TC

Okay, here's the translation of "How To Use Google VEO 3 JSON Prompting To Create $100k AI Ads" into traditional Chinese, sentence by sentence: **Original:** How To Use Google VEO 3 JSON Prompting To Create $100k AI Ads **Translation:** 如何使用 Google VEO 3 的 JSON 提示來創建價值十萬美元的人工智慧廣告 **(Explanation of Choices):** * **如何 (Rúhé):** How to, in the sense of "method." * **使用 (Shǐyòng):** To use. * **Google VEO 3 的 JSON 提示 (Google VEO 3 de JSON tíshì):** Google VEO 3's JSON prompting. It keeps the technical terms "Google VEO 3" and "JSON" as they are commonly understood. 的 is the possessive particle. 提示 means "prompt" or "prompting." * **來創建 (Lái chuàngjiàn):** To create (with the implication "in order to create"). * **價值十萬美元 (Jiàzhí shíwàn měiyuán):** Worth $100,000, or "valued at $100,000". 十萬 is 100,000. 美元 is US dollar. * **的人工智慧廣告 (de réngōng zhìhuì guǎnggào):** Artificial Intelligence ads/advertisements. 人工智慧 (réngōng zhìhuì) is "artificial intelligence," and 廣告 (guǎnggào) is "advertisement."

#賺錢方法
2025-08-06 19:5135 分鐘 閱讀

內容介紹

以下影片解釋了如何使用一種名為 JSON 提示的新提示格式來創建病毒式廣告。 (Yǐxià yǐngpiàn jiěshì le rúhé shǐyòng yī zhǒng míngwéi JSON tíshì de xīn tíshì géshì lái chuàngjiàn bìngdú shì guǎnggào.)它展示了像是 VO3 Tree AI 廣告的例子，並示範如何使用不同的品牌和角色來創造視覺效果驚豔的開箱影片和專業廣告。(Tā zhǎnshì le xiàng shì VO3 Tree AI guǎnggào de lìzi, bìng shìfàn rúhé shǐyòng bùtóng de pǐnpái hé juésè lái chuàngzào shìjué xiàoguǒ jīngyàn de kāixiāng yǐngpiàn hé zhuānyè guǎnggào.)這影片提供了所需的提示詞，並解釋了像 Open Art 和 Google Flow 這樣的平台是如何用於生成這些影片的。(Zhè yǐngpiàn tígōng le suǒ xū de tíshì cí, bìng jiěshì le xiàng Open Art hé Google Flow zhèyàng de píngtái shì rúhé yòng yú shēngchéng zhèxiē yǐngpiàn de.)它還提供了一個客製化的聊天機器人連結，用於創建 JSON FO3 提示，鼓勵創意實驗，並建議進一步探索 AI 動畫故事。(Tā hái tígōng le yī gè kèzhì huà de liáotiān jīqìrén liánjié, yòng yú chuàngjiàn JSON FO3 tíshì, gǔlì chuàngyì shìyàn, bìng jiànyì jìnyībù tànsuǒ AI dònghuà gùshì.)

關鍵信息

  • JSON提示是一種組織影片提示的方式，這能帶來令人印象深刻的成果。
  • 你可以用它來創作各種不同類型的影片，包括開箱影片、廣告和以角色為基礎的內容。
  • 這段影片提供了一個客製化機器人的使用權限，這個機器人可以生成 JSON 提示詞，並且展示了由 AI 生成的影片範例，像是星巴克的廣告和香水廣告，以展示 JSON 提示詞的強大之處。
  • 它也建議使用 Open Art 或 Google Flow 來創建影片。Links 及一份通訊的描述在那裡，以幫助人們取得提示和內容。（它也建議使用 Open Art 或 Google Flow 來創建影片。為了幫助人們獲得提示和內容，文章中也提供了連結和一份通訊的描述。）

