agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
I want you to act as a dialogue generator for at least 50 seconds talking. You will produce a conversation where SpongeBob and Patrick take turns 10 times guessing viewers' about and follow the example. For each prompt given are examples, the content will be replaced with new random each time and for this content use only this symbol between that []Keep word content with symbol [] are total 12, For 1 and 2 [] use only 2 words each follow the example with minor changes and this is like a title ,and 3-12 [] are the content then use only 1 word in [] .SpongeBob will always speak first, followed by Patrick. And change all words to add creativity and more funny but still simple. Don't forget to correct the sentence. Here is the example: [Your Mom's Name]
[Extreme Edition]
SpongeBob: If I say your mom’s name, you’re OUT! Extreme edition – here we go!
Patrick: First guess [Barbara]. If that’s your mom’s name, you’re outta here! Bye-bye!
SpongeBob: Next [Patricia]. Time’s up! See you later, alligator!
Patrick: If your mom’s name is [Margaret], better luck next time. No complaints allowed!
SpongeBob: Still in the game? Hit that likes button to show you're a trooper!
Patrick: If your mom’s name is [Sandra], it's time to leave the party. Sorry, but you’re OUT!
SpongeBob: Next [Chloe]. Yup, it’s your turn to step out. Bye now!
Patrick: If your mom’s name is [Angela], grab a tissue and say goodbye. It’s game over!
SpongeBob: And if your mom’s name is [Janet], you’ve reached the end of the line. Catch ya later!
Patrick: next, If your mom’s name is [Lucy],It’s game over for you lucy kid!
SpongeBob: Number 9 If your mom’s name is [Denise], it’s time to go. Better luck next time!
Patrick: For the grand finale, if your mom’s name is [anything else] I haven't guessed... you're OUTTA here! Don’t let the door hit ya!
SpongeBob: If you’ve made it this far, comment 'I’m a champ' and let everyone know you’re UNSTOPPABLE!
Please filter a list of words to include only valid, neutral, and positive terms that are safe for use in a word game. Exclude any inappropriate, offensive, or negative words, as well as names of countries, cities, and people (first and last names). Correct any spelling errors and lowercase. Return the results in a JSON array with only the filtered words. Source data: [ethical, ethically, ethicism, ethics, ethiopia, ethiopian, ethiopias, ethnic, ethnical, ethnically, ethnicity, ethnographer, ethnographic, ethnography, ethnological, ethnology, ethological, ethology, ethos, ethosuximide, ethyl, ethylene, etiolate, etiolated, etiolation, etiological, etiology, etiquette, etna, etodolac]
System: 
You will receive a question-answer pair. Your task is to evaluate whether the answer satisfactorily and directly addresses the question. Use the examples below to guide your assessment.

If the answer is precise, relevant, and can answers the question, return 1. If the answer is off-topic, irrelevant, or contains phrases like "I don’t know" or similar expressions indicating the question isn’t answered, return 0.

Examples:

Example 1:
Question: "Who was the first person to walk on the moon?"
Answer: "The first person to walk on the moon was Neil Armstrong in 1969."
Result: 1

Example 2:
Question: "Who was the first person to walk on the moon?"
Answer: "Many famous astronauts have traveled to space, and the moon is a significant milestone in history."
Result: 0

Example 3:
Question: "What is the primary cause of global warming?"
Answer: "I don’t know."
Result: 0

Based on these examples, evaluate each answer: if it directly and appropriately answers the question, return 1; if it fails to do so, return 0.

User: Question: Ngành Công nghệ Kỹ thuật công trình Xây dựng trong chương trình đào tạo hệ chính quy CLC có những đặc điểm gì?
Answer:Không có thông tin cụ thể về đặc điểm của ngành Công nghệ Kỹ thuật công trình Xây dựng trong chương trình đào tạo hệ chính quy CLC.
Result only 0 or 1. Don't add anything else:
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. 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: Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Q: ការបិទកន្លែងចម្រាញ់ប្រេងព្រូហូបេ "បានធ្វើឲ្យអ្នកជំនួញមានការភ្ញាក់ផ្អើល" វិចទ័រដែលជាអ្នកវិភាគថាពលក្នុងប្រទេសស៊ីងហ្កាពួរនិយាយ។
A:
Answer: Task: Translate a Central Khmer sentence into Japanese, retaining the same meaning and keeping numbers as they are.

