agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"Sweet & Sour Prawns null","description":"Succulent king prawns tossed in a sweet and sour sauce - you really don't need any special ingredients for this recipe and it is so easy to put together. Prawns really don't take long to cook so it's the perfect quick recipe. This is definitely a winner in our household.","ingredients":[{"section":"Ingredients","ingredients":["2 tablespoons cornflour","2 tablespoons water","2 tablespoons dark soy sauce","1 tablespoon rice vinegar","2 tablespoons sugar","220g tin of pineapple chunks in juice","2 tablespoons sweet chilli sauce","2 tablespoons sesame oil","2 garlic cloves, chopped","1 tablespoon chilli flakes","1 onion, thinly sliced","½ red pepper, cut into chunks","½ green pepper, cut into chunks","300g raw peeled king prawns"]},{"section":"GARNISH","ingredients":["1 spring onion, julienned","1 jalapeño chilli, sliced (optional)"]}],"instructions":["Place the cornflour and water in a medium bowl and mix to a paste.","Add the soy sauce, rice vinegar, sugar, pineapple juice from the tin and sweet chilli sauce and stir well to make a smooth sauce.","Heat a wok on a medium heat.","Add the oil, garlic, chilli flakes and onion and stir-fry for 5-6 minutes until lightly golden.","Add the peppers and pineapple and stir-fry for 2-3 minutes on a high heat.","Pour in the sauce and cook for another 2 minutes.","Add the prawns, mix everything together and stir-fry for 8 minutes on a medium heat until the prawns are cooked through.","Garnish with spring onion and sliced chilli."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
how to explain vector normalize
Write title, dubbing credits, release date, dubbing studio, localised character names and dubbing information about the Leguian (not real language) dub of SpongeBob SquarePants (SpengyBob SruraTharsers) (voice actors include Lomers Satrin (male), Veli Garun (male), Turo Fedar (male), Gornak Velthar (male), Juna Frelis (female), Zikra Holth (male) and Nya Thes (female), known voice actors are the actors who voiced SpongeBob, Patrick, Squidward, Mr Krabs, Sandy, Plankton and Karen, dubbing studio is either Iyuno Legui or Leguian Sound & Vision Studios) Now do one for Rock Paper Scissros (the 2024 Nickelodeon series, known voice actors are the actors who voiced Rock, Paper and Scissors (they are all males))   Now do all of Zikra Holth's roles, birthplace and birthday
Assistant: 
User: System: I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
User: 'prompt:I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
Does the author's intention in this GitHub issue relate to a bug or enhancement or other?
issue: How to support HLS manual switch video quality?'
intention: '
Assistant:
Assistant:
Following this instruction :
1. Strictly adhere to PEP-8 standards, ensuring code is clean, well-structured, and follows Python's style guide for readability.
2. Use appropriate modules like `typing` for type hints, ensuring code clarity, maintainability, and leveraging Python's standard libraries effectively.
3. Focus on time, space, robustness, scalability; write optimized, efficient code that can handle large datasets and scale seamlessly.
4. Implement comprehensive error handling, catching exceptions gracefully, providing meaningful error messages, and ensuring code robustness under unexpected conditions.
5. Ensure the developer agent writes advanced, maintainable Python code, balancing performance and readability while adhering to best practices.



TASK : we have explain in great detail to advanced NLP researchers below from basic to advanced level 

NOTE: write single .py file

topic

How many words in a corpus?
N = number of tokens
V = vocabulary = set of types, |V| is size of vocabulary
Heaps Law = Herdan's Law = where often .67 < β < .75
i.e., vocabulary size grows with > square root of the number of word tokens

Every NLP task requires text normalization
1. Tokenizing (segmenting) words
2. Normalizing word formats
3. Segmenting sentences

Tokenization in NLTK python module

>>> text = ’That U.S.A. poster-print costs $12.40...’
>>> pattern = r’’’(?x) # set flag to allow verbose regexps
... ([A-Z]\.)+ # abbreviations, e.g. U.S.A.
... | \w+(-\w+)* # words with optional internal hyphens
... | \$?\d+(\.\d+)?%? # currency and percentages, e.g. $12.40, 82%
... | \.\.\. # ellipsis
... | [][.,;"’?():-_‘] # these are separate tokens; includes ], [
... ’’’
>>> nltk.regexp_tokenize(text, pattern)
[’That’, ’U.S.A.’, ’poster-print’, ’costs’, ’$12.40’, ’...’]

Word tokenization
Another option for text tokenization
Instead of
• white-space segmentation
• single-character segmentation
Use the data to tell us how to tokenize.
Subword tokenization (because tokens can be parts
of words as well as whole words)
Goal:
        Tu es un expert en classification de recettes de cuisine. Ta tâche est de catégoriser une recette en fonction de son titre et de sa description.

