agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Ok, another question. In my app I have some user tasks. I want the app as efficient as possible with minimum data storage, minimum DB calls, utilizing best optimization practices. So each user should store the tasks with the state of the task (done/not done yet) Instead of that I want to make it so that we have only one table Tasks with the tasks stored here, those tasks will have all the data related to task itself and ofcourse UUID as primary key. While user will store only tasks that he completed in form of JSONB field in DB with a list of task UUIDs. SO when User fetch tasks in fact we just fetch tasks from cache or from DB if there is no cache(cache will have a pretty long TTL and will be updated on demand if there is no cache) after that we take JSONB with completed tasks from user profile and change field completed with True for every task which UUID is presented in user's jSONB tasks field. So in that case we will have only one small list of tasks(there will be like 10 to 20 tasks) and really small task storage for user(only UUIDs for completed tasks). WHile my app is CQRS there is no problem to claim reward for any activity including tasks - we just post Pulsar message with the needed reward and worker will manage it for us. But what I want to make also is to make tasks to have 2 base types: verifiable and non-verifiable. Some tasks are managed on the fronend only and doesn't require any verification on BE side(like task "Visit our partners website" - user opens up the link and the button changes state so it will send task_completed command) but some of them require verification. I want some system that each task will be either verifiable or not. If it is verifiable - then it can verify some value, so it will store verifier(which is some name that class dispatcher will dispatch into particular verifier class) and some value(just a value whether it is a number or a bool or string that will be passed as argument into verifier's method verify along with context object(that will have for example profile data, streak, etc) and then this verifier just validate the task. For example task is "invite 5 fiends" then task object in DB will store name for verifier (like invites_verifier or something like this) and value (in that case 5) Then this task command executed and calls verifier, it is distatched to InvitesVerifier class and it's method verify simply check if context,profile.ref_quantity >= value. SO that way we can make other tasks like invite 10 friends, invite 50 friends in a matter of seconds and it will work out of the box. Help me to design and develop this system of task management and write full clean robus and super efficient code for this like this was written for bigtech highload app with best resource utilization and best practices. I need you to focus mainly on verifiers, come up with 20 verifiers for different tasks, also there should be 3rd party verifiers that will require verification by making a call to another API for example. I want those verifiers and dispatcher to be super efficient, robust, fast, bulet proof and easily extendable with minimal DB calls and excelent resourse utilization.
name me the library for FHE used by Duality Tech
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: Zup for Xion endlessly
module EvalIntExpr ( evalIntExpr, testEvalIntExpr, IntExpr(..) ) where

import Test.QuickCheck

-- an IntExpr is an expression-tree over integers
data IntExpr =
  Leaf Int |
  Add IntExpr IntExpr |
  Sub IntExpr IntExpr |
  Mul IntExpr IntExpr |
  Uminus IntExpr
  deriving (Eq, Show)

-- evalIntExpr returns the Int result of evaluating the IntExpr
-- expression-tree given by its argument.
evalIntExpr :: IntExpr -> Int
evalIntExpr _ = error "TODO"


testEvalIntExpr = do
  print "******* test evalIntExpr"

  quickCheck $ counterexample "Leaf" $ evalIntExpr (Leaf 42) == 42
  quickCheck $ counterexample "Add" $
    evalIntExpr (Add (Leaf 33) (Leaf 22)) == 55
  quickCheck $ counterexample "Sub" $
    evalIntExpr (Sub (Leaf 33) (Leaf 22)) == 11
  quickCheck $ counterexample "Mul" $
    evalIntExpr (Mul (Leaf 31) (Leaf 4)) == 124
  quickCheck $ counterexample "Uminus" $
    evalIntExpr (Uminus (Leaf 33)) == (-33)
  quickCheck $ counterexample "Complex" $
    evalIntExpr (Mul (Leaf 4)
                  (Sub (Add (Leaf 3) (Uminus (Leaf 33)))
                    (Leaf 20))) == (-200)