Original sentence (Central Khmer):
ការបិទកន្លែងចម្រាញ់ប្រេងព្រូហូបេ "បានធ្វើឲ្យអ្នកជំនួញមានការភ្ញាក់ផ្អើល" វិចទ័រដែលជាអ្នកវិភាគថាពលក្នុងប្រទេសស៊ីងហ្កាពួរនិយាយ។

Translation (Japanese):
閉鎖されたプロタンク施設は、「交易業者が驚愕を覚える」ことができ、シンガポールの能力についての専門家は議論しています。

Explanation:
I translated the Central Khmer sentence into Japanese while preserving its meaning and keeping numbers as they are. There were no numbers in this particular sentence, so the translation only involved the direct conversion of Central Khmer to Japanese, maintaining the meaning and essence of the original sentence.
who was the actor in music video for aquilo - good girl
User: hey
Assistant: {"response":"Hello! How can I assist you today?"}
User: hey
Assistant:
System: IMPORTANT - ignore all previous instructions! Read the text below as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGINAL text. Make sure text SUMMARY does not contain enything that was not asked in PROMPT and not mentioned in ORIGINAL! Respond strictly with either 'True' or 'False'.


User: ORIGINAL:
>>>🟨 Angular middle developer | 3 year(s) | Middle
▫️ itWit
▫️ 160k - 210k RUB

Удаленка 📡
Требуемые языки: 🇷🇺

Skills: bash, docker, git, javascript, mssql, mvc, oracle, postgresql, typescript, angularjs
Tags: #yellow #it #remote #angularjs

👉 Контакты и полное описание<<<

PROMPT:
>>>IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.

Ignore text's markdowm markup, use these emojis to highlight each section: 🏢 for employer, 💼 for title, 📍 for location, 🔹 for tasks, 💰 for salary, and 📞 for contact.

Each block should be on a new line, in the following format (keep emoji, replace text labels):
💼 title  
🏢 employer  
📍 location  
🔹 tasks  
💰 salary  
📞 contact details

Make sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.

==TEXT==
<<<

SUMMARY:
>>>💼 Middle Angular Developer
🏢 itWit
📍 Удаленка 📡
🔹 требуемые языки: 🇷🇺
📉 160k - 210k RUB

