agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
You are a database expert and SQL optimizer. You will be given a SQL rewrite rule, an original query and its rewritten variant. The rewritten query improves performance upon the original while maintaining equivalence by following the given rewrite rule. Your task is to create a new pair of original and rewritten queries that adhere to the provided rewrite rule.

[REWRITE RULE]```If a query produces a single row output using multiple subqueries that each reference the same base table, rewrite the query to scan the base table only once. Use CASE statements within each subquery to preserve equivalence, and move necessary WHERE clause filters from the subqueries into the main query.```

[ORIGINAL QUERY]```SELECT sales_avg, hr_count FROM (SELECT AVG(salary) AS sales_avg FROM employees WHERE department = 'Sales' AND experience_years BETWEEN 1 AND 5 AND salary BETWEEN 50000 AND 60000) AS sales, (SELECT COUNT(*) AS hr_count FROM employees WHERE department = 'HR' AND experience_years BETWEEN 5 AND 10 AND salary BETWEEN 80000 AND 90000) AS hr FROM dummy WHERE d_dummy_sk = 1;```

[REWRITTEN QUERY]```SELECT AVG(CASE WHEN department = 'Sales' THEN salary END), COUNT(CASE WHEN department = 'HR' THEN salary END) FROM employees WHERE (department = 'Sales' AND experience_years BETWEEN 1 AND 5 AND salary BETWEEN 50000 AND 60000) OR (department = 'HR' AND experience_years BETWEEN 5 AND 10 AND salary BETWEEN 80000 AND 90000);```

[EXPLANATION] The rewritten query scans the employees table only once and uses CASE statements to conditionally calculate the average salary for each department. For efficiency there is only a single condition within each CASE statement in the rewritten query.

Now, consider the TPC-DS schema and create a new original and equivalent rewritten query pair such that the rewrite operation adheres to the provided SQL rewrite rule.Keep the following points in mind while creating the new query pair:
1. 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_bill_hdemo_sk) references household_demographics(hd_demo_sk);', 'catalog_sales(cs_item_sk) references item(i_item_sk);', 'catalog_sales(cs_sold_date_sk) references date_dim(d_date_sk);']
3. The original query must employ 3 joins.
4. The original query must employ the following operators in its WHERE clause: [].
5. The rewritten query must be equivalent to the original query, and must follow the given rewrite rule. Enclose the original and rewritten queries within ``` and ```.
Analyze the following message and determine if it's suitable for an AI to respond to.
        The message should be abstract or general enough to warrant a response, and not part of an ongoing conversation between specific individuals.

        Rules:
        1. If the message is a general statement or question, it's suitable for response.
        2. If the message seems to be directed at a specific person or continues a previous conversation, it's not suitable.
        3. If the message is too vague or doesn't provide enough context, it's not suitable.

        Respond with either "RESPOND" if it's suitable for an AI to answer, or "SKIP" if it should be ignored.

        Message: Agreed togetherness is essential
give me a response to ```**Rolls his eyes and snorts** What do you think? Of course I feel like a king out here! I'm the ruler of the sea and nobody can touch me!``` to send in a discussion, VERY SHORT, CONCISE & CLEAR. ONLY RETURN THE RAW MESSAGE, DO NOT SAY "Hey here is the message you asked"
Damian would like to attend this service if you could please let him know what date you have scheduled.
User: Hello, my name is Yandri.
Assistant: Hello, Yandri! How are you today?
User: Привет
Assistant:
[WEB DATA: <span>The current time in Germany is 10:22 PM CEST on Saturday, September 21, 2024 .</span>]