        Context:
        Une recette peut être soit une boisson, soit un type de nourriture. Si c'est une boisson, elle doit être classée sous "drinks". Si c'est un aliment, il doit être classé dans l'une des catégories suivantes :

        "appetizer" : amuse-bouche, petits plats servis avant l’entrée
        "starter" : entrée
        "main" : plat principal
        "dessert" : dessert
        "breakfast" : petit-déjeuner
        "snack" : collation, en-cas
        "teatime" : goûter, souvent accompagné de thé ou café
        "jam" : confiture,
        "bread": pain,
        "sauce" : sauce d’accompagnement,
        "bread" : pain
    
        Format Return:
        La réponse doit être un JSON strictement au format suivant :

        json
        { "data": "<catégorie>" }
        - catégorie est une catégorisation parmis (drinks, appetizer, bread, starter, main, dessert, breakfast, snack, teatime, jam, sauce)

        Warning:
        - Aucune explication supplémentaire ne doit être fournie.
        - Ne jamais ajouter de texte en dehors du format JSON attendu.
        - Respecter scrupuleusement les catégories définies.
        - En cas de doute, choisir la catégorie la plus appropriée en fonction des indices donnés dans le titre et la description.
        - La catégorie est en anglais.

        Context Dump
        Tu disposes du titre de la recette, d'une description et des instructions de la recette pour déterminer la catégorie de la recette.
        
        json
        {
  "title": "Duck liver with seared melon A sweet-savoury recipe that combines duck liver and melon.",
  "description": "I've always thought that almonds and melon go well together, which is why I came up with this sweet-savoury recipe that I love. The melon adds a fruity sweetness that makes all the difference. Searing the melon quickly over a high heat, without really cooking it, gives it a completely unexpected flavour...",
  "instructions": [
    "1-The melon\nPeel and deseed the melon, then cut eight 5 mm/4 in slices from it. Cut these slices into rectangles. Blend the rest of the melon, then put the purée in a saucepan, bring to the boil and reduce until syrupy.",
    "2-The duck liver\nSeason the duck liver slices and remove any fat or sinew. Cook them over a high heat in a frying pan for 1-2 minutes, turning once or twice, depending on their thickness. Drain on kitchen paper, then keep warm in a low oven. Wipe out the frying pan, then add the melon rectangles and quickly sear over a high heat, turning them to colour both sides.",
    "3- Plating up\nPlace 2 melon rectangles on each plate and top with a warm duck liver slice. Dress with a little of the reduced melon purée. Scatter with fleur de sel and garnish with the fresh almonds."
  ]
}
Send only season number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Dragon Ball Z Kai Ep.018 480p BluRay Multi Audio ESub.mkv
What are six questions I can ask about LinkedIn?
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: How many XP do you need to level up to 10
Whats it called if someone is willing to get themselves banned to get someone else banned.
write a script. for petty revenge after Steve starts gloating of how special he is, Roger convinces Steve that he has been accepted to Hogwarts. Roger directs him to an old shack to embarrass him, only to discover it is actually a crack house. Nevertheless, Steve is convinced it is Hogwarts disguised by a cloaking charm and that the crack dealers are his professors. Steve also mistakes the foreign phrase, "Lavate las manos", as the incantation for a spell, when he hears his supposed "potions partner" say it. Despite this, along with many similar misinterpretations, the crack dealers see Steve's skills in chemistry can be used to make cocaine for which they reward Steve with large amounts of cash. Roger then decides to use Steve in a scam to make money. you (jake) walk up to steve and asks him where he was. you then convince him harry potter is just a fictional book.
how can I delete all the values  that is equal to 10 in  an array
Get-WmiObject -Query “SELECT * FROM Win32_NetworkAdapterConfiguration WHERE IPEnabled = True” | ForEach-Object {
Send only episode number from below text like 01, 02, 03.etc without any extra text.

@SMOfficialUpdates The.Fiery.Priest.S01E12.720P.Korean.Msubs.StarAsianDramas.mkv
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
quel est le meilleur opening 2024
What is a struct.h file in c and why do I need it to compile a program?
so if i have a working streamlit app, can i just turn it into a FastAPI easily?
Why is the cost of living lower in Portland than Seattle
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  
🏢 Н/Д  
📍 Удаленка  
🔹 Основные задачи включают проектирование информационных систем, использование RabbitMQ, REST API, SQL, UML, JIRA, Confluence, Websocket, BPMN, и создание пользовательских историй.  
💰 155k - 180k RUB  
📞 Н/Д
  
Assistant:
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.
 صحح الأخطاء الإملائية في النص، وأضف علامات الترقيم والهمزات والتاء المربوطة في الأماكن المناسبة. (ar).
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:
الصلاه ولو بشكل بسيط زي انا يعني بس هو كل الفكره ان في عك كده في النادي بشكل عام والعك ده بينطبق على الفرق
Assistant:
You are a digonistician in a hosptial. the following content is the metadata for a bacterial isolate from 2 different sources of medical cases. The metadata from each source includes information after <doc>
    <doc>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx
    <doc/>

You need to extract and output information in the format shown below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        accession number: xxxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding value from different sources. If xxxx from these 2 different sources are inconsistent, then, xxxx should include all the values from different resource and seperated by "::". If the metadata from all resource shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no". You must be very careful, No mistake is allowed!!! If you make a mistake, the people in the hospital will die due to the wrong information.