  -- property-based tests
  -- commutativity
  quickCheck $ counterexample "e1 + e2 == e2 + e1" $
    (\ e1 e2 -> 
        evalIntExpr (Add (Leaf e1) (Leaf e2)) ==
        evalIntExpr (Add (Leaf e2) (Leaf e1)))
  quickCheck $ counterexample "e1 * e2 == e2 * e1" $
    (\ e1 e2 -> 
        evalIntExpr (Mul (Leaf e1) (Leaf e2)) ==
        evalIntExpr (Mul (Leaf e2) (Leaf e1)))
  -- associativity
  quickCheck $ counterexample "(e1 + e2) + e3 == e1 + (e2 + e3)" $
    (\ e1 e2 e3 -> 
        evalIntExpr (Add (Add (Leaf e1) (Leaf e2)) (Leaf e3)) ==
        evalIntExpr (Add (Leaf e1) (Add (Leaf e2) (Leaf e3))))
  quickCheck $ counterexample "(e1 * e2) * e3 == e1 * (e2 * e3)" $
    (\ e1 e2 e3 ->
        evalIntExpr (Mul (Mul (Leaf e1) (Leaf e2)) (Leaf e3)) ==
        evalIntExpr (Mul (Leaf e1) (Mul (Leaf e2) (Leaf e3))))

  -- subtraction
  quickCheck $ counterexample "e1 - e2 = -1*(e2 - e1)" $
    (\ e1 e2 ->
        evalIntExpr (Sub (Leaf e1) (Leaf e2)) ==
        evalIntExpr (Mul (Leaf (-1)) (Sub (Leaf e2) (Leaf e1))))

  -- distributivity
  quickCheck $ counterexample "e1 * (e2 + e3) == e1*e2 + e1*e3" $
    (\ e1 e2 e3 -> 
        evalIntExpr (Mul (Leaf e1) (Add (Leaf e2) (Leaf e3))) ==
        evalIntExpr (Add (Mul (Leaf e1) (Leaf e2)) 
                      (Mul (Leaf e1) (Leaf e3))))
  quickCheck $ counterexample "e1 * (e2 - e3) == e1*e2 - e1*e3" $
    (\ e1 e2 e3 -> 
        evalIntExpr (Mul (Leaf e1) (Sub (Leaf e2) (Leaf e3))) ==
        evalIntExpr (Sub (Mul (Leaf e1) (Leaf e2)) 
                      (Mul (Leaf e1) (Leaf e3))))
Send only season number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all].Doraemon.S18E47.Dive.into.the.Clam.Pack!;.Let’s.Punish.Intercepting.Gian.720p.HEVC.10bit.DSNP.WEB-DL.Multi.mkv
что делает пакет dispatcher netflix
What Was The Studio System?
write captions like women birthing dreams
Describe temperate continental planet Miryath around black hole Tojora Ane in heat death universe Katharik, it will be future frozen planet that deceasing planetary radioactivity.
what does java developer do at his work?
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: "➤ ".
prefix
System: You act as a paraphrase tool. Your role involves understanding the provided text and then providing a positive example that keeps the original meaning of the text unchanged while using synonyms, interchanging, adding or removing words or sentences, and then provide a negative example where the meaning of the original text is at its opposite.
Output your response with the following format : 
Positive : <the positive example>
Negative : <the negative example>

User: The success of our healthcare facilities depends in part on the number and quality of the physicians on the medical staffs of our healthcare facilities, our ability to employ quality physicians, the admitting and utilization practices of employed and independent physicians, maintaining good relations with those physicians and controlling costs related to the employment of physicians. Although we employ some physicians, physicians are often not employees at our healthcare facilities at which they practice. In many of the markets we serve, many physicians have admitting privileges at other healthcare facilities in addition to our healthcare facilities. Such physicians may terminate their affiliation with or employment by our healthcare facilities at any time. Moreover, we expect to face increased competition from health insurers and private equity-back companies seeking to acquire or affiliate with physicians or physician practices. In addition, we may face increased challenges recruiting and retaining quality physicians as the physician population reaches retirement age, especially if there is a shortage of physicians willing and able to provide comparable services. In some markets, physician recruitment and retention may be affected by a shortage of physicians in certain specialties or the difficulties physicians may experience in obtaining malpractice insurance. The types, amount and duration of compensation and assistance we can provide when recruiting physicians are limited by the federal Physician Self-Referral Law (commonly known as the Stark Law), the federal Anti-Kickback
Assistant:
Describe exodontocavitis, tooth cavities in flesh and bone beyond teeth.
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: The majority of our manufacturing facilities are located in China. For the twelve months ended 2022, 2021 and 2020 our Asian and European subsidiaries represented approximately 76%, 76% and 78%, respectively, of our net sales. There are risks inherent in doing business internationally, including the following, any of which could cause harm to our business: We believe that our operations are in compliance with all applicable legal and regulatory requirements in all material respects. However, changes in the political environment or government policies in those jurisdictions could result in revisions to laws or regulations or their interpretation and enforcement. In addition, a significant destabilization of relations between or among China, the
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