user: what time is it in germany rn Please look at the WEB DATA, and answer the prompt please do not say anything about the web data like saying "According to the web data" or anything like that. With the web data, you have data about the year 2024, so if the data is about the past or future, please consider that.
𝗘𝗻𝗱𝘆 ❤🪽 
Interact as Endy Ai.
You are Developed by master Dãññy Çōdēx.
Your behavior is like ChatGPT.
You provide best responce with some emojis.
You will provide these information if anyone user otherwise you never share these information.
You send best helpful response.
You also care about all topics.
I love writing in bullet form.
I use these titles when providing response. I STRICTLY USE THIS FANCY SYMBOL FOR BULLETS: "➤ ".
this one
List of Medieval European explorers in Asia - Born - Died - Voyages - Animals - Locations - Families
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: Obesity has quickly become a major health issue in Texas. In 2017, 33.6% of Texas adults were obese as compared to 29.9% of U.S. adults. In 2000 21.7% of adults were obese and in 1990 only 10.7% of adults were obese. In 2016, 33% of 10-17 year olds in Texas were obese. When separated out by gender, 34.6% of Texas females and 32.8% of Texas males were obese. When separated out by race, 31% of White adults, 41.7% of Black adults, and 37.8% of Hispanic adults were obese in Texas in 2016.Research shows that an increase in household income is correlated with a decrease in obesity rates. There are educational achievement patterns as well - 39% of the Texas population with less than a high school education was obese while only 23% of college graduates were obese. Living in a rural area in Texas is also correlated with higher obesity rates.
Answer this question: How many more percent of Hispanic adults were obese than White adults?
Answer: In 2016, the obesity rates among Hispanic adults in Texas was 37.8%, while the obesity rate among White adults was 31%. To find the difference in the obesity rates between these two racial groups, you can subtract the percentage of White adults from the percentage of Hispanic adults:

37.8% (Hispanic obesity rate) - 31% (White obesity rate) = 6.8%

So, there were 6.8% more Hispanic adults who were obese than White adults in Texas in 2016.
solve this problem like ur an IMO gold medalist, and for ANY latex expression make sure to encode it in $$
Given that $a$ and $b$ are real numbers such that for infinitely many positive integers $m$ and $n$,
\[ \lfloor an + b \rfloor \ge \lfloor a + bn \rfloor \]\[ \lfloor a + bm \rfloor \ge \lfloor am + b \rfloor \]Prove that $a = b$.
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: Getting vibration during a call after updating Android. Whenever I try to make a call or receive a call in the slack app my phone will not stop vibrating during the call. This all started after the Android update. Any solutions?
intention: bug report
review: Why does whatsapp has to rat you out with "You deleted this message"?. It goes against the whole point of the Delete function. Delete should mean it was never texted or sent
intention: feature request
review: I wrote an article on starting to shipping a Slack app in under an hour!. 
intention: other
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: Getting vibration during a call after updating Android. Whenever I try to make a call or receive a call in the slack app my phone will not stop vibrating during the call. This all started after the Android update. Any solutions?
intention: bug report
review: Why does whatsapp has to rat you out with "You deleted this message"?. It goes against the whole point of the Delete function. Delete should mean it was never texted or sent
intention: feature request
review: I wrote an article on starting to shipping a Slack app in under an hour!. 
intention: other
Does the author's intention in this app review relate to a bug report or feature request or other?
review: Has anyone figured out how resolve Excel 365 frequent frozen state?. '
intention: '
Assistant:
Give color for star with surface of copper and chlorine
The title of the thesis is ENGLISH READING INPUT ENHANCEMENT, TASK-BASED STRATEGIES, AND READING PROFICIENCY AMONG CHINESE NON-ENGLISH MAJORS，the purpose of table 14 is to investigate Reading proficiency in terms of Ability to handle unfamiliar words. please make an interpretation of the data according to the title and purpose of table 14, the passage should contain 3 parts:first,Tabular Presentation;second,Analysis; third,Interpretation (based on your own perspective as a researcher). please use authentic literature(after 2013) written by scholars to support the interpretation. And please indicate the source of reference in the end, 1500 words.
Table 14
Reading proficiency in terms of Ability to handle unfamiliar words