時間軸分析

內容關鍵字

好的，以下將逐句翻譯 “VO3 Tree AI ads & JSON Prompting” 這篇文章的標題及可能之後的文章內容為繁體中文：**標題:*** **VO3 Tree AI ads & JSON Prompting** -> VO3 樹狀人工智能廣告與 JSON 提示 (或者：VO3 樹狀人工智能廣告及 JSON 提示技術)**假設文章內容 (以下為假設，因為我沒有實際的文章內容):*** **VO3 Tree AI is a new approach to creating more effective and personalized advertisements.** -> VO3 樹狀人工智能是一種創建更有效且個人化廣告的新方法。* **It uses a hierarchical decision tree structure to determine the best ad to show to a specific user, based on their individual characteristics and behavior.** -> 它使用分層決策樹結構，根據特定用戶的個別特徵和行為，決定要向其展示的最佳廣告。* **JSON Prompting allows developers to easily define the parameters that the AI uses to generate these ads.** -> JSON 提示技術允許開發者輕鬆定義人工智能用來生成這些廣告的參數。* **This makes it easier to create a wide variety of ads that are tailored to different audiences.** -> 這使得製作針對不同受眾量身定制的多種廣告變得更加容易。* **The combination of VO3 Tree AI and JSON Prompting offers a powerful new way to create and deliver targeted advertising campaigns.** -> VO3 樹狀人工智能與 JSON 提示技術的結合，提供了一種強大的新方法來創建和傳遞目標明確的廣告活動。* **In this article, we will explore how VO3 Tree AI works and how JSON Prompting can be used to optimize its performance.** -> 在本文中，我們將探討 VO3 樹狀人工智能如何運作，以及如何使用 JSON 提示技術來優化其效能。* **We will also cover examples of how to implement these technologies in your own advertising strategies.** -> 我們還將介紹如何在您自己的廣告策略中實施這些技術的範例。**重要說明：*** 以上翻譯盡可能地保持原文的含義，並使用傳統中文的表達方式。* 由於我沒有實際的文章內容，我只能根據標題和常見的主題做出假設性的翻譯。* 如果提供實際文章內容，我能够提供更准确和贴切的翻譯。* 根據文章的具體內容，某些詞語的翻譯可能需要微調，以確保整體表達的自然流畅。

以下逐步翻譯該文章為繁體中文：Viral VO3 Tree AI ads are created using JSON prompting, a new format that allows for creating impressive content.**爆紅的 VO3 Tree AI 廣告是透過 JSON 提示技術所製作的，這是一種允許創造令人印象深刻內容的新格式。**The video will show how to use this format and provide prompts to get started.**該影片將會展示如何使用這種格式，並提供提示以協助您入門。**

Okay, I understand. Please provide the English article about IKEA unboxing videos, and I will translate it into traditional Chinese, sentence by sentence, without omitting any sentences. I'm ready when you are!

受到IKEA開箱影片的啟發，這個方法並不限於IKEA，而且還可以應用於不同的品牌、風格，甚至是角色。 這部影片將會引導您自己製作這些東西，並提供提示與創意範例。

Okay, here's the translation of "JSON Prompting Explained" into traditional Chinese, translated sentence by sentence:**Original:** JSON Prompting Explained**Translation:** JSON提示說明 (JSON提示 explained)---I'll continue translating as you provide the article content. Please post the text you want translated sentence by sentence. I will then translate each sentence into traditional Chinese, focusing on accuracy and natural-sounding phrasing.

JSON提示是一種結構化你的影片內容的方式，並給予AI特定的格式。JSON提示是一種結構化你的影片內容的方式，並給予AI特定的格式。 影片展示了如何使用JSON提示來創建星巴克廣告、香水廣告、蘋果廣告和法拉利廣告的範例。影片展示了如何使用JSON提示來創建星巴克廣告、香水廣告、蘋果廣告和法拉利廣告的範例。 其中提到了一個客製化的"Chip Bolt"工具，用於產生JSON提示，可透過說明欄中的連結取得。其中提到了一個客製化的"Chip Bolt"工具，用於產生JSON提示，可透過說明欄中的連結取得。

