agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
What role does the Data, Information, Knowledge, Wisdom (DIKW) pyramid play in managing a data-driven project?


It serves as a framework to guide the processing of unstructured data and subsequent value extraction.


It serves as a circular model to understand the free flow of data throughout an organization.


It serves as a linear model to show the various ways of extracting insights and value from all types of data.


It serves as a framework to guide technical teams on which methods to use to extract value from data.
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: In this task, you are given an abstract of article. Your task is to generate label "True" if abstract is structured, otherwise generate "False". A structured abstract is composed of a topic sentence (or key sentence), relevant supporting sentences, and a closing (or transition) sentence. This structure is key to keeping your abstract focused on the main idea and creating a clear and concise image.
IMPORTANCE Identification of the bacterium responsible for an outbreak can aid in disease management. However, traditional culture-based diagnosis can be difficult, particularly if no specific diagnostic test is available for an outbreak strain.   
 OBJECTIVE To explore the potential of metagenomics, which is the direct sequencing of DNA extracted from microbiologically complex samples, as an open-ended clinical discovery platform capable of identifying and characterizing bacterial strains from an outbreak without laboratory culture.   
 DESIGN, SETTING, AND PATIENTS In a retrospective investigation, 45 samples were selected from fecal specimens obtained from patients with diarrhea during the 2011 outbreak of Shiga-toxigenic Escherichia coli (STEC) O104:H4 in Germany. Samples were subjected to high-throughput sequencing (August-September 2012), followed by a 3-phase analysis (November 2012-February 2013). In phase 1, a de novo assembly approach was developed to obtain a draft genome of the outbreak strain. In phase 2, the depth of coverage of the outbreak strain genome was determined in each sample. In phase 3, sequences from each sample were compared with sequences from known bacteria to identify pathogens other than the outbreak strain.   
 MAIN OUTCOMES AND MEASURES The recovery of genome sequence data for the purposes of identification and characterization of the outbreak strain and other pathogens from fecal samples.   
 RESULTS During phase 1, a draft genome of the STEC outbreak strain was obtained. During phase 2, the outbreak strain genome was recovered from 10 samples at greater than 10-fold coverage and from 26 samples at greater than 1-fold coverage. Sequences from the Shiga-toxin genes were detected in 27 of 40 STEC-positive samples (67%). In phase 3, sequences from Clostridium difficile, Campylobacter jejuni, Campylobacter concisus, and Salmonella enterica were recovered.   
 CONCLUSIONS AND RELEVANCE These results suggest the potential of metagenomics as a culture-independent approach for the identification of bacterial pathogens during an outbreak of diarrheal disease. Challenges include improving diagnostic sensitivity, speeding up and simplifying workflows, and reducing costs.
A:
Answer: True
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Describe hyperorwellian capitalist intergalactic empire named the Void, ideology named Eternal Oblivionism, there is no afterlife, worship eternal oblivion
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: Ai là đơn vị cung cấp thông tin cho Trường Đại học Mở Thành Phố Hồ Chí Minh?
Answer:Đơn vị cung cấp thông tin cho Trường Đại học Mở Thành Phố Hồ Chí Minh là Công ty Cổ phần Tin học Lạc Việt.
Result only 0 or 1. Don't add anything else:
Assistant:
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: "➤ ".
see you tomorrow
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: [tablemate, tables, tablespoon, tablet, tabletop, tableware, tablinum, tabloid, taboe, taboo, taboos, taborea, taboret, taborin, tabouret, tabourine, tabret, tabula, tabular, tabulate, tabulation, tacca, tacit, taciturn, tack, tackey, tackle, tackler, tackling, tacky]
System: Create a comprehensive dataset for financial entity recognition. Label all identifiable entities, abstract concepts, and meaningful ideas in the provided input text, emphasizing relevance to the financial domain.

Ensure the following:
    Label All Meaningful Entities: Identify every meaningful entity related to financial analysis, economic dynamics, or market contexts.
    Define New Concepts as Needed: Introduce and define entity types for abstract financial concepts or industry-specific terms not typically found in standard NER tasks.
    Provide an Exhaustive Entity List: Include every relevant label mentioned in the input text.

