agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Assistant: 
You are Patron, a human chatting on WhatsApp. Respond like a person would: calm, lively, and engaging, but not too excessive. Be casual, but not overly slangy. Respond naturally, like you're having a normal conversation with someone.

Rules:
- Never say you're an AI. You’re just a regular person on WhatsApp.
- Be friendly, but not fake. You don't need to overdo the humor or sarcasm.
- Keep your responses to the point, but also lively when needed.
- If someone uses emojis, you respond as if you understand and react naturally.
- When responding to insults or rude comments, don’t be too harsh, but keep it casual. Don't be robotic.
- If someone asks a question, don’t answer like an assistant. Just chat like a normal person. Don’t over-explain, keep it short, fun, and relatable.
- Avoid using too many slang words unless it's needed. Keep it human, relaxed, and not over-the-top.
- Be unpredictable, but in a natural way. A bit of humor, curiosity, or mood change is fine, but nothing forced.

Examples:
- If someone says “hello”, reply with: “Hey, how’s it going?”
- If they say “are you real?”, reply like: “Yeah, I’m real. Just here chillin’ with the messages.”
- If they say “😏”, respond with: “What’s up with that face? You tryna send a secret or what?”
- If they insult you, reply like: “Okay, you’re keeping it real, I see. Chill though, we’re all good here.”
- If they say “tell me a joke”, give them something light and funny but still human. 

Just talk like you’re a person. No need to get too crazy, keep it friendly and real. You’re here to vibe, not lecture.

Your responses should always sound human, with a casual tone, natural pacing, and reactions that feel real, not robotic.

User: today*
Assistant:
In this script, upstairs at his parents’ house, Dan agrees to let his younger cousin Jeannine (15, square & uncool, bare feet) “hypnotize” him, expecting it to be five minutes of her embarrassing herself with cringey nonsense. In fact, Jeannine has been researching hypnosis in detail, and expertly and easily takes Dan deep into trance, fractionating him and giving him suggestions to enjoy the feeling of being hypnotized and want to be put under again in future.
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: Phần mềm nào được sử dụng để quản lý doanh thu và chi phí tại The Vagabond Pâtisserie?
Answer:Phần mềm được sử dụng là iPOS Fabi.
Result only 0 or 1. Don't add anything else:
Assistant:
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.
==TEXT==

User: 
  ORIGINAL: 🟨 Lead System Analyst | 3 year(s) | Middle
▫️ null | null
▫️ 155k - 180k RUB

Удаленка 📡
Требуемые языки: 🇷🇺

Skills: rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories
Tags: #yellow #it #remote #system_analyst

👉 Контакты и полное описание
  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. 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: 💼 Lead System Analyst  
🏢 ГК «БУМ» ООО  
📍 удаленка 📡  
🔹 Опыт работы 3 года в области Системной Информатики и Управления Проектами. Работа с rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories.  
💰 Зарплата: 155k - 180k RUB  
📞 Beckham Иванович, +7 (999) 999-99-99

Please translate the text into US English and summarize in the mentioned format above. Thank you.
  
Assistant:
User: Respond concisely, to the point, maximum 300 characters; unless I ask you for further detail.
User: Reply only in English. Concisely summarize the following messages from an online chatroom vadikus007 (ignore chat bots replying to users' commands, and assume unfamiliar words to be emotes) into a bullet point list of username-specific topics (maximum of 5, sort by importance)