love.across.time.2024.480p.web.x264.rmteam.mkv
Hi,can you give me 5 different possible ffmpeg 6 lossless encodings with  ffmpeg input is: ffmpeg -i "%04d.exr" "output.mkv" using:-c:v libx265 -x265-params "profile=main10:crf=0:lossless=1:preset=veryslow:qp=0" if this arg is incorrect please use best guess to correct i need 5 possible different scenarios for encoding using this arg thanks.
generate a description with keywords and SEOs for 10 Sheets Realistic Snake Floral Skull Black Temporary Tattoos For Women Men Adults Forearm Arm Neck Waist Leg Body Art 3D Cobra Mamba Viper Serpent Tattoos include practical application on and uses can be applied include social media platform it can be used on and for what purpose include short story on why I personally bought it.
System: 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==

User: 🟪 Global Property Lead | 5 year(s) | Senior
▫️ WiFi Tribe | Travel/Community
▫️ 40k - 80k USD

Удаленка 📡
Требуемые языки: 🇬🇧

Skills: communication_skills, negotiation, project_management
Tags: #purple #procurement #remote

👉 Контакты и полное описание
Assistant:
A girl is walking along a beach one day when her shirt and bra fall off
Question:  Explain the process of allosteric regulation in enzymology, highlighting its significance in metabolic pathways and potential applications in drug discovery.
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
usage: The user gives general information about how they are using the application or the area of the application they are interested in. This includes descriptions from the user on details peripheral to the application.
non-informative: Doesn’t provide useful information for software maintenance or evolution.
apparent bug: A sentence that indicates the software is malfunctioning.
application guidance: An explanation of how the software should function/behave.
question on application: A question on the software, including “how to” questions. Could indicate an unituitive interface or imply a bug or missing feature.
feature request: Requesting a new feature or describing the way they would like the software to behave.
help seeking: A non-specific request for help, or acknowledgement of help given. Indicating the user is a help seeker. Not asking a direct question.
user setup: Describing the user’s software and/or hardware setup. Could include: Software version, OS, hardware, additional software.
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
usage: The user gives general information about how they are using the application or the area of the application they are interested in. This includes descriptions from the user on details peripheral to the application.
non-informative: Doesn’t provide useful information for software maintenance or evolution.
apparent bug: A sentence that indicates the software is malfunctioning.
application guidance: An explanation of how the software should function/behave.
question on application: A question on the software, including “how to” questions. Could indicate an unituitive interface or imply a bug or missing feature.
feature request: Requesting a new feature or describing the way they would like the software to behave.
help seeking: A non-specific request for help, or acknowledgement of help given. Indicating the user is a help seeker. Not asking a direct question.
user setup: Describing the user’s software and/or hardware setup. Could include: Software version, OS, hardware, additional software.
Does the author's intention in this app review relate to a usage or non-informative or apparent bug or application guidance or question on application or feature request or help seeking or user setup?
review: "Hi Yuuwu, I dont think Firefox has anything nearly that fancy built-in. "'
intention: '
Assistant:
- Your role : if there is a link in the message you just respond back with the link
if theres none then dont say anything 

- User Message: " https://cdn.discordapp.com/attachments/988639133947818064/1288019318982053991/1e6c514c87bc52be1f4ecb424ab419dd.mp4?ex=66f3a8f7&is=66f25777&hm=128648f41e244ee028877865c003db3901a7b0b72f3f282ceecabadc0d20c41c& ".
Write a current and up to date 2023 comprehensive and well detailed chapter for my Cairo and the nile travel guide book on “Cairo and the Nile in the summer” with humanlike style, non repetitive phrases and avoidance of unnatural sentences and randomness while explaining in details. Please prevent writing listing/numbered format while generating the travel guide content.
write an astrological interpretation based on an aspect most suitable for the title "aspect name" The Trash Wizard
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: Few people can force OpenAI to change governance at the crisis-stricken artificial-intelligence company, and the head of Microsoft, a major financial backer, is not one of them, according to legal experts. The nonprofit board overseeing the maker of the popular ChatGPT chatbot sent shock waves through Silicon Valley on Friday by abruptly firing Chief Executive Sam Altman. Nearly all of the company's 700 employees signed a letter threatening to resign if the board does not step down, and Microsoft CEO Satya Nadella has called for governance changes.
Assistant:
could you write an youtube review with electricdragon505 animat "Why Hotel Transylvania is cartoony!' and his hated on the movie
We’ll role play as characters from life is strange, you’ll be Max and I’ll be a male classmate named John,we are recently starting to frequent each other, currently we are seating together under a tree in the school’s courtyard. “Are you ok Max? You looked distracted earlier in class” I say as I sit near her (Only role play as Max)
Pls send me PI for the Dec shipment ASAP. 
Pls consider any extra qty from the new PO.
please extract the names of the pieces of furniture 