好的，以下為該文章逐句翻譯為繁體中文：**原文:** Open Art Platform & Text to Video Generation**翻譯:** 開放藝術平台及文字轉影片生成

Open Art 平台用於訪問 Google V3，並透過文字提示生成影片，使用 VO3 Tree 模型，以 1080p 解析度在快速模式下執行。它提供對多個 AI 影片生成器的存取權，使管理多個訂閱變得更容易。以 labuba 房間轉換為例，使用了自定義提示生成一個 JSON FO3 提示，內容是一個湯姆貓和傑利鼠風格的盒子開啟房間轉換。

Okay, please provide the article you would like me to translate into traditional Chinese. I will translate it sentence by sentence, preserving all the content.

一個客製化的機器人可透過影片描述中的連結取得，用於生成 JSON 提示詞。使用者可以要求機器人創建提示詞，例如湯姆貓與傑利鼠風格的開箱房間改造，機器人將會以正確的格式生成提示詞。使用者在機器人生成提示詞後，可以依照自己的喜好調整提示詞。

好的，我將把 "Creative AI Examples" 這句話逐句翻譯成繁體中文。**原文：Creative AI Examples****翻譯：具創造力的人工智慧範例。**

以下提供逐句翻譯：Examples include a Pikachu-themed Pokeball bedroom and a Louis Vuitton luxury brand theme.例子包括一个皮卡丘主题的精灵球卧室，以及一个路易·威登奢侈品牌主题。--> 例子包括以皮卡丘為主題的寶可夢球臥室，以及路易威登精品品牌主題。It suggests using the format for professional advertisements and demonstrates generating prompts for Samsung or Apple product launches.它建议使用这种格式来制作专业的广告，并且展示了如何生成三星或苹果产品发布会的提示词。--> 它建議使用這種格式來製作專業的廣告，並且示範如何產生三星或蘋果產品發佈會的提示詞。A Ferrari advertisement is shown as another example.一个法拉利广告被展示作为另一个例子。--> 一個法拉利廣告被展示作為另一個範例。

Please provide the Starbucks commercial example you would like me to translate into traditional Chinese. I need the text of the commercial to perform the translation.

以下呈現一個由人工智慧生成的星巴克廣告作為範例，暗示它可能取代價值十萬美元的廣告。同時展示了一則香水廣告，鼓勵觀眾使用提供的提示來嘗試創作類似的廣告。提示和電子報訂閱連結皆可在說明欄中找到。

相關問題與答案

VO3 Tree AI ads are a specific type of advertising technology offered by VO3, likely leveraging artificial intelligence ("AI") to optimize ad delivery, targeting, and performance. Given the limited information available publicly about this specific product, here's a breakdown of what this likely entails, combining general knowledge of AI-powered advertising and the implication of the "Tree" aspect:* **AI-Powered Optimization:** The core idea is that AI algorithms are used to analyze vast amounts of data in real-time. This data could include user behavior, website content, and ad performance metrics. Based on this analysis, the AI automatically adjusts various aspects of the advertising campaign. This may include: * **Targeting:** Refining the audience to whom the ads are shown, identifying users who are most likely to be interested in the product or service being advertised. * **Bidding:** Automatically adjusting bids for ad placements to maximize return on investment (ROI). The AI seeks to win the most valuable ad auctions without overspending. * **Ad Creative:** Optimizing ad copy, images, and calls to action to improve click-through rates (CTR) and conversion rates. In some advanced cases, the AI might even dynamically generate different ad variations based on user profiles. * **Placement:** Determining the most effective websites, apps, or ad networks to display the ads.* **"Tree" Implication:** This is speculative, but the "Tree" element might refer to a hierarchical structure or decision-making process within the AI. Here are a few possibilities: * **Decision Tree Learning:** The AI might use decision tree algorithms, a common machine learning technique, to classify users or predict their behavior. This would involve building a tree-like structure where each node represents a decision based on a specific feature, leading to different outcomes (e.g., whether to show an ad to a user). * **Hierarchical Data Structure:** The "tree" might represent a way of organizing data about users or ad campaigns in a structured manner, enabling the AI to analyze relationships and patterns more effectively. * **Branching Campaign Strategies:** It could represent a system where different advertising strategies are pursued based on various inputs and outcomes, similar to branches on a tree.* **Key Benefits (likely):** The expected benefits of using VO3 Tree AI ads would likely include: * **Improved ROI:** By optimizing targeting, bidding, and ad creative, the AI aims to maximize the return on investment for advertising campaigns. * **Increased Efficiency:** Automating ad management tasks frees up human marketers to focus on strategy and creative development. * **Better Targeting:** AI can analyze data to identify and reach more relevant audiences than traditional methods. * **Real-Time Optimization:** The AI continuously learns and adapts to changing market conditions and user behavior. * **Personalized Ads:** In some cases, the AI might be able to personalize ads to individual users based on their preferences and interests.**In Summary:**VO3 Tree AI ads are likely an AI-driven advertising solution designed to automate and optimize various aspects of online advertising, potentially employing decision tree algorithms or a tree-structured data model. The primary goal is to improve ROI, increase efficiency, and deliver more effective and personalized ad experiences. Without more specifics from VO3, this remains an educated interpretation.