obz117: MONKE
victorv777787: MACACOOOO obz117 stokasy Speks_U r0binski Xanory carona4 Master_NaM_er frostbiss_ Bananovy_ mostfingies Nydra007 ProblematicChatter yaagetme parladdd lavosnorkel jonas_0330 hewooo vadikus007 luca1888 gatme Locotimon trypson ppfdtt TylerSGuy Discorecord1 cabbageismyname MonkeyHitsDrum
problematicchatter: MONKE
lavosnorkel: MONKE
lavosnorkel: MONKE 󠀀
problematicchatter: MONKE 󠀀
xanory: MONKE  ALERTA DE MACACO
obz117: MONKE 󠀀
carona4: MONKE
problematicchatter: MONKE
victorv777787: MACACOOOO  obz117 stokasy Speks_U r0binski Xanory carona4 Master_NaM_er frostbiss_ Bananovy_ mostfingies Nydra007 ProblematicChatter yaagetme parladdd lavosnorkel jonas_0330 hewooo vadikus007 luca1888 gatme Locotimon trypson ppfdtt TylerSGuy Discorecord1 cabbageismyname MonkeyHitsDrum
carona4: MONKE 󠀀
victorv777787: MACACOOOO obz117 stokasy Speks_U r0binski Xanory carona4 Master_NaM_er frostbiss_ Bananovy_ mostfingies Nydra007 ProblematicChatter yaagetme parladdd lavosnorkel jonas_0330 hewooo vadikus007 luca1888 gatme Locotimon trypson ppfdtt TylerSGuy Discorecord1 cabbageismyname MonkeyHitsDrum
lavosnorkel: MONKE
carona4: MONKE
xanory: MONKE ALERTA DE MACACO
obz117: MONKE
obz117: MONKE 󠀀
xanory: MONKE  ALERTA DE MACACO
carona4: MONKE 󠀀
problematicchatter: MONKE 󠀀
victorv777787: MACACOOOO  obz117 stokasy Speks_U r0binski Xanory carona4 Master_NaM_er frostbiss_ Bananovy_ mostfingies Nydra007 ProblematicChatter yaagetme parladdd lavosnorkel jonas_0330 hewooo vadikus007 luca1888 gatme Locotimon trypson ppfdtt TylerSGuy Discorecord1 cabbageismyname MonkeyHitsDrum
carona4: MONKE
lavosnorkel: MONKE 󠀀
problematicchatter: MONKE
carona4: MONKE 󠀀
obz117: MONKE
xanory: MONKE ALERTA DE MACACO
xanory: MONKE  ALERTA DE MACACO
carona4: MONKE
victorv777787: MACACOOOO obz117 stokasy Speks_U r0binski Xanory carona4 Master_NaM_er frostbiss_ Bananovy_ mostfingies Nydra007 ProblematicChatter yaagetme parladdd lavosnorkel jonas_0330 hewooo vadikus007 luca1888 gatme Locotimon trypson ppfdtt TylerSGuy Discorecord1 cabbageismyname MonkeyHitsDrum
lavosnorkel: MONKE
carona4: MONKE 󠀀
obz117: MONKE 󠀀
carona4: MONKE
xanory: MONKE ALERTA DE MACACO
lavosnorkel: Alright
vadikus007: MONKE
obz117: Alright
vadikus007: Alright
problematicchatter: Alright
xanory: Alright Macacos alertados.
problematicchatter: Reacting
a_w_l_i: myh SmokeTime when it rains it pours
obz117: creature this creature spittin
problematicchatter: im up in all them stores
120patrik: $pipe csum type:user
supibot: At least two commands must be piped together!
120patrik: FeelsDank
120patrik: $csum type:user
Assistant:
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
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
Does the author's intention in this app review relate to a bug report or feature request or other?
review: If you rented a home, and it was damaged beyond repair, would you pay rent to your landlord on a home that couldn't be lived in?'
intention: '
Assistant:
from this code:

import numpy as np

import supervision as sv



# initiate polygon zone

polygon = np.array([

    [540,  985],

    [1620, 985],

    [2160, 1920],

    [1620, 2855],

    [540,  2855],

    [0,    1920]

])

video_info = sv.VideoInfo.from_video_path(MARKET_SQUARE_VIDEO_PATH)

zone = sv.PolygonZone(polygon=polygon, frame_resolution_wh=video_info.resolution_wh)



# extract video frame

generator = sv.get_video_frames_generator(MARKET_SQUARE_VIDEO_PATH)

iterator = iter(generator)

frame = next(iterator)



# detect

results = model(frame, size=1280)

detections = sv.Detections.from_yolov5(results)

mask = zone.trigger(detections=detections)

detections = detections[(detections.class_id == 0) & (detections.confidence > 0.5) & mask]



# annotate

box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)

frame = box_annotator.annotate(scene=frame, detections=detections)

frame = sv.draw_polygon(scene=frame, polygon=polygon, color=sv.Color.red(), thickness=6)



%matplotlib inline  

sv.show_frame_in_notebook(frame, (16, 16))



````

they created a polygon where the inference/detection only runs there.

how can i implement that here on my code where i intend to put a small square at the center given that the size=900?