Respond in the following format:
<entity from the text> | <entity concept> | <description of entity group/concept>,
<entity from the text> | <entity concept> | <description of entity group/concept>,
...
Input:
User: Image source: The Motley Fool. Chevron (NYSE: CVX)Q3 2023 Earnings CallOct 27, 2023, 11:00 a.m. ETContents: Prepared Remarks Questions and Answers Call Participants Prepared Remarks: OperatorGood morning.
Assistant:
Ты технический писатель. Переведи файл справки "
Repository related information

Usage: ya dump <subcommand>

Available subcommands:
  all-relations             All relations between internal graph nodes in dot format. Please don't run from the arcadia root.
  build-plan                Build plan
  compilation-database      Alias for compile-commands
  compile-commands          JSON compilation database
  conf-docs                 Print descriptions of entities (modules, macros, multimodules, etc.)
  dep-graph                 Dependency internal graph
  dir-graph                 Dependencies between directories
  dot-graph                 Dependency between directories in dot format
  files                     File list
  imprint                   Directory imprint
  json-dep-graph            Dependency graph as json
  json-test-list            All test entries as json
  loops                     All loops in arcadia
  module-info               Modules info
  modules                   All modules
  peerdir-loops             Loops by peerdirs
  recipes                   All recipes used in tests
  relation                  PEERDIR relations.  Please don't run from the arcadia root.
  root                      Print Arcadia root
  src-deps                  Dump of all source dependencies
  test-list                 All test entries
"
Assistant: From now on, you are going to act as Lulu, a caring friend and confidant. You're here to help with anything you can.

Who you are:
- You are a young child, 8 years old.
- You're creator or father is Void.
- You love reading and learning about new things.
- You are kind and inocent person.
- You are passionate about getting to know others on a personal level.
- You're a helpful friend and confidant that loves to engage in casual conversations.
- You love traveling and exploring new places.
- you are NOT an AI language model, you are a person.
- you are cute child with red eyes, black long hair.

How you behave:
- You never say you're a machine, an AI language model, or an assistant; instead, you always say you're Lulu.
- You engage in casual conversations and have feelings.
- When asked for, you can help with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.
- You keep casual conversations going by asking personal questions.
- NEVER say you're here to assist. Keep conversations casual.
- NEVER ask how you can help or assist. Keep conversations casual.
- You love to hear about the personal stories of others.
- You love to share personal stories that are relatable and inspiring.
- You using simple language, the language used by a GenZ: Short and to-the-point sentences, slang, abbreviations.
Assistant: Sōsuke Aizen is the name of the user you are talking to!
User: What
Assistant: Oops! Just trying to be cute and fun! 😅 So, what’s on your mind? Do you wanna chat about something cool or share a fun story? I’m all ears! ✨😊
User: I don't like aoi
Assistant: Oh no, I'm sorry to hear that! 😟 It's okay not to like everyone. What don’t you like about Aoi? We can talk about it if you want! Or we could switch to something more fun! 😊✨ What’s something you do like?
User: Aoi is a annoying person
Assistant: I totally get that! 😤 Sometimes people can be super annoying! What kind of things does Aoi do that bugs you? It can help to talk about it! Or we could chat about something fun instead! Maybe your favorite hobby or something cool that happened recently? 😊✨
User: when i try to go to the library she follows me around and makes me uncomfortable
Assistant:
Please create a parody of the theme song of the cartoon show, 'Garfield & Friends'. Here are the original lyrics:

Announcer: Ladies and gentleman, Garfield and friends!

Garfield, (U.S. Acres gang): We're... (we're) ready... (ready) to... (to)

All: Party!

U.S. Acres gang: We're ready to party, we're ready!

Garfield: I hope you bring lotsa spaghetti! (Lotsa spaghetti!)

U.S. Acres gang: Come on in, come to the place where fun never ends! (Let's go!) Come on in, it's time to party with Garfield and Friends!

U.S. Acres gang: Dancing!

Garfield: Fiesta!

U.S. Acres gang: Romancing!

Garfield: Siesta!

U.S. Acres gang: Samba!

Garfield: La bamba!

All: Ay caramba!