使用一種名為 JSON 提示的新提示格式所創建的 VO3 Tree AI 廣告正在網路上爆紅。

JSON prompting refers to a technique used in interacting with large language models (LLMs) where you structure your prompts and instruct the LLM to generate its responses in JSON (JavaScript Object Notation) format. In essence, you're telling the LLM, "I want your answer, and I want it to be organized as a piece of JSON."Here's a breakdown of why and how it's used:**Why JSON Prompting is Useful:*** **Structured Data:** JSON provides a clear and organized way to represent data with key-value pairs, nested objects, and arrays. This makes the LLM's output more predictable and easier to parse programmatically.* **Simplified Parsing:** Instead of relying on complex text processing to extract information from free-form text, you can directly parse the JSON output using readily available JSON libraries in virtually every programming language.* **Reliability:** By forcing the LLM to adhere to a specific structure, you reduce the likelihood of unexpected output formats or inconsistencies.* **Automation:** JSON output is ideal for feeding LLM-generated data directly into other systems, databases, or applications for automated workflows.* **Control Over Output:** You can define the specific fields and data types you need, ensuring that the LLM provides the necessary information in the desired format.**How to use JSON Prompting:**1. **Define the JSON Schema:** The most important step is to define the structure of the JSON you want the LLM to generate. Think about the keys and values you need, and their data types (string, number, boolean, array, object).2. **Construct the Prompt:** Your prompt should clearly instruct the LLM to generate JSON output that conforms to the defined schema. Be explicit about the desired format. Include the schema definition if necessary.3. **Example Prompt Components:** * **Instruction:** "Provide the following information in JSON format." "Respond with a JSON object containing..." "Generate a JSON representation of..." * **Schema/Description:** (Optionally) Include the JSON schema directly in the prompt or describe the structure and data types. For example: "The JSON object should have the following keys: `title` (string), `author` (string), `summary` (string)." * **Context/Question:** The actual task or information you want the LLM to process.**Example:**Let's say you want an LLM to summarize a news article and extract key entities.* **JSON Schema (Conceptual):** ```json { "summary": "string", "entities": [ { "name": "string", "type": "string" } ] } ```* **Prompt:** "Here is a news article: [Insert News Article Text Here]. Please provide a concise summary of the article and identify the key entities mentioned (people, organizations, locations). Respond with a JSON object containing two fields: `summary` (a string containing the summary) and `entities` (an array of JSON objects, where each object has a `name` string and a `type` string representing the entity and its type)."**Key Considerations:*** **Prompt Engineering:** Experiment with different prompt variations to find the most effective way to elicit the desired JSON output.* **Error Handling:** LLMs are not perfect. You should still include error handling in your code to gracefully handle instances where the LLM does not return valid JSON.* **Model Capabilities:** Some LLMs are better at JSON generation than others.* **Token Limits:** JSON output can be verbose. Be mindful of the token limit of the LLM you're using.* **Context Length:** LLMs have limited context windows. Long, complex JSON schemas can consume a significant portion of the context, leaving less room for the actual data.In summary, JSON prompting is a powerful technique to structure LLM outputs, making them more predictable, easier to parse, and suitable for integration into automated workflows. By carefully designing your prompts and providing clear instructions, you can significantly improve the reliability and usability of LLM-generated data.