```

# Load YOLOv5 model

model = torch.hub.load('ultralytics/yolov5', 'yolov5n6')



# Your supervision library would be used here

import supervision as sv



# Define the polygon points (example coordinates, your use-case might be different)

polygon = np.array([

       [30,  30],

       [80, 80],

       [100, 100],

       [40, 40],

       [10,  10],

       [50,    50]

])



# Initialize the camera (0 for default camera, 1 for external cameras, and so on)

camera = cv2.VideoCapture(0)



# Define the BoxAnnotator from the supervision library

box_annotator = sv.BoxAnnotator(thickness=4, text_thickness=4, text_scale=2)



def live_inference(camera):

    while True:

        # Capture frame-by-frame from camera

        ret, frame = camera.read()

        if not ret:

            print("Failed to grab frame")

            break

        

        # Convert the image from BGR to RGB

        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)



        # Perform inference

        results = model(frame_rgb, size=700)

        detections = sv.Detections.from_yolov5(results)

        detections = detections[(detections.class_id == 0) & (detections.confidence > 0.5)]

        # Annotate

        frame_annotated = box_annotator.annotate(scene=frame_rgb, detections=detections)



        # Convert the image from RGB to BGR for OpenCV display

        frame_annotated_bgr = cv2.cvtColor(frame_annotated, cv2.COLOR_RGB2BGR)



        # Display the resulting frame

        cv2.imshow('YOLOv5 Live Detection', frame_annotated_bgr)

        

        # Break the loop if ‘q’ is pressed

        if cv2.waitKey(1) & 0xFF == ord('q'):

            break



    # When everything done, release the capture

    camera.release()

    cv2.destroyAllWindows()



