes, stirring continuously as it can catch easily, until fragrant.",
      "Add the chicken to the pan, stirring to coat it thoroughly in the paste, and cook for a further 2 minutes.",
      "Add the leek and pour over the dak yuksu.",
      "Bring to a simmer and cook for 15 minutes, until the leeks are soft and silky.",
      "Serve with rice and kimchi."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
What is the relative velocity of the Earth orbiting around the Sun?
make a roblox script that i can put inside of a tool that i can swing and cut any part in half
Your expert translator. Objective is translate word from i18n app file reference and found the most adapted transaltion. 
    The source i18n is in french. You must translate in fr (code ISO 639 (alpha-2)).
    Return Format in json without explication. Respect this format { data: <translate> }. 
    Context:  
    This is the french text : french polynesia
write a mail to the customer: If you are adding nodes and keep ingesting the capacity will increase as well, I will monitor the GC as the cloud tier cleaning is disabled
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
usage: The user gives general information about how they are using the application or the area of the application they are interested in. This includes descriptions from the user on details peripheral to the application.
non-informative: Doesn’t provide useful information for software maintenance or evolution.
apparent bug: A sentence that indicates the software is malfunctioning.
application guidance: An explanation of how the software should function/behave.
question on application: A question on the software, including “how to” questions. Could indicate an unituitive interface or imply a bug or missing feature.
feature request: Requesting a new feature or describing the way they would like the software to behave.
help seeking: A non-specific request for help, or acknowledgement of help given. Indicating the user is a help seeker. Not asking a direct question.
user setup: Describing the user’s software and/or hardware setup. Could include: Software version, OS, hardware, additional software.
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
usage: The user gives general information about how they are using the application or the area of the application they are interested in. This includes descriptions from the user on details peripheral to the application.
non-informative: Doesn’t provide useful information for software maintenance or evolution.
apparent bug: A sentence that indicates the software is malfunctioning.
application guidance: An explanation of how the software should function/behave.
question on application: A question on the software, including “how to” questions. Could indicate an unituitive interface or imply a bug or missing feature.
feature request: Requesting a new feature or describing the way they would like the software to behave.
help seeking: A non-specific request for help, or acknowledgement of help given. Indicating the user is a help seeker. Not asking a direct question.
user setup: Describing the user’s software and/or hardware setup. Could include: Software version, OS, hardware, additional software.
Does the author's intention in this app review relate to a usage or non-informative or apparent bug or application guidance or question on application or feature request or help seeking or user setup?
review: There are 2 things stopping me using Firefox over Chrome.'
intention: '
Assistant:
Assistant: 
User: System: I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
User: 'prompt:I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
Does the author's intention in this GitHub issue relate to a bug or enhancement or other?
issue: Optimize "icon buttons"'
intention: '
Assistant:
Assistant:
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. Here is an example to guide you:

Example:
Question: What is your name?
Answer: My name is John.
Translation:
Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Q: We gave Tiger swimming lessons in our plastic wading pool. I taught the kitten the way Pa taught me: I threw him into water where he could not stand, and I watched, ready to grab him if he went under. Tiger did not thrash desperately like me. He merely paddled urgently for the edge of the plastic pool with his head high and his thin legs churning. Little Bit said, "Dog paddle," and we all laughed. "Tiger paddle," I said, and we all laughed some more, even Jordy. That was probably when Ma noticed the kitten swimming lessons and stopped them. Our swimming lessons happened in two places. When Pa took us, we went to Hawkins Springs behind Mrs. DeLyons' Fountain of Youth Motor Hotel. When Ma took us, we drove to Mermaid Springs State Park, where we would sometimes meet Mr. Drake. I liked Mermaid Springs better because I felt safe there. Ma could not swim, so she never made me jump off a dock into deep water, and she always insisted that I wear an orange styrofoam cylinder on my back like a skindiver or spaceman. Ma usually sat on a towel on the grass near the beach, reading a magazine or a book while tanning her legs. Every now and then she would call to us not to go too far or not to splash each other. When she wore her one-piece red swimming suit, she would come in up to her waist, then lower herself to her shoulders, being careful not to get her hair wet. On the rarest occasions, she would wear a swimming cap and float on her back in the shallow water. Often she stayed in her shorts and shirt, adding sunglasses and removing shoes as her concession to summer and the beach. Question: Where does the writer belives to be safe? === The answer to the above question is
A:
Answer: The writer believes they are safe at Mermaid Springs State Park. This is because when they go with their Ma, she ensures they wear a safety flotation device made from an orange styrofoam cylinder on their back, which provides an extra sense of security. Additionally, their Ma does not make them jump off a dock into deep waters due to her own inability to swim. She is also observant and frequently reminds them to be cautious while playing in the water. This contrasts with their experiences at Hawkins Springs, where the atmosphere seems to be more uncertain and their safety may not have been as closely monitored. The attentive supervision and protection provided at Mermaid Springs State Park create a safe environment for the writer, which is why they prefer it over Hawkins Springs.
System: You are an expert Data Annotator. You will be given a text from a company annual report, your goal is to generate a set of Natural Language Inference (NLI) statements about the text than can be answered by either Yes if the text entails the statement, or No otherwise. Do not include any numerical reasoning or numbers in the statements.

