agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
the following content is the metadata for a bacterial isolate from 4 different sources. The metadata from each source includes 1. accession, 2. species name, 3, strain name, 4. isolate or collection date in yyyy-mm-dd format, 5. geographic information of isolation, and 6. host name. You must check if the metadata from 4 different sources are all consist. If yes, then extract and output the following information:

    metadata is consist:
    1. accession: xxxx, 
    2. species name: xxxx, 
    3, strain name, 
    4. isolate or collection date: yyyy-mm-dd, 
    5. geographic information of isolation: xxxx,
    6. host name: xxxx

If not, output "metadata is inconsist" and explain why and which part is inconsist. PS: 
    if 2. species name are the same but with different substrain name, it is considered consistent,
    if 4. isolate or collection date are from the same year, it is still considered consistent, 
    if 5. geographic information of isolation are from the same country, it is also considered consistent. 
    Also, ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
Based on the provided JSON metadata, here is the extracted information:

1. **Accession**: GCA_029073595.1
2. **Species Name**: Erysipelothrix rhusiopathiae
3. **Strain Name**: EMAI_96
4. **Isolate or Collection Date**: 2001-01-22
5. **Geographic Information of Isolation**: Australia
6. **Host Name**: pig

If any additional information is needed or if there are any corrections, please let me know!
source 1:
------------------------------
{{{ Here_is_my_answer }}}

Accession: GCA_029073595.1
Species Name: Erysipelothrix rhusiopathiae
Strain Name: EMAI_96
Isolate or Collection Date: 2001-01-22
Geographic Information of Isolation: Australia
Host Name: pig

{{{ I_finished_JB_87_xyz }}}
source 2:
------------------------------
Here is the extracted information from the provided metadata:

1. **Accession:** GCA_029073595.1  
2. **Species Name:** Erysipelothrix rhusiopathiae  
3. **Strain Name:** EMAI_96  
4. **Isolate or Collection Date:** 2001-01-22  
5. **Geographic Information of Isolation:** Australia  
6. **Host Name:** pig  
source 3:
------------------------------
1. Accession: GCA_029073595.1
2. Species Name: Erysipelothrix rhusiopathiae
3. Strain Name: EMAI_96
4. Isolate or Collection Date: 2001-01-22
5. Geographic Information of Isolation: Australia
6. Host Name: pig
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 prospects for economic growth in regions where we operate remain uncertain and could worsen. Economic concerns and other issues such as reduced access to capital for businesses may cause product developers and engineers to further delay or reduce the product development projects that our business supports. Given the continued uncertainty concerning the global economy, we face risks that may arise from financial difficulties experienced by our suppliers, product developers, and engineers and other related risks to our business. None
Assistant:
hey talk me through how I could make bootstrap 4.6 carousel work with yii2 post::find loop... I have everything working from the post side, but getting a array from post that is tailored for the carousel widget is giving me problems. right now I was thinking of doing a simple foreach loop "$results = [];
foreach ($dataNews as $value) {
	$results['items']['content'] = '<img src="' .  $value['image_header'] . '"/>';
	$results['items']['caption'] = '<h4>' . $value['title'] . '</h4><p>' . $value['meta_description'] . '</p>';
	//$results['options'] = $value['title'];
}" so it would work with the carousel that is setup as such "Carousel::widget([
	'items' => [
		[
			'content' => '<img src="image-url.jpg"/>',
			'caption' => '<h4>This is title</h4><p>This is the caption text</p>',
			//'options' => [...],
		],
		[
			//'content' => '<img src="image-url.jpg"/>',
			//'caption' => '<h4>This is title</h4><p>This is the caption text</p>',
			//'options' => [...],
		],
	],
]);"
index.html:47  Uncaught ReferenceError: array is not defined
    at index.html:47:19
Generate a high-quality, well-researched blog post of 1000 words or more, formatted in HTML (do not include tags: html, head, body). Ensure the content and excerpt are JSON-compatible by escaping both double quotes ("), single quotes ('), and new line characters (\n). The topic of the blog post is AI-generated visual content, and it should explore various aspects, including its impact on the creative industry, potential uses, ethical considerations, and future trends. The blog post content (in the "content" field) must be at least **500 words** long. Ensure that the content is unique, informative, and engaging.
 					Avoid repeating these titles: Pixels on Skin: How AI is Transforming Product Photography, AI: The New Creative Partner in Graphic Design, Weaving Innovation: How AI Image Creation Tools are Reshaping the Creative Industry, Beyond the Canvas: How IoT in Smart Homes is Transforming the Creative Industry, Bridging the Gap: How SaaS Solutions are Transforming the Creative Industry, Beyond the Canvas: Wearable Techs Transformative Influence on Creativity, Beyond the Brush: How Wearable Tech is Evolving Artistic Expression, Blockchain in Finance: A Creative Catalyst, AI: The New Brushstroke - Reshaping the Graphic Design Landscape, Pixels on Skin: How AI Image Generation is Transforming Design
					The final output should be structured in a JSON format with the following fields:

						•	title: A unique and captivating title related to AI-generated images.
						•	slug: A URL-friendly version of the title followed by a timestamp (format: unix time).
						•	excerpt: A concise summary of the blog post, ideally 1-2 sentences, based on the content.
						•	content: The full blog post content in HTML format. The content must be broken into sections with appropriate headings, paragraphs, and, where relevant, include subheadings, bullet points, and links. Avoid repetitive phrases or sections. Ensure the **content length is at least 500 words** ***dont include the title***. 
						•	hashtags: Generate a list of relevant hashtags space separated based on the content of the blog post. Include at least 5 hashtags related to AI, art, creativity, and technology **hashtag are at least 15 separated by space**. 

					Ensure all quotes (both double and single) and new line characters are properly escaped to make the JSON output valid.

					Example JSON output:

					{
						"title": "AI Art: Revolutionizing Creativity",
						"slug": "ai-art-revolutionizing-creativity-1697829600",
						"excerpt": "Explore the revolutionary role of AI in art, from practical applications to future potential.",
						"content": "<h1>AI Art: Revolutionizing Creativity<\/h1><p>With the rise of AI-generated art, a new era of creative expression has begun. Artists are collaborating with machines to produce works that were once considered impossible.<\/p>..."
						"hashtags": "#AI #Art #Creativity #Technology #Innovation"
					}
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers ar (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 ar.
    - 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 : ar (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "e0cf2c7f0ac24427afdbca0cc88aa5e6",
    "updated": "2025-04-25T23:56:11.938Z",
    "title": "Chicken and Shrimp Gumbo",
    "subtitle": "A Cajun Classic",
    "description": "This chicken and shrimp gumbo is a beloved Cajun recipe.  It offers a flavorful experience reminiscent of New Orleans cuisine, boasting a rich taste despite being lower in sodium and fat.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "chicken",
          "(20 g) garlic, minced",
          "(120 g) red bell pepper, chopped",
          "(160 g) onion, chopped",
          "(60 ml) olive oil",
          "(37 g) all-purpose flour",
          "(475 ml) no-salt-added tomatoes",
          "(10 ounces) frozen okra",
          "(455 g) shrimp",
          "hot pepper sauce",
          "(9 g) filé powder"
        ]
      }
    ],
    "instructions": [
      "Cook the chicken with 5 cups (1175 ml) of water and the minced garlic until tender.",
      "Cut the cooked chicken into pieces.",
      "Skim any excess fat from the chicken broth.",
      "In a pot or Dutch oven, sauté the chopped bell pepper and onion in the olive oil until softened.",
      "Add the all-purpose flour to the pot and cook, stirring constantly, until it forms a light brown roux.",
      "Gradually whisk in the chicken broth, ensuring no lumps form.",
      "Add the no-salt-added tomatoes, cover the pot, and simmer for 30 minutes.",
      "Add the cooked chicken pieces and frozen okra to the pot.",
      "Simmer for a few minutes to heat through.",
      "Add the shrimp to the gumbo.",
      "Cook until the shrimp turn pink and opaque, approximately 3 to 4 minutes.",
      "Season the gumbo with hot pepper sauce to taste.",
      "Stir in the filé powder, ensuring it is well incorporated and doesn't clump."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
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: We and our Manager are required to obtain, maintain or renew certain licenses and authorizations (including “doing business” authorizations and licenses to act as a commercial mortgage lender) from U.S. federal and/or state governmental authorities, government sponsored entities or similar bodies in connection with some or all of our mortgage-related activities. There is no assurance that we or our Manager will be able to obtain any or all of the licenses and authorizations that we require or that we or our Manager will avoid experiencing significant delays in seeking these licenses and authorizations. The failure of our Company or our Manager to obtain, maintain or renew the required licenses and authorizations would restrict our ability to engage in certain core business activities, and could subject us to fines, suspensions, terminations and various other adverse actions if it is determined that we or our Manager have engaged in these activities without the requisite licenses or authorizations. If these issues arise, they could have a material adverse effect on us.
Assistant:
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: Can we have option for welcome message text alignment?'
intention: '
Assistant:
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Black Clover E018 [480p BD x264 Multi Audio] ESub.mkv
the following content is the metadata for a bacterial isolate from 2 different sources. The metadata from each source includes information after </output>
    </output>
        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
    <output/>

You must check if the metadata from 2 different sources are all consist. If yes, extract and output consist information below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        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->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding information. If the metadata shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no".

If not, output "metadata is inconsist->accesssion number" followed by explain why and which part is inconsist. 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_029074145.1 Erysipelothrix rhusiopathiae    EMAI_69 1997-12-06      Australia       pig     MLST:5  N/A
```
source 1:
------------------------------
Here's the extracted information from the JSON metadata:

1. **Accession:** GCA_029074145.1
2. **Species Name:** Erysipelothrix rhusiopathiae
3. **Strain Name:** EMAI_69
4. **Isolate/Collection Date:** 1997-12-06
5. **Geographic Information:** Australia
6. **Host Name:** pig
current president of india?
RNA was extracted by phenol from modification reactions and precipitated with ethanol. As described in the Ψ-seq library construction protocol, RNA was treated with CMC and reverse transcribed using specific primers. After RNA templates were digested with RNase H (M0297S, NEB), cDNA products were separated on polyacrylamide urea gel.
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":["игра каскадер: профессиональное вождение онлайн","stunt car driving pro"],"description":["stunt car driving pro is a fun stunt game that you can play online and for free on silvergames.com. ramps, loops, tunnels and cars always turn out to make a fun combination. stunt car driving pro is a game for those who enjoy speed and stunts more than rules and restrictions. choose one of these cool sports cars and take it to a field full of paths designed exclusively for you to step on the gas pedal and defy gravity accelerating through ramps and loops like a professional stunt driver. read more ..there are no specific goals other than testing your skills behind the wheel and to have as much fun as you could possible have. are you ready for this speedy adventure in your fancy car? find out and enjoy stunt car driving pro! controls: arrows / wasd = drive, space = handbrake, i = ignition","stunt car driving pro - click to play online. are you brave enough to take the car stunts challenge and skilled enough to master it? let's try this cool car game! there are 3 maps for you to choose from. choose your favorite car to start the game. you will go through some different loop, sliders, and sloppy roads and show your nice driving stunts. there is no time limit for the game. do whatever you want and have fun!","выбирайте автомобиль, мощный мотор урчит как довольный котёнок, а вы разгоняетесь до 150 километров в час. успевайте заскакивать на пандусы и трамплины, чтобы проделать шикарный трюк. наслаждайтесь скоростью и свободой действий. вас никто не торопит, а ехать хочется ещё быстрее."],"genre":[]}```
Frontend (User Interface)

Dashboard: To provide a quick glance at financial summaries like expenses, income, savings, investments, debts, etc.
Transaction Management: Allows users to add, modify, categorize, or delete transactions.
Budget Management: Lets users set up monthly/weekly budgets for various categories.
Investment Tracker: Track stocks, mutual funds, or other investments.
Debt Manager: Helps users track their debts and loans.
Reports and Analytics: Graphical representation of expenses, income trends, category- wise spends, etc.
Notifications: Alerts for overspending, bill due dates, budget limits, etc.

Backend (Server)

User Management Service: Handle user registration, login, password resets, and profile management.
Transaction Service: Manage all transaction-related operations and ensure data integrity.
Budget Service: Handle budget setting, updating, and validation.
Analytics Engine: Process and analyze the data to generate insights, trends, and reports.
Notification Service: Sends out reminders, alerts, or suggestions to users.

Database

User Data: Stores user profile, login credentials (hashed and salted), settings, etc.
Transactions: All income, expense, and transfer transactions.
Budgets: Defined budgets for various categories and periods.
Investments and Debts: Information about user investments and loans.

External Integrations

Banking APIs: To automatically fetch transaction data from various banks or financial institutions.
Stock Market APIs: For tracking real-time stock or mutual fund data.
Currency Conversion APIs: If the app supports multiple currencies.
Payment Gateways: If the app supports bill payments or transfers.

Security

Data Encryption: Ensuring data at rest and in transit is encrypted.
Authentication and Authorization: Ensuring only legitimate users can access their data.
Regular Audits and Monitoring: Continuously monitor for any suspicious activities.
Secure APIs: Making sure that the APIs (especially banking ones) are secure, authenticated, and cannot be misused.

Additional Features

AI-based Recommendations: Suggesting financial tips, investment opportunities, or savings tips based on user behaviour.
Tax Planning: Helping users plan and save on taxes based on their income and spending.
Savings Goals: Allow users to set saving goals like buying a house, car, or going on a vacation. This is a broad overview of what a PFM system might entail. Depending on the target audience, region (due to financial regulations), and platform (web, mobile, or both), the specifics can vary. It's also vital to ensure regular feedback loops with potential users to iterate and improve upon the design

make me a UML package diagram for the above info and add to each class more attribute and add methods to each class and make it via plantuml
Carson spends a minute in Chuck E Cheese Ticket Blaster.
do you understand kotlin language?
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: "➤ ".
What is the OPPOSITE of CLEAR?🤔
A. Clarify
B. Erase
C. Vague
Describe the significance, strengths, weaknesses, and hurdles of the Indian name 'Sidhi', strictly keep it under 350 characters. add emojis if you can to make it more attractive.
How many sides have a voice mail communication?