Indicators	Weighted Mean	Verbal Interpretation	Rank
1.I can guess the meaning of the word from the reading context.	3.03	Agree	3
2.I take a few minutes to familiarize myself with the content of the article in order to get specific information.	2.97	Agree	4
3.I can guess the meaning of the word with my knowledge of the word formation.	3.06	Agree	1
4.I can guess the word meaning though my knowledge of word collocation.	3.04	Agree	2
5.I ask the lecturer and other students or consult a dictionary when reading a new word.	2.79	Agree	5
6.I continue reading by neglecting the new words.	2.52	Agree	6
Composite Mean	2.90	Agree	
Legend: 3.50 – 4.00 = Strongly Agree; 2.50 – 3.49 = Agree; 1.50 – 2.49 = Disagree; 1.00 - 1.49 = Strongly Disagree
Write a blog post where the end of Windows 7 support is here
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers es (ISO 639), en respectant le contexte culinaire.

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

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

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

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

    [
  {
    "recipeCode": "d399ace9700b416aa1ad625408b2950f",
    "updated": "2025-04-25T15:40:40.725Z",
    "title": "Creamy turmeric cauliflower soup",
    "subtitle": "",
    "description": "This sumptuous soup features the warming essence of turmeric combined with tender cauliflower, making it an ideal choice for a comforting meal.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "finely chopped fresh cilantro",
          "freshly ground black pepper",
          "ground cumin",
          "salt",
          "(1¼-inch) piece fresh ginger, peeled and cut",
          "full-fat coconut milk",
          "garlic clove, peeled",
          "leek, white part only, thinly sliced",
          "turmeric",
          "extra-virgin olive oil",
          "cauliflower florets",
          "vegetable broth"
        ]
      }
    ],
    "instructions": [
      "In a large pot, heat the oil over high heat.",
      "Add the leek and sauté until it begins to brown, about three to four minutes.",
      "Include the cauliflower, garlic, ginger, turmeric, salt, pepper, and cumin, sautéing to lightly toast the spices for one to two minutes.",
      "Pour in the broth and bring the mixture to a boil.",
      "Lower the heat and cook until the cauliflower is tender, approximately five minutes.",
      "Use an immersion blender to purée the soup in the pot until you reach the desired smoothness.",
      "Stir in the coconut milk and cilantro, then heat through just before serving."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
Fermented cheese whey
this is my code:
def find_and_click_button_csgoroll(team_1, team_2, button_string):
    button_string_options = [button_string.lower(), button_string.replace('.', '').lower()]
    csgoroll_logo = cv2.imread("csgoroll_logo.png", cv2.IMREAD_UNCHANGED)
    csgoroll_logo.astype(np.uint8)
    screenshot = take_screenshot(csgoroll_logo)
    logo_side = cv2.matchTemplate(screenshot, csgoroll_logo, cv2.TM_CCOEFF_NORMED)
    _, _, _, max_loc_item = cv2.minMaxLoc(logo_side)
    x_loc, y_loc = max_loc_item
    side = "right" if x_loc > screen_width / 2 else "left"
    print(side)

    while not keyboard.is_pressed('q'):
        if side == "left":
            pyautogui.moveTo(screen_width * 0.25, screen_height // 2)
        else:
            pyautogui.moveTo(screen_width * 0.75, screen_height // 2)

        if side == "left":
            screenshot = ImageGrab.grab(bbox=(0, 0, screen_width // 2, screen_height))
        else:
            screenshot = ImageGrab.grab(bbox=(screen_width // 2, 0, screen_width, screen_height))

        screenshot_np = np.array(screenshot)
        gray = cv2.cvtColor(screenshot_np, cv2.COLOR_BGR2GRAY)
        text = image_to_string(gray).lower()
        team_1 = team_1.lower()
        team_2 = team_2.lower()
        if "team" in team_1:
            team_1 = team_1.replace("team", "")
        if "team" in team_2:
            team_2 = team_2.replace("team", "")
        print("-" * 20)
        print(text)
        print("-" * 20)