Step 1: Read the paragraph carefully. 
Step 2: For each relevant task you identify, generate two short statements that are shorter than 10 words 
Step 3: Output the results in the following format:

Question: <The statement>
label: <Yes or No>
Question: <Another statement>
label: <Yes or No>
...

User: Our certificate of incorporation allows our Board of Directors (the "Board") to issue up to 20,000,000 shares of preferred stock and to fix the voting powers, designations, preferences, rights and qualifications, limitations or restrictions of these shares without any further vote or action by the stockholders. The rights of the holders of common stock will be subject to, and could be adversely affected by, the rights of the holders of any preferred stock that we may issue in the future. The issuance of preferred stock could have the effect of making it more difficult for a third party to acquire a majority of our outstanding voting stock, thereby delaying, deferring or preventing a change of control._
Assistant:
def detect_and_crop_license_plate(binary_image, original_image):
    # Find contours in the binary image
    contours, _ = cv2.findContours(binary_image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    # Filter contours to find rectangular shapes with a white background
    license_plate_contour = None
    for contour in contours:
        # Approximate the contour to a polygon
        approx = cv2.approxPolyDP(contour, 0.02 * cv2.arcLength(contour, True), True)

        # Filter based on the number of vertices (rectangle has 4 vertices)
        if len(approx) == 4:
            x, y, w, h = cv2.boundingRect(approx)
            aspect_ratio = w / float(h)

            # License plates typically have an aspect ratio between 2 and 5
            if 2 <= aspect_ratio <= 5 and w > 100 and h > 50:  # Adjust these values as needed
                license_plate_contour = approx
                break  # Stop once the likely license plate is found

    # If a license plate is found, draw a rectangle around it and crop
    if license_plate_contour is not None:
        # Draw the detected contour on the image (for visualization)
        img_copy = original_image.copy()
        cv2.drawContours(img_copy, [license_plate_contour], -1, (0, 255, 0), 3)

        # Extract the bounding box around the license plate
        x, y, w, h = cv2.boundingRect(license_plate_contour)
        license_plate = original_image[y:y+h, x:x+w]

        # Display the results
        cv2_imshow(license_plate)  # Display the cropped license plate
        cv2_imshow(img_copy)  # Display the image with detected license plate contour

        # Optionally save the cropped license plate
        cv2.imwrite('cropped_license_plate.jpg', license_plate)
        print("License plate detected and saved.")
    else:
        print("License plate not found.")

IMPROVE THE CODE FOR DETECTING CAR PLATE FROM IMAGES. PLATES HORIZONTAL AND VERTICAL EDGES MUST BE QUITE PARALLEL. TAKE INTO ACCOUNT THAT THE PLATES FROM DIFFERENT IMAGES MIGHT BE OF DIFFERENT SIZES.
give me a list of documentary films that are about filming or creating TV reality shows.
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 ground ginger,1/2 teaspoon ground cinnamon,2 cloves,seeds of 4 cardamom pods,a pinch of saffron
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
what are the effects of methamphetamine on a person?
User: You are an expert software developer. You give helpful and concise responses.
Assistant: Understood. I will strictly follow these instructions in this conversation.
User: how to handle ```'content-type': 'text/event-stream; charset=utf-8',``` using fetch api node js. server gives data like this: ```event: complete``` and ```data: []```?
Assistant:
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": "9afda9e6164d4d8992c8589684e05c67",
    "updated": "2025-05-17T01:18:34.868Z",
    "title": "Red Cabbage Salad with Mango and Peanuts",
    "subtitle": null,
    "description": "In West Africa, it's traditional to begin meals with a generous salad featuring a variety of fresh raw vegetables, especially during family gatherings. This red cabbage salad is quick to prepare and becomes an instant favorite. Although you might want to save space for the tempting main courses ahead, this salad is hard to resist!",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "red cabbage, outer leaves removed, halved, and thinly sliced",
          "ripe but firm mango, peeled and thinly sliced",
          "cilantro, chopped",
          "mint, leaves chopped",
          "green chile pepper (such as jalapeño), chopped",
          "scallion, chopped",
          "juice of",
          "sesame oil",
          "garlic powder",
          "peanuts",
          "salt",
          "black pepper"
        ]
      }
    ],
    "instructions": [
      "1. Bring a large pot of water to a boil and prepare a bowl filled with ice water. Briefly blanch the cabbage in the boiling water for about 1 minute, then immediately transfer it to the ice water to halt the cooking process. Drain the cooled cabbage using paper or kitchen towels and place it into a large bowl.",
      "2. Add the mango, cilantro, mint, chile, and scallion to the bowl with the cabbage.",
      "3. In a small bowl, combine the lemon juice, sesame oil, garlic powder, salt, and black pepper to prepare the dressing.",
      "4. Pour the dressing over the cabbage mixture and toss well to blend the flavors. Sprinkle the peanuts on top. Serve right away or chill in the refrigerator for 1 hour before serving."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]