agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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: Our business is digital marketing consultation, not an online platform. But since our PRC subsidiary assists our customers to applying customers’ apps to other app platform, we may be subject to various internet-related laws and regulations. These internet-related laws and regulations are relatively new and evolving, and their enactment timetable, interpretation and implementation involve significant uncertainties. For example, On February 7, 2021, the State Administration for Market Regulation, or the SAMR, promulgated Guidelines to Anti-Monopoly in the Field of Platform Economy, or the Anti-Monopoly Guidelines for Platform Economy. The Anti-Monopoly Guidelines for Platform Economy provides operational standards and guidelines for identifying certain internet platforms’ abuse of market dominant position which are prohibited to restrict unfair competition and safeguard users’ interests, including without limitation, prohibiting personalized pricing using big data and analytics, selling products below cost without reasonable causes, actions or arrangements seen as exclusivity arrangements, using technology means to block competitors’ interface, using bundle services to sell services or products. In addition, internet platforms’ compulsory collection of user data may be viewed as abuse of dominant market position that may have the effect to eliminate or restrict competition. As of the date of this Annual Report, neither we nor our PRC subsidiary have been subject to any anti-monopoly investigation, penalty of litigation initiated by government authorities or third parties. Furthermore, we will continue to attach attention to the updates of
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers it (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 it.
    - 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 : it (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "6f14fa5a8c88433486b9d9314af14394",
    "updated": "2025-04-21T01:48:17.946Z",
    "title": "Fig Fudge",
    "subtitle": "This smooth fudge is remarkably simple to prepare and offers a creamy, caramel-like texture. Experiment with different dried fruits for a unique flavor experience.",
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "cashew butter or other nut butter",
          "coconut oil + oil for greasing",
          "dried figs, stemmed",
          "raw cacao powder",
          "honey or coconut syrup",
          "vanilla extract",
          "sea salt",
          "2 tablespoons water, if needed"
        ]
      }
    ],
    "instructions": [
      "Combine the nut butter and 3 tablespoons of coconut oil in the top portion of a double boiler and melt.",
      "Set aside a small teaspoonful of the melted mixture for later use.",
      "Transfer the remaining melted mixture to a high-speed blender or food processor. Snip the figs into smaller pieces using kitchen scissors and add them to the blender.  Incorporate the cacao powder, honey (or coconut syrup), vanilla extract, and salt.",
      "Blend until the mixture is completely smooth.",
      "If the mixture appears too thick, gradually add one to two tablespoons of water until the desired consistency is reached.",
      "Lightly grease a container with coconut oil and pour the fudge mixture into it.",
      "Drizzle the reserved nut butter mixture over the top of the fudge.",
      "Place the container in the freezer for a few hours to allow the fudge to set.",
      "Once firm, remove the fudge from the freezer and allow it to reach room temperature. Cut into squares and serve.",
      "Store leftover fudge in the refrigerator or freezer."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
@app.post("/inference")
async def inference_endpoint(
    audio_file: UploadFile = File(...),
    video_file: UploadFile = File(...),
    bbox_shift: float = Form(0),
    batch_size_args: int = Form(8),
    use_saved_coord_args: bool = Form(False),
    trim_video: bool = Form(False),
):
    # 保存上传的文件到临时目录
    with tempfile.TemporaryDirectory() as tmp_dir:
        audio_temp_path = os.path.join(
            tmp_dir, f"audio{os.path.splitext(audio_file.filename)[1]}")
        with open(audio_temp_path, 'wb') as f:
            content = await audio_file.read()
            f.write(content)

        video_temp_path = os.path.join(
            tmp_dir, f"video{os.path.splitext(video_file.filename)[1]}")
        with open(video_temp_path, 'wb') as f:
            content = await video_file.read()
            f.write(content)

        # 调用推理函数
        output_video_path, bbox_shift_text = inference(
            audio_path=audio_temp_path,
            video_path=video_temp_path,
            bbox_shift=bbox_shift,
            batch_size_args=batch_size_args,
            use_saved_coord_args=use_saved_coord_args,
            trim_video=trim_video,
            result_dir=tmp_dir
        )

        # 将生成的视频作为响应返回
        return FileResponse(
            output_video_path,
            media_type='video/mp4',
            filename=os.path.basename(output_video_path)
        )
        针对上面代码写一个js调用示例代码
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (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 pt.
    - 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 : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "9fbfe115c0e2402ebb7ecb052d003d9b",
    "updated": "2025-04-24T11:04:14.645Z",
    "title": "English Pea Toast",
    "subtitle": "A delightful appetizer, first course, or light meal featuring fresh, early-season peas.  A layer of mild, sweet sheep's cheese complements the peas beautifully, but whipped ricotta is also an excellent choice.",
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "english peas in their pods, shelled (1% to 2 cups peas)",
          "red spring onions or scallions, trimmed (including ½ inch off the green tops), thinly sliced on a sharp angle, soaked in ice water for 20 minutes, and drained well",
          "lemon, halved",
          "kosher salt and freshly ground black pepper",
          "handful mint leaves",
          "extra-virgin olive oil",
          "four ½-inch-thick slices country bread",
          "fresh sheep cheese, fromage blanc, mild goat cheese, or whipped ricotta",
          "parmigiano-reggiano cheese, for grating"
        ]
      }
    ],
    "instructions": [
      "Combine the shelled peas and sliced onions in a bowl. Squeeze the juice of half a lemon over the mixture and season generously with salt and pepper.",
      "Add the mint leaves. Taste and adjust the seasoning with additional lemon juice, salt, or pepper as needed.  Drizzle with ¼ cup of olive oil.",
      "Grill, broil, or toast the bread slices on both sides until golden brown.",
      "Spread the chosen fresh cheese onto each piece of toast and arrange them on serving plates.",
      "Spoon the pea mixture over each toast, pressing gently to adhere the peas to the cheese.",
      "Garnish with a generous grating of Parmigiano-Reggiano cheese and a light drizzle of olive oil."
    ],
    "notes_ingredients": "Fresh sheep cheese, fromage blanc, mild goat cheese, or whipped ricotta can be used.",
    "notes_instructions": null
  }
]
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers zh (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 zh.
    - 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 : zh (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "c2ee2b6ec3934d18b43635ca60979508",
    "updated": "2025-04-25T19:24:57.515Z",
    "title": "Roasting Nuts and Seeds",
    "subtitle": null,
    "description": "Enhance the natural flavors of nuts and seeds by roasting them. This process brings out their rich, nutty notes and delicate oils.",
    "ingredients": [
      {
        "section": "For the Roasted Nuts and Seeds",
        "ingredients": [
          "raw nuts or seeds (amount as per recipe's instruction, or roast in bulk)"
        ]
      }
    ],
    "instructions": [
      "Preheat oven to 300°F.",
      "Spread nuts or seeds in a single layer on a large baking sheet with a rim.",
      "Roast according to the times listed below.",
      "Nuts are ready when fragrant and evenly browned when cut in half. Seeds should be fragrant, slightly puffed, and browned on the outside.",
      "Allow to cool completely. Store in an airtight container or zip-top bag in the refrigerator for up to 6 months or in the freezer for up to 1 year.",
      "Roasting Times:",
      "Almonds: 18-20 minutes",
      "Hazelnuts: 18-20 minutes (after cooling, rub hazelnuts in a large colander to remove skins)",
      "Peanuts: 15-20 minutes",
      "Pumpkin seeds: 10-15 minutes",
      "Sunflower seeds: 10-15 minutes",
      "Walnuts: 15-20 minutes"
    ],
    "notes_ingredients": "Use shelled raw or shelled blanched nuts and seeds.",
    "notes_instructions": "Roasting times are approximate. Monitor the nuts and seeds closely while roasting."
  }
]
hi, who won the world cup in 1992
Send only resolution from below text like 1080p, 720p.etc without any extra text,
        
➡️ Episode - 15
🎧 Language - Hindi Official 
📀 Quality - 480p
⭐️Main channel :[ @SBANIME ]
func _move_to_nearby_location(sittable):
	print("Attempting to find available locations to move player to")
	var seat_position = sittable.global_transform.origin
	var exit_distance: float = 1.0
	var max_distance: float = 10.0 # Max distance from Sittable to try, multiplies the random direction
	var step_increase: float = 0.5
	var max_attempts: int = 10
	var navmesh_offset_y: float = 0.25
	var attempts: int = 0


	var player_position = self.global_transform.origin

	while attempts < max_attempts:
		# Generate random direction
		var random_direction = Vector3(
			randf_range(-0.1, 0.1),
			randf_range(-0.1, 0.1),  # Degree of Y random actually makes this work better at finding candidates
			randf_range(-0.1, 0.1)
		).normalized()
		
		var candidate_pos = seat_position + (random_direction * exit_distance)
		candidate_pos.y = navmesh_offset_y  # to check navmesh at navmesh height

		navigation_agent.target_position = candidate_pos

		# Check if position is reachable
		if navigation_agent.is_navigation_finished():
			currently_tweening = true
			var tween = create_tween()
			navigation_agent.target_position.y += 1 # To avoid player going through floor
			tween.tween_property(self, "global_transform:origin", navigation_agent.target_position, sittable.tween_duration)
			tween.tween_property(neck, "global_transform:basis", original_neck_basis, sittable.rotation_tween_duration)
			tween.tween_callback(Callable(self, "_stand_up_finished"))
			return
		else:
			exit_distance += step_increase
			attempts += 1

		if exit_distance > max_distance:
			exit_distance = 1

	# If no valid location found, try leave node
	print("No available location found after ",attempts, " tries. Testing for leave node.")
	_move_to_leave_node(sittable)
System: You are an expert Data Annotator. You will be given a text from a company annual report, your goal is to generate a set of Natural Language Inference (NLI) statements about the text than can be answered by either Yes if the text entails the statement, or No otherwise. Do not include any numerical reasoning or numbers in the statements.

Step 1: Read the paragraph carefully. 
Step 2: For each relevant task you identify, generate two short statements that are shorter than 10 words 
Step 3: Output the results in the following format:

Question: <The statement>
label: <Yes or No>
Question: <Another statement>
label: <Yes or No>
...

User: We are subject to federal, state, and international laws relating to the collection, use, retention, security, and transfer of personally identifiable information (“PII”). Federal laws include the Gramm-Leach-Bliley Act, the Fair Credit Reporting Act, the Drivers Privacy Protection Act, the Health Insurance Portability and Accountability Act, and Federal Trade Commission policies. Several states, like New York, Nevada, and California, have passed laws in this area, and other jurisdictions are considering imposing additional restrictions or creating new rights concerning PII. These laws continue to develop and may be inconsistent from jurisdiction to jurisdiction. Complying with emerging and changing requirements may cause us to incur substantial costs or require us to change our business practices. Noncompliance could result in significant reputational harm, penalties, and legal liability._In the same year that it adopted Solvency II, the EU adopted the General Data Protection Regulation ("GDPR"). Effective since 2018 after a two-year implementation period, GDPR regulates data protection and privacy in the EU and transfers of personal data outside the EU. GDPR’s main tenet is to give individuals primary control over their personal data. While GDPR has no direct impact on U.S. companies like us without an EU presence, it and any future EU data privacy actions may influence U.S. regulators over time._
Assistant:
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: #Менеджер_по_работе_с_клиентами
700 – 2500 USD на руки

Обязанности:
• Консультация клиентов, обучающихся на онлайн курсе по Инвестициям (фондовый рынок, валютный);
• Ответы на вопросы, разъяснение информации относительно покупок тех или иных ценных бумаг, валют;
• Консультационная помощь в формировании клиентского портфеля.
• Проведение ВИДЕО Zoom-встреч, презентация компании и заключение сделок;

Требования:
• Грамотная речь и умение четко доносить свои мысли;
• Уверенность в себе, твердость намерений;
• Наличие собственного ПК с камерой, гарнитуры, и постоянный доступ к интернету;
• Знание разговорного английского от B2.

Мы предлагаем:
• Работу в удаленном формате;
• График работы 5/2 с 10:00 до 19:00 по московскому времени;
• Конкурентную заработную плату оклад от 400$ до 700$ (по результатам второго этапа с РОПом + % от 1 до 5);
• Оплачиваемое обучение;
• Карьерный рост до РОПа.

Контакты:
+77023122992 (ПИСАТЬ В РАБОЧЕЕ ВРЕМЯ С 10-19 ПО МСК)
zhazira.kenzhegaliyeva@gmail.com

😀😃😄 - 25 вакансий по удаленке ежедневно
  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: 💼 title: 🌟Менеджер по работе с клиентами
🏢 employer: 💰Инвестиционные курсы
📍 location: 🌐Удаленный
🔹 tasks: 🔰Консультация клиентов по Инвестициям, обучающихся онлайн; Ответы на вопросы, разъяснение информации.
💰 salary: 💸700 - 2500 USD на руки
📞 contact details: 📱+77023122992 ( За Gimnazium 24)

Note: This requires a good speaking language and English B2 level. The position offers a competitive salary, flexible schedule, paid courses, and a career progression.
  
Assistant:
You are tasked with generating a concise title for a new chunk based on its summary.

        Step 1: Read the chunk summary.
        Step 2: Identify the key concept or theme.
        Step 3: Create a brief title that captures the essence of the chunk.

        Example:
        Summary: "This chunk contains information about food preferences."
        Output: "Food Preferences"

        Provide only the new chunk title.

        Summary of the new chunk:
        This chunk highlights various activities aimed at enhancing students' practical knowledge and skills for their future careers while fostering connections with industry professionals.
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: Coming in a flash Xion
i want yt-dlp to query an url until 251 format is available and if yes download it
Translate the following text from Russian to Belarusian:

Имя сервера Response must contain only the translation
Problem - Lock has a 3 digit code. Crack it with these hints:

Clue 1: (2 9 1) - One number is correct and in the right place.

Clue 2: (2 4 5) - One number is correct but in the wrong place.

Clue 3: (4 6 3) - Two numbers are correct but in the wrong place.

Clue 4: (5 7 8) - Nothing is correct.

Clue 5: (5 6 9) - One number is correct but in the wrong place.
What is the main difference between capitalism and socialism?
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (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 pt.
    - 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 : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "3680d97e8c1244ad9043865b66efec23",
    "updated": "2025-05-04T22:37:03.977Z",
    "title": "Clarified Butter and Basic Vinaigrette",
    "subtitle": null,
    "description": null,
    "ingredients": [
      {
        "section": "For the clarified butter",
        "ingredients": [
          "unsalted butter"
        ]
      },
      {
        "section": "For the basic vinaigrette",
        "ingredients": [
          "part acid (any kind of vinegar or citrus juice).",
          "parts fat (usually some kind of oil, or homemade mayonnaise).",
          "flavoring (garlic, mustard, eggs - optional)."
        ]
      }
    ],
    "instructions": [
      "Cut the butter into 1-inch cubes.",
      "Place the cubes in a small pot or saucepan over medium-low heat and gently melt until it simmers, avoiding stirring.",
      "As the butter simmers, white foamy dairy solids will rise to the surface.",
      "Use a spoon or ladle to carefully skim off the dairy solids, discarding them and leaving only the clear clarified butter.",
      "After removing most of the milk solids, strain the butter through cheesecloth into a glass storage jar, discarding the solids and cheesecloth afterwards.",
      "Let the clarified butter cool before storing.",
      "Combine all vinaigrette ingredients in a glass container with a lid and shake vigorously until fully blended, or place them in a mixing bowl and whisk until combined.",
      "Alternatively, blend the vinaigrette using a blender or food processor."
    ],
    "notes_ingredients": null,
    "notes_instructions": "Clarified butter can be stored in the refrigerator for up to 6 months or kept at room temperature for up to 3 months.\nVinaigrettes are a versatile staple, perfect for salads as well as delicious marinades and dressings for meat, seafood, and vegetables."
  }
]
If it possible to make a conditional compilation in C with checking a defined macros?
Write a story about a man who tries making orange gloopy slime, but he pours too much of a ingredient designed to make it extra gooey, This ingredient makes it sentient, First it gains consciousness, then the ability to move, then the ability to speak, The man hears it saying "Crud" as it falls off the bowl and splatters onto the floor, It then shapes itself into a blob and runs away, It then learns to shape-shift into numerous forms, taking advantage of it's malleable body, It becomes very playful and well respected