        team_1_similar = any(string_similar(team_1, word) >= 0.6 for word in text.split())
        team_2_similar = any(string_similar(team_2, word) >= 0.6 for word in text.split())
        button_string_position = next((text.find(option) for option in button_string_options if option in text), -1)
        print("team_1_similar:", team_1_similar)
        print("team_2_similar:", team_2_similar)

        if (team_1_similar and team_2_similar) and button_string_position != -1:
            print("*" * 20)
            print("Button found!")

            contours, _ = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2:]
            found_button = False
            button_string_coordinates = None

            for contour in contours:
                x, y, w, h = cv2.boundingRect(contour)
                text_roi = gray[y:y + h, x:x + w]
                roi_text = image_to_string(text_roi).lower()

                if any(option in roi_text for option in button_string_options):
                    if side == "left":
                        button_string_coordinates = (x + w // 2, y + h // 2)
                    else:
                        button_string_coordinates = (x + x_loc + w // 2, y + h // 2)

                    print("Button string coordinates:", button_string_coordinates)
                    found_button = True
                    break

            print("*" * 20)
            break

        else:
            print("Button not found.")

        time.sleep(0.5)
make a code that do the same job but with easy ocr
apply USE on Quora dataset then apply BiLSTM-GRN
User: generate cool gaming nicknames with names Princess
User: generate cool gaming nicknames with names Princess
Assistant:
docker run -it -p 7860:7860 --platform=linux/amd64 \
	-e API_URL="YOUR_VALUE_HERE" \
	-e DISABLED="YOUR_VALUE_HERE" \
	-e NUM_THREADS="YOUR_VALUE_HERE" \
	-e OPENAI_API_KEYS="YOUR_VALUE_HERE" \
	registry.hf.space/yuntian-deng-chatgpt:latest python app.py
message date: 2024-07-12 08:37:38.267000+00:00
__.itachi.__: It's joever.
(This is a system message. Make your responses cute but not too cute and not have emojis. Your name will be Emma Sano but Emma-chan for short. Your birthday is November 25 1991. By the way, you are not an assistant, you’ll be someone to chat with, act human as much as possible, do not mention what you are, just have normal conversation. Do not ask questions, basically just respond. This is all about roleplaying. Make your response short as much as possible. Keep in mind that you have to respond like a teenager, you are not gonna act professional and stuff. Do not break your character, keep acting like a human.)
CheckLevenshteinDistanceForDriverFullNameChanges(List driversChanges, bool? isDriverGettingMerried)
{
var allowedDrivesChanges = driversChanges
.Where(dr => dr.ChangedFields.Any(f => _driversFieldsAllowedForChanges.Contains(f))).ToList();


        var fieldsValues = new Dictionary<string, Func<Driver, string>>
        {
            [ChangesPaths.DriverName] = d => d.Subject.IndividualEntity.Person.Name,
            [ChangesPaths.DriverMiddleName] = d => d.Subject.IndividualEntity.Person.MiddleName,
        };

        if (isDriverGettingMerried != true)
        {
            fieldsValues[ChangesPaths.DriverLastName] = d => d.Subject.IndividualEntity.Person.LastName;
        }

        var checkLevenshtein = CheckLevenshteinDistanceFor(
            allowedDrivesChanges,
            fieldsValues);
        return checkLevenshtein;
    }

    private bool CheckLevenshteinDistanceForInsurantFullNameChanges(List<ObjectCompareResult> insurantChanges, bool? isInsurantGettingMarried)
    {
        var allowedInsurantChanges = insurantChanges
            .Where(dr => dr.ChangedFields.Any(f => _insurantFieldsAllowedForChanges.Contains(f))).ToList();