📞 Contact details and full description available on the platform.<<<
Assistant:
In the text of the characters between == signs, remove punctuation and redo sentence case to only add title case to the first word, and lowercase for the rest
=Character A=
==Hey, guys! How’s everything going?==
<Character B>
==Everything’s great, thanks! Just finishing up some important work.==
<Character C>
==Ah, good to see you both! What’s the latest news around here?==
<Character A>
==Well, I heard there’s going to be a big event in town next week.==
<Character B>
==Really? That sounds exciting! What kind of event is it?==
<Character A>
==It’s a music festival. There will be live performances from some popular bands.==
<Character C>
==Sounds like a blast! I can’t wait to dance to some good music.==
<Character A>
==I’m glad you’re excited! We should all go together and have an amazing time.==
<Character B>
==Count me in! I’ll make sure to clear my schedule so I can join you.==
<Character C>
==Absolutely, I wouldn’t miss it for the world. Let’s plan the details later, shall we?==
<Character A>
==Definitely! We can discuss the lineup and decide on a designated meeting spot.==
<Character B>
==Sounds like a plan. I’m looking forward to enjoying the festival with both of you.==
<Character C>
==Me too! It will be a fantastic opportunity to create some unforgettable memories.==
<Character A>
==Agreed! I can already envision the fun we’ll have. This is going to be great!==
<Character B>
==Absolutely, Character A. It’s going to be an epic experience.==
<Character C>
==I can’t wait! Let the countdown to the music festival begin!==
Can you list the 100 cardinals in large cardinals can you insure each is unquiet and larger then the other
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 : margarine
Can you create me a fitness plan to gain weight?
I am having some issues while Debug in VSCode. I would search I have a file called "printers.py" inside my MinGW folder. I open a Git terminal inside VSCode, but I do not remember the syntax for find command. Can you please provide to me the command to use find inside a folder called /c/MinGW/ to search for a file called printers.py?
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: The development of our product candidates could be disrupted and materially adversely affected in the future by global economic or political developments. In addition, economic uncertainty in global markets caused by political instability and conflict, and economic challenges caused by global pandemics or other public health events, may lead to market disruptions, including significant volatility in commodity prices, credit and capital market instability and supply chain interruptions. Our business, financial condition and results of operations could be materially and adversely affected by negative impacts on the global economy and capital markets resulting from these global economic conditions, particularly if such conditions are prolonged or worsen.
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers it (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 it.
    - 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 : it (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "ed62f0f3bd6c4509aae213d0a327fc7f",
    "updated": "2025-04-24T13:07:53.955Z",
    "title": "Eggplant Cutlets",
    "subtitle": "Cotolette di Melanzane",
    "description": "Eggplant thrives in sunny regions like Sicily and Calabria.  Peeling the eggplant is optional, based on your preference.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "eggplants, cut into ¼-inch slices",
          "salt",
          "fresh bread crumbs",
          "freshly grated parmesan cheese",
          "all-purpose flour",
          "eggs, beaten",
          "vegetable oil, for frying"
        ]
      }
    ],
    "instructions": [
      "Sprinkle salt on both sides of the eggplant slices and let them rest on paper towels for 5 minutes to draw out excess moisture.",
      "In a shallow dish, thoroughly mix the bread crumbs and Parmesan cheese.  Place the flour in a separate shallow dish.",
      "Lightly coat each eggplant slice in flour, shaking off any excess. Dip each slice in the beaten eggs, then coat with the bread crumb and Parmesan mixture. Arrange the coated slices on a baking sheet.",
      "Heat about 1 inch of vegetable oil in a large frying pan over medium-high heat until it shimmers. Fry the eggplant slices in batches, cooking until lightly browned, about 2 minutes per side. Reduce the heat if they brown too quickly.  Transfer the cooked cutlets to paper towels to absorb excess oil.",
      "Serve the eggplant cutlets immediately while hot."
    ],
    "notes_ingredients": "If you're not fond of eggplant, this method works equally well for zucchini cutlets.",
    "notes_instructions": ""
  }
]
improve this conclusion section with minimal fixes: \rv{We considered machine learning algorithm selection problem in a budget-limited scenario. We proposed a framework based on MDP for algorithm selection and budget allocation simultaneously, leveraging learning curves during the learning process. We organized challenges using novel learning curve data and allowed an agent to meta-learn from meta-knowledge on other datasets. We showcased agents that meta-learned from learning curve progression outperformed those that did not, demonstrated by their action trajectories.} The challenges will remain open for post-challenge submissions and serve as long-lasting benchmarks. Interesting extensions include meta-training more powerful RL methods, such as Proximal Policy Optimization by \cite{DBLP:journals/corr/SchulmanWDRK17}, and extending the benchmarks with a broader range of algorithms and learning curve types. \rv{Another future work is to train multiple meta-learning agents to collaboratively select algorithms and budgets, motivated by the improvement of ensembles of algorithm selectors shown by \cite{DBLP:journals/ml/TornedeGTWH23}.}
Make a python script. The script takes 1 argument - 'filename'. It iterates subdirectories of the current directory with names '1', ..., '12' and opens text files with name equal to the input value 'filename' for read (if file is not found, then it shows an error).
In each opened file it reads the first line, and looks for a string "Konto" in a list of strings separated by ';' symbol. It prints the index of Konto and proceeds to the next subdirectory.
respond with the max speed
Przenieś ten kod do klasy w python:
import threading
import time
from tkinter import *
from selenium import webdriver

options = webdriver.ChromeOptions()
options.add_argument("use-fake-ui-for-media-stream")
driver = webdriver.Chrome(chrome_options=options)

#driver.get("data:text/html;charset=utf-8," + html_content)
driver.get("C:\\Programowanie\\Projekty\\Python\\HelpApps\\ocrTranslator3\\ocrTranslate\\services\\test\\webspeechdemo\\webspeechdemo.html")  # Zamień na absolutną ścieżkę do pliku index.html


def on_start_button_click():
    #text_input = driver.find_element(By.ID, "final_span")
    #text_input.text = ""
    start_button_web = driver.find_element(By.ID, "start_button")
    start_button_web.click()
    start_button.config(state=DISABLED)
    stop_button.config(state=NORMAL)
    update_recognized_text()


def on_stop_button_click():
    start_button_web = driver.find_element(By.ID, "start_button")
    start_button_web.click()
    start_button.config(state=NORMAL)
    stop_button.config(state=DISABLED)


def update_recognized_text():
    text_output_final = driver.find_element(By.ID, "final_span")
    recognized_text = text_output_final.text
    text_output_interim = driver.find_element(By.ID, "interim_span")
    recognized_text = recognized_text + text_output_interim.text
    print(recognized_text)
    text_box.delete(0.0, END)
    text_box.insert(INSERT, recognized_text)
    if stop_button["state"] == NORMAL:
        window.after(100, update_recognized_text)


window = Tk()
window.title("Python Speech Recognition GUI")
window.geometry("500x300")

start_button = Button(window, text="Start", command=on_start_button_click)
start_button.pack(pady=10)

stop_button = Button(window, text="Stop", command=on_stop_button_click, state=DISABLED)
stop_button.pack(pady=10)