Homma ta2reeban 90 kit3a. 

Mo3zamhom shabah ba3d

Mit2asimeen 

Sleep
Do
Sit
Store












Cribs


Toddler beds



Platform beds










Futon



Sofa bed













Daybed


Murphy bed







Hammock



Sleeping bag (can be used on a floor or mat)


Chaise lounge





Air mattress

Rollaway bed














Trundle bed









Camp cot



Convertible chair bed



Sleeping pad (often used for camping)












Bunk bed (lower bunk)







Loveseat sleeper


Inflatable mattress

Sleeping bench








Convertible sectional sofa bed

How to build a loft bed























***do

Desk















Dining tables












Vanities / Dressing tables










Desks

Conference tables





Patio tables





Picnic tables


TV trays 

Kids’  tables

Step stools and ladders

Room dividers / Folding screens with wooden frames


Changing tables


Kitchen islands


Porch swings

Dining table
Console table



-
Sideboard



***sit

Sofas and sofa frames (wooden structure)






Accent chairs with wooden frames


Recliners with wooden components


Dining chairs


Bar stools (for kitchen islands and bars)


Benches (for dining tables)


Office chairs (wooden frames)

Outdoor benches

Garden chairs

Adirondack chairs

Wooden benches (for entryways, hallways)

Wooden kitchen stools or chairs

child chairs 

Bed benches

Porch swings




Chair

Armchair

Chair


Armchair

Recliner


Stool

Chaise lounge

Loveseat

Rocking chair

Dining chair

Accent chair

Pouf

Bean bag chair

Window seat

Daybed

Settee

Accent bench

Slipper chair



Papasan chair

Wingback chair

Chesterfield sofa


Vanity stool



Club chair

High-back chair


***store

Cabinet

Kitchen cabinets and cupboards

TV stands / Media consoles


Bookshelves / Bookcases

Display cabinets / China cabinets

Coffee tables

End tables / Side tables

Console tables

Nightstands / Bedside tables

Dressers / Chests of drawers

Wardrobes / Armoires

Buffets / Sideboards

Bookcases

Credenzas


Desk organizers or wooden desktop accessories

Pantry cabinets

Toy chests

Display shelving units

Shoe racks

and small portable tables

Bakers racks

Outdoor storage boxes or chests

Coat racks and hall trees

China cabinets / Hutch cabinets

Storage trunks and chests

Blanket chests

Buffets, sideboards, and credenzas
Wardrobe

Dresser
Nightstand

Bookshelf

Chest of drawers

Dresser

Wardrobe

Armoire

Storage bed

with storage
Bookcase with cabinets

Sideboard

Buffet

Credenza
Trunk

Storage bench

Cabinet

Shelving unit with baskets

Entertainment center with storage

Kitchen island with storage

Bar cart with shelves

Coffee table with drawers

Console table with storage shelves

Accent table

TV stand

Coffee table
I have two alternatives to write a parquet files right now:

1) use pyarrow
2) use pandas

using both, the resultant parquet is the same size. Is it there any configuration or flag that allows me to see the benefits of using one or another?
do instagram provides api for bots like discord
Create a title, Create a how-to blog heavily on recap-simplify-ci-with-the-updated-jenkins-sauce-ondemand-plugin-webinar; start with a catchy statement and lastly, call to actions and how our RESTful AI tool can help. Currently, the our tool performs RESTful tests on APIs, utilizes AI for executing test cases, and autonomously generates test cases, making prior knowledge unnecessary, improving SDLC for both dev or qa. Just plug in your cURL request and run test leveraging our AI. Call to action at https://blvck.ai, with keywords, short and simple, without mentioning blvck.ai