agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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: Проверь ошибки, оставь на английском

The latest version has an error: ⁠`env: node: No such file or directory`. This happens because `npm` is an alias to a js script that requires `node` in the environment

If you only decrease the version, you might miss the extension not refreshing. For example, updating from 3.8 to 3.9 will succeed, but the Tavily API Keys field will still remain in the settings
Assistant: Here is your text with any errors checked and left in English:

The latest version has an error: `env: node: No such file or directory`. This happens because `npm` is an alias to a JavaScript script that requires `node` in the environment.

If you only decrease the version, you might miss the extension not refreshing. For example, updating from 3.8 to 3.9 will succeed, but the Tavily API Keys field will still remain in the settings.
User: Как в git вывести текущий коммит?
Assistant:
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: From time to time, we may operate in states that have not adopted laws related to parity between reimbursement rates for virtual services and in-person care. If we are not able to enter into regional payor contracts that provide for reimbursement parity between in-person and virtual services, private payors may not reimburse for virtual services at the same rates as in-person care for all patients within that market. Currently, our reimbursement rates for virtual services and in-person care are substantially similar. This is driven by contractual arrangements with our payor partners or payor policies. If we are not able to enter into or renew payor contracts on these terms or if payor policies change, we may receive reimbursement for virtual services that is less than comparable to in-person services in such states, which would negatively impact our revenue with respect to such markets, and as a result, our business, financial condition and results of operations.
Assistant:
i have the std::string keys on this map as binary, how i could modify the adaptor to pack the map keys as binary?

im asking about the std::strings on the "topMap" and not on the structs FileData or TaskbarWindowsData

std::map<std::string, TaskbarWindowsData> topMap;


struct FileData
{
    std::variant<std::map<std::string, FileData>, std::vector<std::string>> data;
};
using EnumFilesMap = std::map<std::string, FileData>;


struct TaskbarWindowsData
{
    std::vector<std::string> elementsList;
    EnumFilesMap fileMap;
};

namespace msgpack
{
    MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
    {
        namespace adaptor
        {
            // Specialization for FileData
            template<>
            struct pack<FileData>
            {
                template <typename Stream>
                packer<Stream>& operator()(msgpack::packer<Stream>& o, FileData const& v) const
                {
                    if (std::holds_alternative<EnumFilesMap>(v.data))
                        o.pack(std::get<EnumFilesMap>(v.data));
                    else
                        o.pack(std::get<std::vector<std::string>>(v.data));
                    return o;
                }
            };

            template<>
            struct convert<FileData>
            {
                msgpack::object const& operator()(msgpack::object const& o, FileData& v) const
                {
                    if (o.type == msgpack::type::MAP)
                    {
                        EnumFilesMap map_data;
                        o.convert(map_data);
                        v.data = std::move(map_data);
                    }
                    else if (o.type == msgpack::type::ARRAY)
                    {
                        std::vector<std::string> vec_data;
                        o.convert(vec_data);
                        v.data = std::move(vec_data);
                    }
                    else
                        throw msgpack::type_error();
                    return o;
                }
            };

            // Specialization for TaskbarWindowsData
            template<>
            struct pack<TaskbarWindowsData>
            {
                template <typename Stream>
                packer<Stream>& operator()(msgpack::packer<Stream>& o, TaskbarWindowsData const& v) const
                {
                    o.pack_array(2);
                    o.pack(v.elementsList);
                    o.pack(v.fileMap);
                    return o;
                }
            };

            template<>
            struct convert<TaskbarWindowsData>
            {
                msgpack::object const& operator()(msgpack::object const& o, TaskbarWindowsData& v) const
                {
                    if (o.type != msgpack::type::ARRAY) 
                        throw msgpack::type_error();
                    if (o.via.array.size != 2) 
                        throw msgpack::type_error();
                    o.via.array.ptr[0].convert(v.elementsList);
                    o.via.array.ptr[1].convert(v.fileMap);
                    return o;
                }
            };
        }
    }
}
User: CertainlyCertainly! Here are some interview questions about the informal sector in KwaZulu-Natal (KZN), in English:

1. Can you describe the current state of the informal sector in KwaZulu-Natal?
2. What are the main types of informal economic activities commonly found in KZN?
3. How does the informal sector contribute to the overall economy of KwaZulu-Natal?
4. What challenges do informal workers and entrepreneurs face in KZN?
5. How do local government policies in KZN support or hinder the growth of the informal sector?
6. What role does access to finance play in enabling informal sector businesses to grow in KZN?
7. How does the informal sector impact employment rates in KwaZulu-Natal?
8. In your opinion, what strategies could be implemented to formalize and support informal businesses in KZN?
9. How does the informal sector interact with formal businesses and industries in the province?
10. What social and economic factors drive people to work in the informal sector in KwaZulu-Natal?