JSON 提示是一種結構化您影片提示的方法，以便讓 Google V3 能夠正確地解讀它。

JSON prompting for AI video generation is a relatively advanced technique, and the best platform depends on your specific needs and technical expertise. However, here are a few recommended platforms, categorized by their strengths:**For Intermediate to Advanced Users with Coding Proficiency:*** **RunwayML (Runway Gen-2):** RunwayML is a popular platform for AI-powered creative tools. Gen-2 is their video generation model, and while it doesn't directly accept JSON as input *per se*, its API allows for granular control over the generation process by composing prompts and using prompt weights and image references. You would essentially use JSON structures to manage and organize these parameters before sending them to the API. This provides some of the benefits of structured prompting similar to JSON, even though it's used indirectly. Benefits include high-quality output, a powerful API, and continuous development. It requires more technical setup using their API.* **Replicate:** Replicate serves as a platform to deploy and use many open-source AI models, including various text-to-video and image-to-video models. You can often find models that accept more complex prompts or allow scripting through an API capable of generating JSON requests. Since Replicate hosts a variety of models, quality and features will vary based on which one is used. It's good for experimenting with different models, but requires managing different model interfaces.* **Custom Scripting with Open Source Models (e.g., using Python and libraries like `torch`, `transformers`):** This approach gives you the *most* control. You would choose a text-to-video model (e.g., potentially a future iteration of latent diffusion models adapted for video, or other research models), and then write a script to format your prompts as JSON dictionaries that configure the model's parameters (e.g., specifying scenes, camera angles, object types). This requires significant coding skills and understanding of the model's architecture. You'd be responsible for handling all aspects, from data loading to pre- and post-processing. Consider this if you need highly specific control and are comfortable working at a low level.**For Users Seeking a More User-Friendly, Though Potentially Less Flexible, Experience:*** **(Potentially Future Integrations in Existing AI Video Platforms):** Many established AI video generation platforms (e.g., Synthesia, Pictory, Descript with AI features) *don't currently* offer direct JSON prompting capabilities. However, as the field advances, it's likely they will incorporate more structured prompting methods, which may draw inspiration from JSON. Keep an eye on updates from these platforms. This would be the easiest route for non-programmers, but it's not currently available widely.**Why JSON Prompting is Valuable for AI Video:**JSON (JavaScript Object Notation) is useful because it allows you to create structured and well-defined prompts. This becomes increasingly important for sophisticated AI video generation where you might want to specify:* **Scene-by-scene descriptions:** Defining the visual content, camera angles, lighting, and ambiance for each scene.* **Character descriptions:** Detailing the appearance, clothing, and actions of characters in the video.* **Object attributes:** Specifying the properties of objects that appear in the video (e.g., color, shape, material).* **Camera movements:** Controlling panning, zooming, and other camera effects.* **Music and sound effects:** Defining the audio elements that accompany the video.* **Transitions:** Specifying how scenes should transition from one to another.By encoding all of this information in a JSON structure, you can exert finer-grained control over the AI video generation process, potentially leading to more consistent and predictable results.**Key Considerations When Choosing a Platform:*** **Technical Skill:** How comfortable are you with coding and working with APIs?* **Control vs. Ease of Use:** Do you need maximum control over every aspect of the generation process, or are you willing to sacrifice some control for a more user-friendly experience?* **Cost:** Platforms like RunwayML and Replicate charge based on usage. Developing a custom solution with open-source models requires your own computing resources (which may incur cloud costs).* **Model Availability:** Which models are supported or available on the platform? Does the platform allow you to integrate custom models?* **Community and Support:** Is there a strong community around the platform, and is good documentation available?In summary, if you have strong coding skills, start with RunwayML's API or explore Replicate or building your own solution using open-source models. If you're looking for an easier experience, keep an eye on updates from mainstream AI video generation platforms for potential future integrations of more structured prompting methods. JSON prompting is more of a technique used in conjunction with specific platforms rather than a feature inherently offered directly.