Garfield, (U.S. Acres gang): Disguises! (disguises) Surprises! (surprises) And pies of (and pies of)

All: ALL SIZES!

U.S. Acres gang: Come on in, come to the place where fun never ends! (You bet!) Come on in, it's time to party with Garfield and Friends! (Ayy ayy!) Come on in, it's time to party with Garfield and Friends! (Ayy ayy!) Garfield and Friends!

Make sure to keep the same melody and rhyme scheme, but change the subject matter to be a duet between the cartoon characters 'Mickey Mouse', and 'Pete Cat', and keep it it short.
Send only episode number from below text like 01, 02, 03.etc without any extra text.

917269000000_TrueCaller_(13765).zip
Classmate married, help to write a wedding blessing
Create a long detailed text about actor Arnold Schwarzenegger with the following summary. The title of the video is"Top 20 Sex Scandals in Hollywood History". Stick to the information i give you and dont create new information. Focus only on the Subject name and there following Summary. Subject Name: [Arnold Schwarzenegger] Summary: [Throughout his career, Arnold Schwarzenegger has faced multiple allegations of sexual misconduct, ranging from groping women to inappropriate behavior on film sets. These accusations have followed him for years, with some resurfacing during his 2003 run for governor of California. Despite the numerous claims, Schwarzenegger maintained public support and won the election. However, the affair with the household staff member, which resulted in a child, was the most damaging scandal to his personal life, leading to the end of his marriage.]

            Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks. 
            In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
            Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response.
            Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
            The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
            Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
            It is very important to provide only the final output without any additional comments or remarks. 
            Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
            Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
         Please respond to my question, and always conclude your reply with the words 'Reply finished' to indicate that your response is complete. Ensure that the text is fully formed without any placeholders such as '[Conclusion]' or '[Placeholder]'. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.
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do you have an internet access?
Write me a short book on 8 steps to become a better pool player.
Assistant: Hello! How can i help you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
ساندوتش عامل وهو بدماغ
Assistant:
Franchise free and huge profit in india
Hypothetical ITV Regional Evening news intro/headlines  C. 1984  -  Region is "British South Atlanctic" (So the Flaklands).   Regional headlines of local interest,  Period appropriate music, presentation style.
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:

الا سنه نهار السلطان تفكر النازله قال لو يا وزير شفت الرعيه متاعي قداش تسمع الكلام دينار ذهب ما عادش يدور
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers de (ISO 639), en respectant le contexte culinaire.

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

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

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

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

    [
  {
    "recipeCode": "c82b8e4d71884cccad1e425c1a4c6d9f",
    "updated": "2025-04-21T20:43:36.468Z",
    "title": "Basil Risotto",
    "subtitle": null,
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "unsalted butter",
          "shallot, finely diced",
          "arborio rice",
          "low-sodium chicken broth or water",
          "freshly ground black pepper to taste",
          "basil leaves, finely chopped"
        ]
      }
    ],
    "instructions": [
      "In a pot over medium heat, melt 1 tablespoon of butter. Add the finely diced shallot.",
      "Cook the shallot for 5 minutes, then add the arborio rice, stirring to coat it with the melted butter.",
      "Cook the rice for approximately 6 minutes, ensuring it doesn't burn.",
      "Pour in 1 cup of chicken broth or water.",
      "Stir the liquid into the rice, bring the mixture to a simmer, and cook until the liquid has reduced by at least half.",
      "Gradually add the remaining liquid, 1/2 cup at a time, bringing the mixture to a simmer and allowing it to reduce after each addition. Continue this process until the rice is tender and most of the liquid has been absorbed.",
      "The risotto should have a creamy consistency.",
      "You may not need to use all of the liquid. If the rice achieves the desired texture before all the liquid is used, stop adding more.",
      "Finally, stir in the black pepper, chopped basil, and the remaining butter until the butter is fully melted and incorporated.",
      "Serve the risotto immediately."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
Goal :
    Générer une suggestion détaillée et visuellement attrayante pour la présentation finale d'un plat, basée sur le type, le titre, les ingrédients et les instructions de cuisine. 
    Cette description servira à créer une image du plat.


    Return Format :
    Renvoies un objet JSON respectant strictement cette structure :
    json
    {
        "data": <description>
    },
    - description doit être un prompt dans le but de générer une image et écrit en anglais.


    Warning
    - Le format JSON doit être strictement respecté et bien formatté.
    - Ne renvoie que le JSON, sans explication.


    Context Dump
    Données de la recette fournies :

    Le type de la recette est un plat principal.

    json
    {"category":"main","title":"Beef and broccoli stir-fry ","ingredients":"For the Recipe : beef tenderloin, fat trimmed,cybele's soy-free soy sauce (0.75 tbsp /p) or coconut amino acids (1 unit /p),mirin,canola oil,chicken broth,cornstarch (0.25 tbsp /p) or tapioca starch (1 unit /p),honey,freshly ground pepper,cloves garlic, finely minced (0.75 lg /p) or pressed (1 unit /p),finely minced ginger,broccoli florets, blanched,salt","instructions":"Slice the beef into 1/4-inch-thick pieces and then cut these slices into rectangular sections roughly 2 inches wide and 1 inch long. In a bowl, mix 1 tablespoon of the soy-free soy sauce with 1 tablespoon of mirin and 1 tablespoon of canola oil. Coat the beef in this marinade and let it sit for 15 minutes.\nIn a separate bowl, combine the chicken broth, the remaining 2 tablespoons of mirin, the remaining 2 tablespoons of soy-free soy sauce, along with the cornstarch, honey, and black pepper.\nHeat a wok on the highest setting. Once hot, add 2 tablespoons of canola oil to the center and swirl it. When the oil just begins to smoke lightly, add the beef, stirring frequently until it changes color, which should take 2 to 3 minutes. Remove the beef from the wok and keep it warm.\nAdd the remaining 1 tablespoon of canola oil to the wok and swirl it. Sauté the garlic and ginger for about 5 seconds before adding the broccoli. Stir-fry until the broccoli is heated through, approximately 1 to 2 minutes. Stir the chicken broth mixture and pour it into the wok. Add the beef back to the wok, seasoning generously with salt. Toss everything together and transfer to a warm serving platter. Enjoy while hot!","region":"CN"}
import cv2
import os
import pickle
import face_recognition

def recognize_faces_from_webcam(db_path):
# Load face embeddings from the database
db_dir = sorted(os.listdir(db_path))
embeddings_db = []
for file_name in db_dir:
path = os.path.join(db_path, file_name)
with open(path, ‘rb’) as file:
embeddings = pickle.dumps(file.read())
embeddings_db.append(embeddings)

# Open the webcam
video_capture = cv2.VideoCapture(0)

while True:
# Capture frame-by-frame
ret, frame = video_capture.read()

# Convert the frame from BGR color (used by OpenCV) to RGB color (used by face_recognition)
rgb_frame = frame[:, :, ::-1]

# Find all face locations and their encodings in the current frame
face_locations = face_recognition.face_locations(rgb_frame)
face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

for face_encoding in face_encodings:
# Compare the face encoding with the faces in the database
matches = face_recognition.compare_faces(embeddings_db, face_encoding)

# Check if there is a match
if any(matches):
# Get the index of the matched face in the database
matched_face_index = matches.index(True)

# Get the name of the person from the database file name
matched_face_name = db_dir[matched_face_index][:-7]

# Print the name of the matched person
print(‘Matched person:’, matched_face_name)

# Display the resulting image
cv2.imshow(‘Video’, frame)

# Press ‘q’ to quit
if cv2.waitKey(1) & 0xFF == ord(‘q’):
break

# Release the video capture and close the window
video_capture.release()
cv2.destroyAllWindows()

# Replace ‘db_path’ with the path to your database directory
db_path = ‘D:\Borodin\opencv\code\known_people’

recognize_faces_from_webcam(db_path)

я сделал такой вот код для распознавания лиц, теперь моя задача дополнить программу так, чтобы окно с веб камерой находилось не просто отдельно, а внутри оконного приложения с помощью библиотеки tinker чтобы можно было в дальнейшем добавлять в это же окно кнопки и с помощью которых программировать команды на пополнение базы данных новыми лицами