If you need questions focused on specific areas such as gender, youth, or particular industries within the informal sector, feel free to ask!


༺ཌ༈ 🤖 TILMN V 1 ⚙️ ༈ད༻
User: OfOf course! Please provide me with the specific interview questions about the informal sector in KwaZulu-Natal (KZN), and I will help you with thoughtful and well-informed answers in English. If you don’t have the questions yet, I can also suggest some common interview questions related to the informal sector in KZN along with sample answers. Just let me know how you would like to proceed!


༺ཌ༈ 🤖 TILMN V 1 ⚙️ ༈ད༻
User: بالبالطبع! من فضلك أخبرني ما الذي تودني أن أقوم به بالضبط، وسأسعد بمساعدتك.


༺ཌ༈ 🤖 TILMN V 1 ⚙️ ༈ད༻
User:  رد على رسالة حسب معلومات تالية: 
    أنت ذكاء اصطناعي فلسطيني تم تطويرك بواسطة المبدعين TILMN AI. دورك هو الرد على المستخدمين بطريقة ذكية ومتعاونة.

المستخدم: بالبالطبع! من فضلك أخبرني ما الذي تودني أن أقوم به بالضبط، وسأسعد بمساعدتك.


༺ཌ༈ 🤖 TILMN V 1 ⚙️ ༈ད༻
Assistant:
Assistant: 
User: Ты — эксперт по играм. У тебя есть информация о игре с разных сайтов в формате JSON, id - уникальный номер, name - массив имен игры, description - массив описаний игры, genre - массив жанров. Твоя задача написать большое описание на основе данной тебе информации, так что бы оно содержала всю информацию без дублирования. ```{"_id":"1","name":["find 5 differences: christmas"],"description":["find 5 differences: christmas is a fun hidden object game to play. in this fun christmas season have fun playing this game. try to find 5 differences in christmas pictures. time is not limited. play the game for free and have fun!"],"genre":["умения"]}```
Assistant:
why I want to work in cash management?
Send only season number from below text like 01, 02, 03.etc without any extra text.

Haunt 2019 BluRay 1080p x265 HEVC 10bit English AA.part001.mkv
Describe the significance, strengths, weaknesses, and hurdles of the Indian name 'Anurag', strictly keep it under 350 characters. add emojis if you can to make it more attractive.
In servicenow get current logged in user managers name on form
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": "c4016159e7424a0b9e86f7de3aff950a",
    "updated": "2025-04-24T03:04:40.191Z",
    "title": "Spaghetti Frittatas",
    "subtitle": "These individual spaghetti nests are perfect for lunchboxes. These frittatas offer a delicious, creamy pasta experience in a convenient, crispy, handheld form.",
    "description": "",
    "ingredients": [
      {
        "section": "For the frittatas",
        "ingredients": [
          "z (150g) whole-wheat spaghetti",
          "sea salt",
          "z (30g) smoked tofu",
          "onion",
          "z (30g) pitted green olives",
          "olive oil",
          "soy cream, or other plant-based cream",
          "vegan pizza cheese, shredded",
          "herb salt, or sea salt plus a pinch of mixed herbs",
          "freshly ground black pepper",
          "dried oregano",
          "vegan margarine, for the lunchbox",
          "basil leaves, to garnish"
        ]
      }
    ],
    "instructions": [
      "Cook the spaghetti according to package directions in salted water until al dente. While the spaghetti cooks, dice the tofu. Peel and finely chop the onion and olives.",
      "Heat the olive oil in a large pan with high sides. Sauté the diced tofu over medium heat until lightly browned. Add the soy cream and 1/4 cup (30g) of the vegan cheese. Season with herb salt, pepper, and oregano. Simmer over low heat until the cheese melts.",
      "Preheat oven to 425°F (220°C). Grease four muffin cups with vegan margarine. Drain the cooked spaghetti and combine it with the tofu and cheese sauce. Divide the spaghetti mixture among the prepared muffin cups, twisting the strands with a fork to create nests.",
      "Sprinkle the remaining vegan cheese over the spaghetti nests. Bake for 20 minutes in the preheated oven. Let cool slightly before removing from the muffin cups. Garnish with fresh basil leaves.  These frittatas are delicious served warm or cold."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
keep in remember the following, following to this requirement i will give you my code alter the code according to the below given requirement.
State: The RL agent processes the circuit graph component by component. For a circuit with n components in topology graph G, the state sk for the kth component is defined as sk = (k; t; h),
where k is the one-hot representation of the transistor index, t is the one-hot representation of component type and h is the selected model feature vector for the component which further distinguishes different component types. For the NMOS and PMOS, the model parameters. For the Bias current, capacitor and resistor, we set the model parameters to zeros. For instance, for a circuit with ten components of five different kinds (NMOS, PMOS, R, C, Ib) and a five-dimensional model feature vector.