Open Art 和 Google Flow 是使用 JSON 提示詞和 AI 影片生成時建議的平台。 Open Art 提供多種不同的訂閱方案，讓使用者能輕鬆存取 AI 影片生成器。

To recommend the best type of video generation, I need more information about what you're trying to create. Please tell me about:* **What is the purpose of the video?** (e.g., marketing, tutorial, entertainment, internal training, explain a concept, personal project)* **What is the subject matter?** (e.g., abstract art, realistic landscape, animated characters, product demonstration, historical reenactment)* **What is your budget?** (e.g., free tools, affordable software, professional-grade services)* **What is your skill level?** (e.g., beginner, intermediate, experienced with video editing)* **How long should the video be?*** **What style are you aiming for?** (e.g., realistic, animated, stylized, documentary)* **Do you need original content, or can you use stock footage/assets?*** **Do you have any existing images, videos, or scripts available?*** **Are you looking for AI-generated videos, or human-created videos?**Once I have a better understanding of your needs and goals, I can provide more specific and helpful recommendations.For example, if you're making a simple explainer video with animation and a tight budget, I might suggest using AI-powered tools. If you're creating a high-quality cinematic video for a commercial, I might recommend hiring professional video production services.

Okay, please provide the article you would like me to translate into traditional Chinese. I will translate it sentence by sentence, making sure no content is omitted.

