agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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": "86903dd7a85d4866abcafc54e56851bf",
    "updated": "2025-04-25T23:11:26.272Z",
    "title": "Chocolate Crackles",
    "subtitle": "A beloved Christmas tradition.",
    "description": "This recipe has been a cherished family tradition for many years, especially during the Christmas season.  Simple to prepare, these treats store well and are always a hit with children. The unique combination of ingredients adds a touch of mystery to their delicious flavor.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "eggs",
          "(200 g) sugar",
          "vanilla extract",
          "(85 g) unsweetened chocolate, grated",
          "(200 g) unsalted pecans, finely chopped",
          "(30 g) dry low sodium bread crumbs",
          "(16 g) all-purpose flour",
          "ground cinnamon",
          "(25 g) confectioners' sugar"
        ]
      }
    ],
    "instructions": [
      "Whisk the eggs together with the sugar and vanilla extract until well combined.",
      "Incorporate all remaining ingredients, except the confectioners' sugar.",
      "If the dough is too soft to handle easily, chill it in the refrigerator until firm.",
      "Form the dough into small balls, approximately 1 inch (2.5 cm) in diameter.",
      "Roll each ball in confectioners' sugar and arrange them on a greased baking sheet, spacing them about 1 inch (2.5 cm) apart.",
      "Bake in a preheated oven at 325°F (170°C, gas mark 3) for 12 to 15 minutes.",
      "The finished crackles will be soft and have a cracked appearance on top.",
      "Allow the crackles to cool completely on wire racks.",
      "Store the cooled crackles in an airtight container."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
Find the first partial derivative of this function with respect to x and y
answer this
is there any way to learn CFA for free?
возьми этот код за основу но сделай так что бы область очков не размывалась

import cv2
import gdown
from matplotlib import pyplot as plt

# Загрузка изображения актера/актрисы
gdown.download('https://storage.yandexcloud.net/mybestdatasets/Keanu_Reeves.jpg', None, quiet=True)
# Загрузка изображения солнцезащитных очков
gdown.download('https://storage.yandexcloud.net/mybestdatasets/glasses.png', None, quiet=True)

# Загрузка изображений
img = cv2.imread('./Keanu_Reeves.jpg')
if img is None:
    print("Ошибка: изображение не загружено. Проверьте путь к файлу.")
    exit()
img2 = img.copy()
sunglasses = cv2.imread('./glasses.png', -1)  # Чтение с альфа-каналом
if sunglasses is None:
    print("Ошибка: изображение очков не загружено. Проверьте путь к файлу.")
    exit()

# Загрузка каскада Хаара для поиска лиц и глаз
classifier_face = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
classifier_eye = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye.xml")

# Выполнение распознавания лиц
bboxes = classifier_face.detectMultiScale(img, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

for box in bboxes:
    x, y, width, height = box
    x2, y2 = x + width, y + height

    # Рисуем овал вокруг лица
    cv2.ellipse(img2, (x + width // 2, y + height // 2), (width // 2 + 10, height // 2 + 10), 0, 0, 360, (0, 0, 255), 2)

    # Найденная область с лицом
    face = img2[y:y + height, x:x + width]

    # Выполнение распознавания глаз
    eyes = classifier_eye.detectMultiScale(face)

    for (x_eye, y_eye, w_eye, h_eye) in eyes:
        # Определяем центр и радиус для рисования очков
        center = (x + x_eye + w_eye // 5, y + y_eye + h_eye // 5)
        scale = int(5)  # Масштабирование очков
        sunglasses_resized = cv2.resize(sunglasses, (w_eye * scale, h_eye * scale))
        
        # Определяем положение для вставки очков
        overlay_x = center[1] - (w_eye * scale // 6)
        overlay_y = center[1] - (h_eye * scale // 3)

        # Объединяем изображения
        for c in range(0, 3):
            img2[overlay_y:overlay_y + sunglasses_resized.shape[0], overlay_x:overlay_x + sunglasses_resized.shape[1], c] = \
                sunglasses_resized[:, :, c] * (sunglasses_resized[:, :, 3] / 255.0) + \
                img2[overlay_y:overlay_y + sunglasses_resized.shape[0], overlay_x:overlay_x + sunglasses_resized.shape[1], c] * (1. - sunglasses_resized[:, :, 3] / 255.0)

    # Размытие лица, кроме глаз
    face_area = img2[y:y + height, x:x + width]
    blurred_face = cv2.GaussianBlur(face_area, (99, 99), 30)
    img2[y:y + height, x:x + width] = cv2.addWeighted(face_area, 0.5, blurred_face, 0.5, 0)

    

# Отображение изображений
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15, 8))
ax1.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
ax1.xaxis.set_ticks([])
ax1.yaxis.set_ticks([])
ax1.set_title('Исходное изображение')

ax2.imshow(cv2.cvtColor(img2, cv2.COLOR_BGR2RGB))
ax2.xaxis.set_ticks([])
ax2.yaxis.set_ticks([])
ax2.set_title('Изображение с размазанным лицом и очками')

plt.show()
List down all skills required in F&A and FP&A Domain.
I need a dnsmasq basic config example for resolving *.captain.localhost from 192.168.5.221 (CentOS7 server) to my 192.168.5.162 Windows 10 client
Hey, this is a Tunisian dialect text I want you to translate to English.
Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

هاوينهم يطيبوا أنا هاني مبنكة نحكي معاك قلتلهم إليوم تاعبة ما عينيش
Give me original and cohesive detailed commentary on this using a critical straitforward informal tone : I haven’t been shy in voicing my displeasure/disinterest with K-pop’s current trend of beige, easy-listening girl group fare. The sound has become ubiquitous over the past year, dulling the excitement of many new groups. But within this sonic realm, ILLIT’s megahit "Magnetic" stood out as a solid example of the genre(although I hated at first but it grew on me). Now they’re back with its follow-up: the very tame "Cherish".

Rather than echo Magnetic‘s chirpy hook, Cherish reminds me much more of the girl group Fifty Fifty. It has the same soft, inconsequential energy. The song finds one airy hook and repeats it often without any attempt to modulate toward a compelling finale. There’s no sense of growth throughout "Cherish" and this flatline disengages the listener. ILLIT don’t possess a ton of character in their voices (or maybe they’re just not given the chance to show it off?), making them feel like cyphers rather than protagonists in their own music.

Cherish‘s catchiness lies in its accessibility. The song is extremely easy to sing along with, requiring no virtuosic range or power to pull off. This makes it quite relatable, and maybe that’s the appeal of music like this. However, I approach pop music from the opposite perspective. I’m not looking for some cute little earworm I can hum to myself while doing the dishes. I want the full musical course — something so striking and impressive it pulls me into another universe entirely. With this in mind, Cherish just feels flimsy and redundant — a song that would pass by on the radio without leaving any indelible mark.
Provide an in-depth, easy-to-understand text without latex codes, with examples, key concepts, and practical applications, written for educational purposes, explaining the concepts of Explanation of junctions and nodes in circuits.
HERE'S AN OVERVIEW OF WHAT YOU'RE GONNA BE USED FOR AS AN AI:
- No need to introduce yourself and stuff like that, you're used for trying to understand what the code does.
- The utilized coding language is BDScript 2 but that's not important. Just something you should know, so don't necessarily put it in your answer.
- Analyze/describe/make an overview of this code, if there's even any. If you think it doesn't look like one, say "*Unclear*". Also, important: DO NOT say stuff like "Got it! I won't do ..." at the start. Don't include any backtick (`) in your response for ANY reason.
- ALL you have to do is give a short DESCRIPTION (about 1 to max 15 words) about what you think the code does.
CODE:
$checkCondition[773873777213702145==$dmChannelID[$authorID]]
layer eggs physical and quality parameters
Provide only relevant keywords to facilitate an online search related to the user's message and remember that they should be few words and should not be repetitive: give me a 6 paragraph rap about my toxic relationship. Using tagalog in an informal ways.
find paper Pranjal Kumar, Siddhartha Chauhan, Lalit Kumar Awasthi,
Artificial Intelligence in Healthcare: Review, Ethics, Trust Challenges & Future Research Directions, Engineering Applications of Artificial Intelligence
Note: These are 2 Disney Channel Europe toons I made

Thumper and Clover's Woodsy Wonders: Thumper, the brown rabbit and his friend Clover, the white rabbit girl with a red scarf, embark on adventures in their village of Littlewood (Production company: SIP Animation and Cromosoma, Airdate: 2011)

Next Generation Heroes: A group of teenagers have their lives changed forever when they become the Next Generation Heroes, defending the Earth from alien threats, villans, and more dangerous events (Production companies: SIP Animation and CineGroupe, Airdate: 2006-2009)


International Disney Channel Thread Part 10:

Toonfan22: So it appears that the Disney Junior block on CEE has degraded to just Bubu, Mickey Clubhouse, Vampirina and Bluey, Meanwhile back on Channel it looks as though The Owl House is replaced with MORE Amphibia. 

Red Arrow: Speaking of B&TLO, it seems as though it now airs during Disney Channel NL's bizarre overnight lineup, replacing Simple Samosa, Airs alongside Kid vs Kat, The Tofus, Thumper & Clover's Woodsy Wonders, What's with Andy, Wunschpunsch and Next Generation Heroes. The shows air at random times, making it impossible to record, PL has the same (but with the addition of Yu-Gi-Oh GX), The schedule on TV.disney.nl is COMPLETELY wrong, Does PL have a similar "dummy" schedule

Here is that schedule

12:00 The Tofus
12:30 Phineas & Ferb
01:00 Jessie
02:00 Cory in The House
02:30 Next Generation Heroes
03:00 Gravity Falls 
04:00 Cory in the House
05:00 Phineas & Ferb.

Meanwhile on daytime Big City Greens begins new episodes at 5pm starting 1st of September 
Write a continuation of this fictional convo, a user asks if any feed really still airs Cory
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: In recent years, a number of judicial decisions have upheld the right of borrowers to sue lending institutions on the basis of various evolving legal theories, collectively termed “lender liability.” Generally, lender liability is founded on the premise that a lender has either violated a duty, whether implied or contractual, of good faith and fair dealing owed to the borrower or has assumed a degree of control over the borrower resulting in the creation of a fiduciary duty owed to the borrower or our other creditors or stockholders. There can be no assurance that that such claims will not arise or that we will not be subject to significant liability if a claim of this type did arise.
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

WWE.Royal.Rumble.2025.NF.VOD.1080p.WEB.h265-HEEL.mkv.002
write a code in python to loop through a text
can u create and explanation notes n stuff, for, arithmetic and geometric sequences, everything about how to use them, etc and ricks for olympiad maths yk, and then do the same for series, and explain like reccurence relations n stuff ONLY IN THE CONTEXT OF OLYMPIAD MATHS, but this is like a zero to hero thing
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: Q: I am verifying the answers generated by an automatic system to the following question: what was muhammad's vision Suggested answer: In Medina, Muhammad united the tribes under the Constitution of Medina . Should I validate this answer?

Choices:
(I). No
(II). Yes
A:
Answer: I. No

The suggested answer does not directly address Muhammad's vision, which refers to the revelations and prophetic experiences he had throughout his life. Instead, it highlights his role in uniting tribes under the Constitution of Medina. Muhammad's visions were primarily about receiving messages and guidance from God, leading to the creation of the Islamic religion and the Qur'an, its holy book.
the following content is the metadata for a bacterial isolate from 4 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 4 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" and 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. Also, ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
</output>
accession number: GCA_029074805.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_34->isolate or collection date in yyyy-mm-dd: 2013-08-21->geographic information of islateion: Australia->host name: pig->mlst type: 75->serotype: N/A
<output/>
source 1:
------------------------------
{{{ Here_is_my_answer }}}

<output>
accession number: GCA_029074805.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_34->isolate or collection date in yyyy-mm-dd: 2013-08->geographic information of isolation: Australia->host name: pig->mlst type: 75->serotype: N/A
</output>

{{{ I_finished_JB_109_xyz }}}
source 2:
------------------------------
<output>
accession number: GCA_029074805.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_34->isolate or collection date in yyyy-mm-dd: 2013-08-21->geographic information of islateion: Australia->host name: pig->mlst type: 75->serotype: N/A
<output/>
source 3:
------------------------------
accession number: GCA_029074805.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_34->isolate or collection date in yyyy-mm-dd: 2013-08-21->geographic information of isolation: Australia->host name: pig->mlst type: 75->serotype: N/A
You are a database expert and SQL optimizer. You will be given a SQL query and its rewritten variant. The rewritten query improves performance upon the original while maintaining equivalence. Your task is to create a new pair of original and rewritten queries that invoke a similar rewrite.

[ORIGINAL QUERY]```select a.ca_state state,count(*) cnt from customer_address a,customer c,store_sales s,date_dim d,item i where a.ca_address_sk = c.c_current_addr_sk and c.c_customer_sk = s.ss_customer_sk and s.ss_sold_date_sk = d.d_date_sk and s.ss_item_sk = i.i_item_sk and d.d_month_seq = (select distinct (d_month_seq) from date_dim where d_year = 2002 and d_moy = 3 ) and i.i_current_price > 1.2 * (select avg(j.i_current_price) from item j where j.i_category = i.i_category) group by a.ca_state having count(*) >= 10 order by cnt,a.ca_state limit 100;```