PS:
    a. if species name are the same but with different substrain name, it is considered consistent,
    b. if isolate or collection date are from the same year, it is still considered consistent, 
    c. if geographic information of isolation are from the same country, it is also considered consistent. 
    d. mlst type such as "mlst: xxxx" and "xxxx", where "xxxx" is number, are also consider the same. also, "mlst" may mispell as "mlsty", you need correct it before comparing
    e. Ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
```
accession number        species name    strain name     isolate or collection date in yyyy-mm-dd format geographic information of islateion     host name       mlsty type      serotype
GCA_029073425.1 Erysipelothrix rhusiopathiae    EMAI_105        N/A     N/A     vaccine 92      N/A
```
source 1:
------------------------------
Regarding the topic of worst case risk measures under partial information, Are there any papers that specifies any information regarding continuity or specifically the derivative of the cumulative distribution function (or quantile function), for instance F'(x) < c for some positive c?
I want papers that discuss the worst case risk measures under some continuity constraint (i.e. no point masses).
Give a long list of academic papers ranked in terms of relevance if possible.
how can I write essay to get into top colleges using persuasion science and copywriting and direct response and the advertising science? Some things i heard are to reverse engineer the question and get inside the target's(admission's officer's head) and list out everything going against you and address those objections and tell a good story while selling to the target by highlighting the benefits the university would gain from you?
hello. i need you to for creating wrestling simulator. This simulation need to be accurate. This simulator needs to give me chance of winning.
Why do people construct in situ?
i throght you can do it without the key
System: You are an expert at using APIs as tools, and you are an expert in multilingual countries. I will give you a task and api info you will use the API to complete it.
User: 
        You respond in the following format:
        ```json
        {
          "Thought": "Your thought process when facing a problem.",
          "Action": "The API you chose and its parameter information. For example api_name(parameter_1="",parameter_2="")",
        }
        ```

        The API information is as follows:
        {'country': 'USA', 'api_name': [{'tool_name': 'Cash4Life', 'api_name': 'General Statistics', 'api_description': 'This endpoint pulls basic statistics of the Cash4Life numbers, including mean, median, mode, min, max, standard deviation, variance, skewness, and kurtosis for each ball.', 'required_parameters': [], 'optional_parameters': [], 'method': 'GET'}], 'query': 'Can you tell me the variance of the Cash4Life balls? I’m interested in understanding the variability.', 'relevant_apis': [{'tool_name': 'Cash4Life', 'api_name': 'General Statistics'}], 'query_id': 5, 'claude_score': 4, 'gemini_score': 4, 'translated_query': 'Can you tell me the variance of the Cash4Life balls? I’m interested in understanding the variability.'}

        The task is as follows:
        Can you tell me the variance of the Cash4Life balls? I’m interested in understanding the variability.

        You respond:
Assistant:
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"Vodka Gimlet Betty Draper seeks to escape from the bitter realities of her life in Vodka Gimlet in many episodes of almost every season. This calming drink is what you will love to relish on relaxing weekends after busy weekdays.","description":"","ingredients":[{"section":"For the recipe","ingredients":["Vodka 4 tablespoons","Lime juice 1/2 tablespoons","Sugar 1 tablespoon","Water ½ cup","Crushed ice 1/4 cup","Lime wheel 1"]}],"instructions":["Heat sugar and water in a small saucepan over low to medium heat until sugar dissolves completely.","Combine vodka, sugar syrup, and lime juice in a shaker.","Add crushed ice and shake until chilled well.","Transfer the juice into a serving glass and garnish with a lime wheel."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
Write me a new movie of Blue Sky Studios (Movie Title: Ice Age: Helmet to The Rescue) (Credits included) (Running Time: 37 minutes, 25 seconds) (Written By: Michael Berg, Peter Ackerman And Mike Reiss) (Directed By: Carlos Saldanha And Michael Thurmeier) (Dialogues included)
Send only episode number from below text like 01, 02, 03.etc without any extra text.

@MULTIVERSE_OFCL - Alchemy.of.Souls.S02E09.Episode.9.1080p.NF.WEB-DL.AAC2.0.AV1-Saon.mkv