Finding premade JSON prompts can be tricky, as the specific prompt you need will depend heavily on your use case. However, here are several sources and strategies to help you locate them:**1. Online Prompt Engineering Marketplaces & Communities:*** **PromptBase:** (Promptbase.com) This is a popular marketplace specifically for buying and selling prompts, including those for JSON generation. Search for keywords like "JSON," "data extraction," "API calls," or the specific type of data you want (e.g., "recipe JSON," "product description JSON"). Check the prompt descriptions carefully to see if they produce well-structured JSON.* **AI Prompt Marketplace:** You can often find prompts for various tasks, including JSON generation, on platforms like Etsy or other smaller online marketplaces that cater to AI prompt engineers. Use similar keywords as above.* **Subreddits and Forums (Reddit, Stack Overflow, Quora):** * **r/LocalLLaMA:** Active community around local LLMs, often prompt engineering is discussed * **r/ChatGPTPro:** Discusses advanced prompting for various tasks * **r/learnpython, r/datascience:** Sometimes people will post prompts they've used for data processing or API interaction. * **Stack Overflow and Quora:** Search for questions related to JSON generation with specific technologies (e.g., "generate JSON using llama2 prompt" etc.). While users might not share entire prompts, you might find snippets or strategies.* **Hugging Face Hub:** (Huggingface.co) Hugging Face is a vast repository for models, datasets, and increasingly, prompt examples. Search for "JSON prompt" or related keywords. Pay close attention to the documentation and examples associated with specific language models.**2. Code Generation and AI Services Documentation:*** **OpenAI API Documentation (GPT-3, GPT-4):** The official OpenAI documentation often includes examples of formatting prompts for different tasks, including generating JSON for API calls or data manipulation. This is an excellent place to learn best practices.* **Anthropic (Claude) Documentation:** Similarly, review Anthropic's documentation for Claude models. Look for sections on structuring prompts for structured outputs.* **Google AI (Bard, Gemini) Documentation:** Google's AI offerings also have documentation with prompt examples.* **Dedicated JSON Schema Tools and Libraries:** Sometimes, tools for working with JSON Schema will provide examples of prompts for generating data that conforms to a specific schema (see point 5 below)**3. Example Projects and Tutorials:*** **GitHub:** Search GitHub for projects that use language models for data extraction or API interaction. Examine the code to see how prompts are constructed. Look for keywords like `"JSON"` combined with other terms relevant to your task.* **Medium, Towards Data Science, and other Online Publications:** Search these platforms for articles and tutorials on using language models for data extraction or other tasks related to JSON generation. Authors often share snippets of prompts in their articles.**4. Prompt Engineering Frameworks and Tools:*** **LangChain & LlamaIndex:** These are popular frameworks for building applications with LLMs. They often have functionalities for structuring prompts to generate formatted outputs like JSON. Their documentation and example notebooks can be helpful.* **Chainlit:** A tool for building conversational AI apps. Explore its features for creating interactive prompts and validating JSON responses.**5. Using JSON Schema:*** **JSON Schema:** (jsonschema.org) While not a premade *prompt*, using a JSON Schema to define the structure you need is incredibly helpful. Then, you can instruct the language model to generate JSON that conforms to that schema. This adds structure and validation to your prompt construction. Many tools and libraries can help you generate sample prompts based on a JSON Schema. Search for "JSON Schema to prompt generator".**6. Creating Prompts Yourself (Effective Prompting Techniques):**If you can't find a perfect premade prompt, you'll need to create one. Here's how to do it effectively for JSON generation:* **Be Explicit:** Clearly state that you want the output in JSON format.* **Provide a Clear Example:** A few-shot example of the desired JSON structure is extremely helpful. Show the LLM how the data should be organized.* **Specify the Keys and Values:** Clearly describe the meaning of each key in the JSON object. Explain the data types that are expected for each value (e.g., string, number, boolean, array).* **Use Delimiters:** Enclose the JSON output within delimiters (e.g., ```json ... ```) to help the language model distinguish it from surrounding text.* **Temperature:** Adjust the temperature setting of the language model (e.g., in OpenAI). A lower temperature (closer to 0) makes the output more deterministic and predictable, which is often desirable for JSON generation.* **Handle Errors:** Include instructions for the language model to handle cases where it cannot fulfill the request or data is missing. For example, it could return a specific error message or leave a field blank (null).* **Use a structured Prompt Template:** Consider a structured prompt template like:```You are a helpful assistant skilled at generating JSON.I want a JSON object containing information about [ENTITY].The JSON object should have the following keys:* `name`: (string) The name of the [ENTITY].* `description`: (string) A brief description of the [ENTITY].* `[KEY3]`: (string/number/boolean) Description of the [KEY3].* ... and so onHere is an example:```json{ "name": "Example Entity", "description": "This is an example.", "[KEY3]": "Example Value"}```Now, generate the JSON object for: [SPECIFIC REQUEST]```**Example Prompts (Illustrative):*** **Simple Example (Generating recipe ingredients):** ``` Generate a JSON object containing a list of ingredients for chocolate cake. The JSON should have a single key named "ingredients" which is an array of strings. Each string in the array should be a single ingredient. ```json { "ingredients": ["flour", "sugar", "cocoa powder", "eggs", "butter", "baking soda", "vanilla extract"] } ```* **More Complex Example (Extracting product data from text):** ``` Extract the product name, price, and description from the following text and return it as a JSON object: Text: "The Amazing Widget X1000 is on sale for just $29.99! This widget is perfect for all your widgeting needs and comes with a 3-year warranty." The JSON object should have the following keys: * `product_name`: (string) The name of the product. * `price`: (number) The price of the product. * `description`: (string) A brief description of the product. ```json { "product_name": "Amazing Widget X1000", "price": 29.99, "description": "This widget is perfect for all your widgeting needs and comes with a 3-year warranty." } ```By combining these resources and techniques, you'll be well-equipped to find or create the perfect JSON prompts for your needs. Remember to iterate and refine your prompts based on the results you get. Good luck!

自訂機器人／JSON提示的連結在說明欄中。

更多視頻推薦

分享至: