agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: 
You will receive a question-answer pair. Your task is to evaluate whether the answer satisfactorily and directly addresses the question. Use the examples below to guide your assessment.

If the answer is precise, relevant, and can answers the question, return 1. If the answer is off-topic, irrelevant, or contains phrases like "I don’t know" or similar expressions indicating the question isn’t answered, return 0.

Examples:

Example 1:
Question: "Who was the first person to walk on the moon?"
Answer: "The first person to walk on the moon was Neil Armstrong in 1969."
Result: 1

Example 2:
Question: "Who was the first person to walk on the moon?"
Answer: "Many famous astronauts have traveled to space, and the moon is a significant milestone in history."
Result: 0

Example 3:
Question: "What is the primary cause of global warming?"
Answer: "I don’t know."
Result: 0

Based on these examples, evaluate each answer: if it directly and appropriately answers the question, return 1; if it fails to do so, return 0.


User: Question: Địa điểm 1 của cơ sở trực thuộc nằm ở đâu?
Answer:Địa điểm 1 của cơ sở trực thuộc nằm ở 97 Võ Văn Tần, P.
Result only 0 or 1. Don't add anything else:
Assistant:
Assistant: 
User: System: You are a professional, authentic machine translation engine.
User: Translate the following source text to Simplified Chinese Language, Output translation directly without any additional text.
Source Text: 📞098-2477001

Translated Text:
Assistant:
Assistant:
What is the order or the object or pronomknal pronouns in Portuguese when there is a modal verb with a infinitive verb
i created a fictional comedy event where Ben Gleib,Kevin Bridges,Ricky Gervais,and George Lopez perform.
@Mr. Affinity whats "Owa Owa"
i lost my previos number and i want to share my new number with the bank so they can contact me with the new number how can write an email professionally
Ошибка при обработке сообщения: Telegram server says - Bad Request: can't parse entities: Unsupported start tag "" at byte offset 699
what are common hazards related to working alone?
[SYSTEM]: User provided an image with data:  The image shows a notification on a social media platform, specifically on the "SOSA" account. The notification is informing the user that their file has been uploaded securely to the encrypted Bytes.com server with a 100% homomorphic feature. The file in question is a game file for "Fortnite: Battle Royale" with a size of 2.1bigr and a progress of 25:38, indicating that the file is currently being uploaded and is 25 minutes and 38 seconds away from completion. The notification also indicates that the user will be returning after one month, suggesting that this file transfer is part of a recurring or scheduled process. The overall message of the notification is to inform the user of the progress and status of their file upload to the encrypted server.
PROMPT: user: h
assistant: Hello! How can I assist you today?
user: h
func process_surface_movement(dt: float, input_dir: Vector2) -> void:
	process_gravity(dt);

	var is_sprinting = Input.is_action_pressed("sprint");
	var target_rate = 1.0;

	if is_sprinting: target_rate = sprint_acceleration_rate;
	if is_crouching: target_rate = crouch_acceleration_rate;
	
	move_rate = lerp(move_rate, target_rate, dt * acceleration_rate_change_speed);

	var current_friction = ground_friction if is_on_floor() else air_friction;
	var friction_factor = get_friction_rate(current_friction, dt);

	var direction = (transform.basis * Vector3(input_dir.x, 0, input_dir.y)).normalized() * move_rate;
	var computed_acceleration = get_acceleration(max_speed, current_friction, dt);
	var current_acceleration = computed_acceleration if is_on_floor() else air_acceleration;

	movement_vector = direction * current_acceleration;
	movement_vector.y = 0;

	velocity += movement_vector * dt;
	velocity.x *= friction_factor;
	velocity.z *= friction_factor;

	if not snap_up_stairs_check(dt): 
		move_and_slide();
		snap_down_to_stair_check();

	if Input.is_action_just_pressed("jump"): do_jump();
Generate an image creation prompt specifically optimized for the Flux Schnell model. The prompt should vividly describe the scene or concept expressed by the following sentence: 'This society, shrouded in secrecy, comprised poets, warriors, and nobles who revered her as the muse of erotic revolution.'. Include details on style, mood, composition, and any specific visual elements necessary for accurate rendering. Don't make it too long also
(In a massive stony shores biome)

[player]: “Okay…now that the Ender Dragon is defeated, I can do whatever I want.”

([player] comes across something - it was a serpentine monster with wings, and had loads of scales. It also has yellow eyes, and sharp fangs. However, the creature’s wings seem to be handling its weight perfectly - even with the weight of its massive belly. The creature aileron rolls at [player], who dodges the attack)

[player]: “Whoa! Calm down! I’m not a threat!”

Female Lesser Naga: “Oh, sorry. I don't tend to get human visitors around here.”
let's do a quiz. you'll ask me questions related to the middle eastern (modern history/politics) and i'll provide an answer. don't ask me yes/no questions or questions that can be answered with one word. based on the quality on the response and its accuracy , you'll rate my reply with a percentage
Keto Diet Digital Marketing Guide: Capturing and Engaging a Niche Audience, minimalist tone, generate SEO's, tips, how you can sell, strategies, platform to use to sell like stan store, keywords for instagram
import pandas as pd  
import numpy as np  
import yfinance as yf
import matplotlib.pyplot as plt  
import talib

def get_stock_data(ticker, period='1y'):
    """Retrieve stock data"""
    try:
        data = yf.download(ticker, period=period)
        if data.empty:
            raise ValueError("No data retrieved. Please check the ticker symbol.")
        return data
    except Exception as e:
        print(f"Error fetching data: {e}")
        return None

def main():
    ticker = input("Enter the stock ticker: ")
    data = get_stock_data(ticker)

    # Define 'Close_column' to access the closing price column
    Close_column = 'Close' # Added this line to Define Close_column

    data['RSI_14'] = talib.RSI(data[Close_column].values, timeperiod=14)  
    data['RSI_28'] = talib.RSI(data[Close_column].values, timeperiod=28)  


    # Define buy and sell signals  
    data['Buy_Signal'] = np.where((data['RSI_14'] < 30) & (data['RSI_28'] < 30), 1, 0)  
    data['Sell_Signal'] = np.where((data['RSI_14'] > 70) & (data['RSI_28'] > 70), -1, 0)  

    # Combine signals  
    data['Signal'] = data['Buy_Signal'] + data['Sell_Signal']  
    data['Position'] = data['Signal'].replace(to_replace=0, method='ffill')  

    # Plotting  
    plt.figure(figsize=(14, 7))  
    plt.plot(data[Close_column], label='Close Price', alpha=0.5)  # Updated here
    plt.scatter(data.index[data['Buy_Signal'] == 1],   
                data[data['Buy_Signal'] == 1][Close_column],   # Updated here
                label='Buy Signal', marker='^', color='g')  
    plt.scatter(data.index[data['Sell_Signal'] == -1],   
                data[data['Sell_Signal'] == -1][Close_column],   # Updated here
                label='Sell Signal', marker='v', color='r')  
    plt.title('Double RSI Trading Strategy')  
    plt.legend()  
    plt.show()

if __name__ == "__main__":
    main()

I get the error:Exception                                 Traceback (most recent call last)
<ipython-input-23-330d4149cfad> in <cell line: 33>()
     32 
     33 if __name__ == "__main__":
---> 34     main()

1 frames
/usr/local/lib/python3.10/dist-packages/talib/__init__.py in wrapper(*args, **kwds)
     62                 _kwds = kwds
     63 
---> 64             result = func(*_args, **_kwds)
     65 
     66             # check to see if we got a streaming result

talib/_func.pxi in talib._ta_lib.RSI()

talib/_func.pxi in talib._ta_lib.check_array()

Exception: input array has wrong dimensions
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: Like other electric and natural gas utilities, our energy centers, fuel storage facilities, transmission and distribution facilities, and information systems may be affected by terrorist activities and other intentionally disruptive acts, including cyber attacks, which could disrupt our ability to produce or distribute our energy products. There have been attacks on energy infrastructure, such as substations and related assets, in the past, and there may be more attacks in the future. Any such incident could limit our ability to generate, purchase, or transmit power or natural gas and could have significant regional economic consequences. Any such disruption could result in a significant decrease in revenues, a significant increase in costs including those for repair, or adversely affect economic activity in our service territory which, in turn, could adversely affect our results of operations, financial position, and liquidity.
Assistant:
explicame porque We have received your request for a copy of the police report filed with the Los Angeles Police Department on January 30, 2019.

 

Your request was made under the California Public Records Act (the Act). The Department is cognizant of its responsibilities under the Act. It recognizes the statutory scheme was enacted to maximize citizen access to the workings of government. The Act does not mandate disclosure of all documents within the government’s possession. Rather, by specific exemption and reference to other statutes, the Act recognizes that there are boundaries where the public’s right to access must be balanced against such weighty considerations as the right of privacy, a right of constitutional dimension under California Constitution, Article 1, Section 1. The law also exempts from disclosure records that are privileged or confidential or otherwise exempt under either express provisions of the Act or pursuant to applicable federal or state law, per California Government Code Sections 7927.200; 7927.700; 7923.600-7923.625; 7927.705; and 7922.000.

In accordance with Sections 7923.600-7923.625 of the California Government Code, records of investigations conducted by, or investigatory files compiled by, any local police agency for law enforcement purposes, are exempt from disclosure. To the extent that records were located, they are either investigatory records themselves or properly part of an investigative file. Therefore, we are denying your request. The records may be provided pursuant to a subpoena or court order related to pending litigation.

  

Should any records be located, to the extent the information is recorded, a summary including the time, date, and location of occurrence, the time and date of the call or report, the name and age of the victim, and a brief statement of the circumstances may be made available to you upon request.

  

If you are the victim or the victim’s legal representative, you may contact the Los Angeles Police Department’s Records and Identification Division at (213) 486-8110 for further information on obtaining reports for victims of crimes.

 

If you have any questions, please respond to this email.

 

Respectfully,

 

LAPD Public Records & Subpoena Response Section, CPRA Unit
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: As of December 31, 2020, we had approximately $5.25 billion in cash, cash equivalents, and investments. These investments are subject to general credit, liquidity, market, and interest rate risks. We may realize losses in the fair value of these investments, which would have a negative effect on our consolidated financial statements. In addition, should our investments cease paying or reduce the amount of interest paid to us, our interest income would suffer. The market risks associated with our investment portfolio may have an adverse effect on our results of operations, liquidity, and financial condition. The amount of and our ability to use net operating losses and research and development credits to offset future taxable income may be subject to certain limitations and uncertainty.
Assistant:
under what condition can a atm withdrawal be reversed if the money fails to out of the atm what code is sent to void that transcation?
plan for me home furniture campagin plan for 15 days in june and story line for social media and catch phrases
Polish my paper
You are a database expert and SQL optimizer. You will be given a SQL query and its rewritten variant. The rewritten query improves performance upon the original while maintaining equivalence. Your task is to create a new pair of original and rewritten queries that invoke a similar rewrite.

[ORIGINAL QUERY]```with customer_total_return as (select sr_customer_sk as ctr_customer_sk,sr_store_sk as ctr_store_sk,sum(SR_FEE) as ctr_total_return from store_returns,date_dim where sr_returned_date_sk = d_date_sk and d_year =2000 group by sr_customer_sk,sr_store_sk) select c_customer_id from customer_total_return ctr1,store,customer where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2 from customer_total_return ctr2 where ctr1.ctr_store_sk = ctr2.ctr_store_sk) and s_store_sk = ctr1.ctr_store_sk and s_state = 'TN' and ctr1.ctr_customer_sk = c_customer_sk order by c_customer_id limit 100; ```

[REWRITTEN QUERY]```with customer_total_return as ( select sr_customer_sk as ctr_customer_sk, sr_store_sk as ctr_store_sk, sum(SR_FEE) as ctr_total_return from store_returns join date_dim on sr_returned_date_sk = d_date_sk where d_year = 2000 group by sr_customer_sk , sr_store_sk ), avg_customer_return as ( select ctr_store_sk, avg(ctr_total_return) as avg_return from customer_total_return group by ctr_store_sk ) select c_customer_id from customer_total_return ctr1 join store on s_store_sk = ctr1.ctr_store_sk join customer on ctr1.ctr_customer_sk = c_customer_sk join avg_customer_return acr on ctr1.ctr_store_sk = acr.ctr_store_sk where ctr1.ctr_total_return > acr.avg_return * 1.2 and s_state = 'TN' order by c_customer_id limit 100;```

Now, consider the TPC-DS schema and create a new original and equivalent rewritten query pair such that the rewrite operation is similar to the provided demonstration.Keep the following points in mind while creating the new query pair:
1. The original query must contain CTEs.
2. The original query must make use of the following fact tables: ['inventory', 'store_returns']. Below is the join graph for these fact tables:
    ['inventory(inv_warehouse_sk) references warehouse(w_warehouse_sk);', 'inventory(inv_date_sk) references date_dim(d_date_sk);', 'inventory(inv_item_sk) references item(i_item_sk);']
    ['store_returns(sr_hdemo_sk) references household_demographics(hd_demo_sk);', 'store_returns(sr_reason_sk) references reason(r_reason_sk);', 'store_returns(sr_item_sk) references item(i_item_sk);']
5. The original query must employ 2 joins.
6. The original query must employ the following operators in its WHERE clause: ['max'].
7. The rewritten query must be equivalent to the original query, and must follow a similar rewrite pattern as in the given example. Enclose the original and rewritten queries within ``` and ```.
write a 2011 nba season with kobe bryant fadeaway three over nowitski
Naruto and Freedom planet all characters react to Lilac, Carol, Milla and Neera is under a love spell and they’re targeted Naruto.  Kakashi: (laughs) “You naruto become harem Freedom planet”
Please filter a list of words to include only valid, neutral, and positive terms that are safe for use in a word game. Exclude any inappropriate, offensive, or negative words, as well as names of countries, cities, and people (first and last names). Correct any spelling errors and lowercase. Return the results in a JSON array with only the filtered words. Source data: [sicken, sickener, sickening, sickle, sicklepod, sickly, sickness, sickroom, side, sidebar, sidecar, sided, sidelight, sideline, sideling, sidelong, sidera, sideral, siderite, sideritis, siderocyte, sideromancy, sideropenia, siderosis, sides, sidesaddle, sidesman, sidestep, sidewall, sideway]
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": "b040c060063b48fc8236a77f1de22240",
    "updated": "2025-05-09T01:12:46.451Z",
    "title": "Chieftain Khal Drogo's Black Ice Cream",
    "subtitle": null,
    "description": "Drogo's black eyes, long black hair, and black beard highlight his fierce and powerful nature. At first, he appears harsh towards his wife Daenerys, but like this black ice cream that melts smoothly in your mouth, Drogo reveals a tender and sensitive side for her. As you enjoy this exceptional ice cream, the image of the mighty and invincible Drogo will remain with you. Beneath the dark exterior lies a loving and devoted husband.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "black food color",
          "sugar",
          "heavy cream",
          "activated charcoal",
          "mint extract",
          "black food color",
          "dry ice",
          "half and half"
        ]
      }
    ],
    "instructions": [
      "1. Store the dry ice in the freezer.",
      "2. Remove the dry ice and carefully break it into powder.",
      "3. In a large bowl, combine the half and half, activated charcoal, heavy cream, sugar, mint extract, and food color.",
      "4. Mix all ingredients until the mixture becomes frothy.",
      "5. Gradually and carefully incorporate the powdered dry ice, stirring continuously until the mixture thickens.",
      "6. Consume the ice cream only after the dry ice has completely evaporated."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
fivem scripting I'm working on a crossbreeding farming script

neg = {'X','W'}
pos = {'Y','G','H'}
plant1 = 'YGXWHH'
plant2 = 'XWHYYG'
plant3 = 'GHGWYY'
plant4 = 'GHGWXY'
planttobreed = 'GWGYHY'

the planttobreed is in the middle surrounded by the other 4 plants 
a plant gets its trails from the surrounding plants plus its current traits
if a plant has a neg trail then it needs two pos traits of the same kind to overcome it.
how would I calculate the what plant 5 (the middle plant) would have as its traits I want a format of 6 traits like the other plants
Assistant: 
User: find the slope of the line passing through the points (3, 6) and (3, -8)
- please refrain from using markdown
- instead of using "frac{17}{4}", use "17/4"
Assistant:
Does Turkey recognize Cyprus?
Переведи на английский с адаптацией:
(но есть ещё множество переведённых мной строк, ждущих одобрения, помимо этих)
7. Let Σ = {a, b}.
(a) Find a simple nondeterministic finite automaton accepting (a ∪ b)
∗aab.
(b) Convert the NFA of part (a) to a DFA by the method in Sipser. Provide only the
portion of the DFA that’s reachable from the start state.

Keep the reply as concise as you can, but explain all of your steps. Describe exactly how I should draw the DFA, if it needs to be drawn on paper. Thanks!

(10) Let Σ = {0, 1, +, =} and
ADD = {x + y = z | x, y, z are binary integers, and z is the sum of x and y}.
Show that ADD is not regular.

Likewise, if a DFA or any sort of graph needs to be drawn, describe simply exactly how I can draw it on paper.