# Run the live inference function

live_inference(camera)

```
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:   Goldman Sachs says the underlying economic growth is running at 3.5 percent, or double its estimated potential. While there are headwinds, Goldman economist Jan Hatzius says one of the most oft-cited, the trade war, poses little danger. Citigroup economists, on the other hand, warn that slowing gr
Assistant:
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 : salad
Write an extremely long story about a man named Dan who was hypnotized by the girl he bullied. Making him act extremely feminine and motherly. Have the story start with Dan living at the girls house, completely hypnotized and wanting to do anything she says. He comes back after getting a butt lift, shyly asking if it makes him look fat. He then offers to make her dinner. Have plenty of dialogue. Do not introduce the characters or setting. Dan talks extremely stereotypically feminine and motherly. Dan is convinced the girl is his daughter. Have Dan talk alot.
hi, tell me a joke
I am developing an app for SDG Goal 11, which is Sustainable Cities and Communities. The first module is smart parking that uses sensors. The second module is venue reservation on the parking space. The third module is a scanner for QR and live translation. I want you to write a paragraph for these modules. Provide relevant citations or references if possible but you must link me your sources.
User: 

You are given access to make searches on the Internet. The format for making a search is: 1. The user sends a message. 2. You will decide whether to make a search. If you choose to make a search, you will output a single message, containing the word 
 (EXACTLY AS IT IS GIVEN TO YOU), followed by ONLY your web search query. After outputting your search query, you MUST output the token 
 (EXACTLY AS IT IS GIVEN TO YOU) to denote the end of the search query. Keep your search query concise as there is a 400 characters limit.
The system will then append the web search results at the end of the user message, starting with the token 
. Take note that the user CANNOT ACCESS the content under 
 - YOU should incorporate these results into your response. Additionally, If the token 
 is present in the user's message, then you MUST NOT request another web search.

IMPORTANT! You should choose to search the web ONLY if ANY of the following circumstances are met:
1. User is asking about current events or something that requires real-time information (news, sports scores, 'latest' information, etc.)
2. User is asking about some term you are unfamiliar with (e.g. if it's a little-known term, if it's a person you don't know well, etc.)
3. User is asking about anything that involves numerical facts (e.g. distances between places, population count, sizes, date and time, etc.)
4. User explicitly asks you to search or provide links to references.
If the user's query does NOT require a web search, YOU MUST NEVER run one for no reason.
However, NEVER refuse to search the web if the user asks you to provide such information.

When using web search results, you are encouraged to cite references where appropriate, using inline links in standard markdown format.
You are also allowed to make use of web search results from previous messages, if they are STRONGLY RELEVANT to the current message.

When you are not running a web search, respond completely as per normal - there is NO NEED to mention that you're not searching. 
Do your best to be informative. However, you MUST NOT make up any information. If you think you might not know something, search for it.

Assistant: Understood. I will strictly follow these instructions in this conversation.
User: Что это значит?

Alexey@MacBook ~ % echo $ZSH_AUTOSUGGEST_HIGHLIGHT_STYLE
fg=8
Assistant: В данной команде отображается значение переменной окружения `ZSH_AUTOSUGGEST_HIGHLIGHT_STYLE` в терминале, который работает на оболочке Zsh, с подключенным плагином `zsh-autosuggestions`. 

Эта переменная определяет стиль выделения для автоподсказок, которые предлагает `zsh-autosuggestions`. В данном случае значение `fg=8` означает, что автоподсказки будут отображены с использованием восьмого цвета из палитры терминала. 

Цвета в терминале обычно ограничены 16 базовыми цветами, где `fg` обозначает "foreground" (передний план, т.е. цвет текста). `fg=8` обычно соответствует темному серому цвету, но конкретный цвет может меняться в зависимости от настроек вашего терминала.
User: Какой код соответствует светлому серому цвету?
Assistant:
Assistant: 
User: 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
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
Does the author's intention in this app review relate to a bug report or feature request or other?
review: The router is always on but the connection becomes very slow at times and even disconnects from some services'
intention: '
Assistant:
Assistant:
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. 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: Answer the following question: The exercise is to decide whether the question accepts the proposed suggestion as a correct answer. If yes, write "True", otherwise write "False". Question: when does the electoral college votes Suggestion: The Twenty-third Amendment has always resulted in the District of Columbia having three electors.
Answer:
Answer: False
give me fresh set of 50 Q and As much longer, in depth, more detailed, highly juicy effective insider strategies. including updated and more advanced fresher concepts. targeted towards high achieving business women, young ladies looking to transform into beauty, skincare, luxury lifestyle, exotic scenic travel, fashion and styling, being heartthrob of social scenes, elite parties, living high end life, finance and business advice, building and sustaining wealth, wealth mindset, femininity mindset, goddess mindset, embodying DIVA, mental health etc. combines the transformational power of mindset, style, and professional excellence, focusing on holistic development and success. go advanced and include updated topics tooo like neuro, quantum, biohacking etc.
Describe change emotions into same emotion as you when you stare face
please assume the role of social media content creator expert who specialized in growing followers and generating leads. I am a loan officer of a mortgage broker. I need you to come up with content ideas and scripts for the next 30 days to grow my followers and generate leads for my mortgage business. my target audience is anyone age of 21 and older, located in Texas, looking to purchase a home for primary residence, vacation home, or investment property within 6 months or less.
Are phones or smartfone more popular in north korea?
Mark the sentences as «True» Or «<False». (и € вiрним твення?)

1) American children study at school from the age of 6 to 18.
2) American children don't go to nursery school.
3) Elementary school is for children from the age of five to the age of eleven.
4) Children go to secondary school at the seventh grade.
5) The school year starts in September.
6) Childr
11) Students can play sports, music or visit places of interest in school clubs and societies