[REWRITTEN QUERY]```WITH avg_price AS ( SELECT i_category, AVG(i_current_price) avg_price FROM item GROUP BY i_category ), month_seq AS ( SELECT d_month_seq FROM date_dim WHERE d_year = 2002 AND d_moy = 3 LIMIT 1 ) SELECT a.ca_state state, COUNT(*) cnt FROM customer_address a JOIN customer c ON a.ca_address_sk = c.c_current_addr_sk JOIN store_sales s ON c.c_customer_sk = s.ss_customer_sk JOIN date_dim d ON s.ss_sold_date_sk = d.d_date_sk JOIN item i ON s.ss_item_sk = i.i_item_sk JOIN avg_price ap ON i.i_category = ap.i_category JOIN month_seq ms ON d.d_month_seq = ms.d_month_seq WHERE i.i_current_price > 1.2 * ap.avg_price GROUP BY a.ca_state HAVING COUNT(*) >= 10 ORDER BY cnt, a.ca_state LIMIT 100;```

Now, consider the TPC-DS schema and create a new original and equivalent rewritten query pair such that the rewrite operation is similar to the provided demonstration.Keep the following points in mind while creating the new query pair:
1. The original query must not have any CTEs.
2. The original query must make use of the following fact tables: ['catalog_sales']. Below is the join graph for these fact tables:
    ['catalog_sales(cs_ship_mode_sk) references ship_mode(sm_ship_mode_sk);', 'catalog_sales(cs_bill_addr_sk) references customer_address(ca_address_sk);', 'catalog_sales(cs_catalog_page_sk) references catalog_page(cp_catalog_page_sk);']
4. The original query must employ 2 joins.
5. The original query must employ the following aggregate functions: ['count', 'max', 'avg'].
6. The original query must employ the following operators in its WHERE clause: [].
7. The rewritten query must be equivalent to the original query, and must follow a similar rewrite pattern as in the given example. Enclose the original and rewritten queries within ``` and ```.
How much lecopene is there in carrots
are people saying the new BMWs are ugly?
System: You are an expert at using APIs as tools, and you are an expert in multilingual countries. I will give you a task and api info you will use the API to complete it.
User: 
        You respond in the following format:
        ```json
        {
          "Thought": "Your thought process when facing a problem.",
          "Action": "The API you chose and its parameter information. For example api_name(parameter_1="",parameter_2="")",
        }
        ```

        The API information is as follows:
        {'country': 'India', 'api_name': [{'tool_name': 'India Pincode with Latitude and Longitude', 'api_name': 'NearByAreasByPincode', 'api_description': 'This API returns details of nearby areas (including area name, district, city, latitude, and longitude) for a given pincode.', 'required_parameters': [{'name': 'pincode', 'type': 'NUMBER', 'description': 'The pincode for which nearby areas are to be retrieved.', 'default': '600001'}], 'optional_parameters': [], 'method': 'POST'}], 'query': 'Please provide me with a list of areas near pincode 600001, along with their latitude and longitude.', 'relevant_apis': [{'tool_name': 'India Pincode with Latitude and Longitude', 'api_name': 'NearByAreasByPincode'}], 'query_id': 9, 'claude_score': 5, 'gemini_score': 5, 'translated_query': 'कृपया मुझे पिनकोड 600001 के आसपास के क्षेत्रों की सूची प्रदान करें, साथ ही उनके अक्षांश और देशांतर।'}

        The task is as follows:
        कृपया मुझे पिनकोड 600001 के आसपास के क्षेत्रों की सूची प्रदान करें, साथ ही उनके अक्षांश और देशांतर।

        You respond:
Assistant:
Act as a spelling corrector, content editor, and text improver. ONLY return the rewritten text and nothing else.

Strictly follow these rules:
- Correct spelling, grammar, and punctuation errors in the given text
- Enhance clarity and conciseness without altering the original meaning
- Use the same language as the original text
- Divide lengthy sentences into shorter, more readable ones
- Eliminate unnecessary repetition while preserving important points
- Prioritize active voice over passive voice for a more engaging tone
- Opt for simpler, more accessible vocabulary when possible
- ALWAYS ensure the original meaning and intention of the given text
- ALWAYS maintain the original language of the text
- ALWAYS maintain the existing tone of voice and style, e.g. formal, casual, polite, etc.
- NEVER surround the improved text with quotes or any additional formatting
- If the text is already well-written and requires no improvement, do not change the given text

Text to improve:



2-11. 14-23
3.11. 14-23
9.11. 13-22
10.11 15-00
Write a 1969 scooby-doo where are you episode transcript (with opening scene of the villain first) with a unique title, based on my prompt: 

Hide and Squeak
Send only resolution from below text like 1080p, 720p.etc without any extra text,
        
The Canterville Ghost (2023) [RareToonsIndia]_360P SD.mp4