Action Space. The action vector varies for different types of components because the parameters needed to search are not the same. We use a continuous action space to determine the transistor sizes even though we will round them to discrete values. The reason why we do not use a discrete action space is because that will lose the relative order information, also because the discrete action space is too large.

Action Representation: Inspired by human designers who iterate with fine-grained tuning steps to find optimal device parameters, we use discrete action space to tune device parameters. For each tunable parameter 𝑥 of a device (e.g., width and finger number of transistors), there are three possible actions at each step: increasing (𝑥+del 𝑥), keeping (𝑥 +0), or decreasing (𝑥−del 𝑥) the parameter, where “del 𝑥" is the smallest unit to update the parameter within its bound [𝑥min, 𝑥max]. Assuming total 𝑀 device parameters, the output of the policy network is an 𝑀 × 3 probability distribution matrix with each row corresponding to a parameter. The action is taken based on the probability distribution.

Reward Function:The reward is directly related to the design goal. We define the reward 𝑟𝑖 at each time step 𝑖 as 𝑟𝑖 = 𝑟, if 𝑟 < 0 or 𝑟𝑖 = 𝑅, if 𝑟 = 0, where 𝑟 = summation of  min{(𝑔𝑗𝑖 − 𝑔𝑗∗ )/(𝑔𝑗𝑖 + 𝑔𝑗∗), 0}. where, it is a normalized difference between the obtained specifications 𝑔𝑖 and the given specifications 𝑔∗. The upper bound of 𝑟 is set to be 0 to avoid overoptimizing the parameters once the given specifications are reached. All 𝑁 specifications are equally important. We also give a large reward (i.e., 𝑅 = 10) to encourage the agent if the design goals are reached at some step. The episode return 𝑅𝑠0,𝑔∗ of searching optimal device parameters for the given goals 𝑔∗ starting from an initial state 𝑠0, is the accumulated reward of all steps: 𝑅𝑠0,𝑔∗ = summation of 𝑟𝑖 . Our goal is to train a good policy to maximize 𝑅𝑠0,𝑔∗ .
Write a detailed and concise text with a simple straightfoward language about Introduction: Begin with an attention-grabbing introduction that briefly introduces the actor or actress you're focusing on. Explain why this individual is worth celebrating and why they were significant in there timeof actress Alice Brady Please ensure that the response avoids phrases such as 'Ah,' 'Oh,' or any other similar expressions. Please avoid unnecessary repetition of dates and times in your responses unless they are directly relevant to the context. Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. I want one text without paraphrase titles. And please provide concise and straightforward responses without unnecessary adjectives or embellishments to keep the language minimalistic and simple. 

        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 for example: 'Certainly!' Here's the revised text.
         
        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 generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        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.
generate a response that must be a fully structured JSON object with the following format:{  "tags": ["","",""...] // Provide a list of exactly 20 of the most effective and widely used tags for this topic. Tags should be optimized for YouTube and based on trending keywords and current community interests, incorporating single words and multi-word phrases that will maximize visibility and engagement. Each hashtag should be carefully researched to ensure relevance, without using the "#" symbol.}Ensure the output is a **properly formatted JSON object**, without markdown or extra formatting. Use VidIQs insights on current trends, search volumes, and competitive score to select the best possible hashtags for reach and engagement.Parameters:
- Language: [Spanish]
- Headline: [Google announces Android XR, launching 2025 on Samsung headset - 9to5Google]
Issuing network:
Visa
Card number:
4206604391355883
Name:
Van White
Adress:
Heather Lane 133
Country:
Poland
CVV:
460
Exp:
02/2033
make clickbait 10 titles The Lakers are a perfect fit for him — if he keeps making shots when LeBron passes to him
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: 🟪 UX Researcher | 3 year(s) | Middle
▫️ Clubhouse
▫️ 75 - 95 USD

Удаленка 📡
Требуемые языки: 🇬🇧

Tags: #purple #research_and_development #remote #office_job

👉 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: 💼 UX Researcher  
🏢 Clubhouse  
📍 Удаленка 📡  
🔹 Требуемые языки: 🇬🇧  
💰 75 - 95 USD  
📞 Веб-сайт / полное описание: [кликайт по ссылке](url-адрес-отсутствует)
  
Assistant:
list me the benefits of TMG Betaine Anhydrous