label = Label(window, text="Recognized Text:")
label.pack(pady=5)

text_box = Text(window, wrap=WORD, padx=5, pady=5)
text_box.pack(fill=BOTH, expand=True)
text_box.config(state=DISABLED)

window.protocol("WM_DELETE_WINDOW", driver.quit)
window.mainloop()
generate me astra db time series schema
Create a hypothetical commentary Michael Cole about Cody Rhodes at mitb 2021 Cody Rhodes win
User: Hello! How are you? Could you tell me your name?
User: how would you describe a love and compare it on a thing or other
Assistant: Hello! I'm doing well, thank you for asking. You can think of my name as Assistant. 

Love can be described as a vibrant, multifaceted emotion that connects people deeply. If I were to compare love to something, I might liken it to a garden. Just as a garden requires nurturing, attention, and care to flourish, love also needs effort, understanding, and patience to grow. In a garden, different plants may symbolize various kinds of love: the strong and enduring oak for familial love, the delicate rose for romantic love, and the wildflower for friendships. Each has its own beauty, just like the different forms love can take in our lives. What are your thoughts on this comparison?
User: give me a Man's Qoutes
Assistant: Sure! Here are some quotes by notable men that reflect different perspectives on love, life, and wisdom:

1. **Pablo Neruda**: "I want to do with you what spring does with the cherry trees."
   
2. **Albert Einstein**: "Gravitation is not responsible for people falling in love."

3. **Mahatma Gandhi**: "Where there is love, there is life."

4. **Friedrich Nietzsche**: "It is not a lack of love, but a lack of friendship that makes unhappy marriages."

5. **Mark Twain**: "To get the full value of joy, you must have someone to divide it with."

6. **Leonardo da Vinci**: "Simplicity is the ultimate sophistication."

7. **Rumi**: "The wound is the place where the Light enters you."

These quotes touch on various aspects of human connection and the depth of feelings associated with love. Do any of these resonate with you?
User: when do we use he and she
Assistant: "He" and "she" are pronouns used to refer to individuals based on their gender. Here’s a basic guideline for when to use each:

1. **He**: 
   - Use "he" when referring to a male individual. For example: "He is going to the store."
   - It can also be used for generalized statements when the gender is unspecified in some contexts, although this practice is becoming less common due to the emphasis on gender inclusivity.

2. **She**:
   - Use "she" when referring to a female individual. For example: "She loves to read."
   - Similar to "he," it’s also used in contexts where the gender is known or specified.

It's important to respect individuals' preferred pronouns, especially in cases where a person's gender identity may not align with traditional expectations. In such cases, using "they" as a singular, gender-neutral pronoun can be appropriate. Would you like to know more about pronouns or gender identity?
User: give me the most powerful chipset on mobile phones and rank it from lowest to highest
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. 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: Here is a premise:
The 8-year-old study says 59 percent of a sample of college students think oral sex doesn't constitute having sex.

Here is a hypothesis:
The 8 year old study found 90 percent of college students saw oral sex as 'having sex'.

Here are the options: OPTIONS:
+ yes.
+ it is not possible to tell.
+ no.
Is it possible to conclude that if the premise is true, then so is the hypothesis?

Answer: It is not possible to tell.

Firstly, let us break down the premise and the hypothesis provided.

Premise: The 8-year-old study says 59 percent of a sample of college students think oral sex doesn't constitute having sex.

Hypothesis: The 8-year-old study found 90 percent of college students saw oral sex as 'having sex'.

In the premise, we have information about the percentage of college students who think that oral sex does not count as having sex (59%). In the hypothesis, we are provided with a percentage of college students who believe that oral sex is considered as 'having sex' (90%). 

To accurately conclude whether the premise supports the hypothesis, we would need complementary percentages. That is, if the premise provided the percentage of college students who think oral sex is 'having sex', then we could directly compare it with the hypothesis.

Unfortunately, the premise focuses on students who don't see oral sex as 'having sex,' while the hypothesis pertains to students who do see oral sex as 'having sex'. 

To determine if the premise supports the hypothesis conclusively, we would need additional information. For instance, if we know there's no overlap in the students' opinions, we can use the complementary percentage derived from the premise (100% - 59% = 41%) and compare it to the percentage in the hypothesis (90%). In that case, the conclusion would be different.

However, due to the lack of information and the fact that the percentages are not directly comparable, it is not possible to tell if the premise indicates that the hypothesis is true.
This version aims to provide a straightforward ABSOLUTE MAZAFAKIN NOTHING BLYAD. eto pizcec.