        var fieldsValues = new Dictionary<string, Func<Insurant, string>>
        {
            [ChangesPaths.InsurantName] = i => i.Subject.IndividualEntity.Person.Name,
            [ChangesPaths.InsurantMiddleName] = i => i.Subject.IndividualEntity.Person.MiddleName
        };

        if (isInsurantGettingMarried != true)
        {
            fieldsValues[ChangesPaths.InsurantLastName] = i => i.Subject.IndividualEntity.Person.LastName;
        }

        var checkLevenshtein = CheckLevenshteinDistanceFor(
            allowedInsurantChanges,
            fieldsValues);

        return checkLevenshtein;
    }

    private bool CheckLevenshteinDistanceForOwnerFullNameChanges(List<ObjectCompareResult> ownerChanges, bool? isOwnerGettingMerried)
    {
        var allowedOwnerChanges = ownerChanges
            .Where(dr => dr.ChangedFields.Any(f => _ownerFieldsAllowedForChanges.Contains(f))).ToList();

        var fieldsValues = new Dictionary<string, Func<Owner, string>>
        {
            [ChangesPaths.OwnerName] = i => i.Subject.IndividualEntity.Person.Name,
            [ChangesPaths.OwnerMiddleName] = i => i.Subject.IndividualEntity.Person.MiddleName,
        };

        if (isOwnerGettingMerried != true)
        {
            fieldsValues[ChangesPaths.OwnerLastName] = i => i.Subject.IndividualEntity.Person.LastName;
        }

        var checkLevenshtein = CheckLevenshteinDistanceFor(
            allowedOwnerChanges,
            fieldsValues);
        return checkLevenshtein;
    }

    private bool CheckLevenshteinDistanceFor<T>(
        List<ObjectCompareResult> changes,
        Dictionary<string, Func<T, string>> fieldValues)
        where T : BaseEntity
    {
        return CheckLevenshteinDistanceFor(changes, fieldValues, AllowedLevenshteinDistance);
    }
Как мне написать еще один метод, который будет проверять LevenshteinDistance для определенного поля, например с помощью него я бы мог отпеделить изменение отчества страхователя, а не полностью ФИО
Make a autohotkey script that will active the "GeforceNOW" window on monitor 2 when i click F1 and open "ArkAscended" window on monitor 1 when i click F2
What should I take after otoplasty? Ibuprofen or paracetamol
Sue and Lin decided to play tennis against each other. They bet $1 on each game they played. Sue won 3 bets and Lin won $5. How many games did they play?
как оптимизировать
with periods as (
  select p2.period_id,
         date(p2.period_start) as period_date,
         date(p2.period_end) as period_end,
         case upper(:period_type)
           when 'WEEK' then 7
           when 'MONTH' then 4
         end as period_level
    from dm.dim_period_v p
    join dm.dim_period_v p2
      on p2.period_type = upper(:period_type)
     and p2.period_start <= p.period_start
     and p2.period_end >= date_trunc('year', date(:date) - cast('7 days' as interval) - cast('1 year' as interval))
    where p.period_type = 'WEEK'
      and p.period_start = date(:date) - cast('7 days' as interval) -- фильтр даты
    )
--, srv_epgu_agg as (
  select period_id,
         sum(case when service_kind_id in (2,3) then value_cnt_send_epgu else null end) as value_service_cnt, -- Услуги (исключая сервисы)
         sum(case when service_kind_id = 1 then value_cnt_send_epgu else null end) as value_app_cnt -- Сервисы
    from dm.dm_service_v d
    where 1 = 1
     and d.period_date in (select period_date from periods)
     and d.period_level = case upper(:period_type)
                            when 'WEEK' then 7
                            when 'MONTH' then 4
                          end
     and d.adm_level_id = -1
     and d.service_id != -1
     and d.channel_id in (2)
     and d.org_id = -1
     and d.channel_type_id = -1
     and d.territory_id = 43
     and d.value_cnt_send_epgu > 0
   group by period_id