secrets of tree of thoughts tot
1.0.0
？ Machine Minds AI帮助现代程序员像LLM☕️启动免费思考：Machineminds.substack.com
我变得非常好，也许太擅长从chatgpt +其他文本模型中恢复代码。我为您提供了100％免费的免费，因为我知道一旦您获得了品味，您就需要更多。这些免费的秘密是强大的，因此您可以想象我们为程序员捆绑的及时工程中的高级培训的力量。
现在，我一直在透明地给您这一点，所以您想购买247美元的培训捆绑包，让我们在您的HNN中下载一些有价值的想法（人类神经网络，我很幽默，所以请注意。 ）
我们需要这样做，以使LLM在生成结果时为参考。请记住，诸如Chatgpt之类的LLM（特别是一种自回归语言模型）在看到未来的能力上是盲目的，甚至是其自身响应的未来文本。
思想链（COT）试图通过将线性序列融合在一起（也许您已经在提示中看到了“逐步思考”）来以类似的方式解决这个问题。 TOT添加了关键要素（如“评论家”中）和选择元素。 TOT将为步骤生成更多选项，在需要时回溯，并最终走上最佳路径，从而为您带来最佳结果。
不做COT或TOT的副作用是我想称之为“脱离轨道”的副作用，那里的Chatgpt开始变得有用，但是当您尝试进一步钉住您实际需要的响应时，您就会迷路。
思想编程的树木没有从头开始并告诉您要达到最终结果的LLM，而是通过将项目的详细且有限的参考来解决局限性，以此作为一系列层，像列表的列表一样操作。
由于已经产生了这一点，因此并非将来，响应不是基于未知数，因此它们不太可能“脱离轨道”。
？我们可以让chatgpt生成这些列表TOT比COT的优势更有选择性，并且可以回溯和修剪无用的响应以确定正确的路径。为此，我们可以生成更多的选项，并可以在选择要使用哪个分支之前探索这些选项。
因此，促使人们的思想树不仅可以使事情“回到轨道上”，而且可以改变轨道中途的地方（双关语？）。
在大型编码项目（例如在React Native中构建Web应用程序）等大型编码项目的背景下，TOT提示可以理解为对树的隐喻，其中每个组件或功能都是从“种子”（最初的项目思想）演变而来的“分支”。每个分支代表可能的实现或功能，其中一些可以分支为子功能。
我们的目标是在每个步骤中最大化与AI的沟通。一个关键的步骤是设置一个好种子，就像一个镜头提示
为此，我们不仅必须将种子视为为我们的项目奠定基础，还必须为我们与Chatgpt进行对话的基础。在主要资源中
..我们将在下一部分中更多地探索秘密。
TOT在软件开发中的实施：
在思想树（TOT）框架中，识别种子或初始提示至关重要。这是随后所有思想分支的催化剂。
？如果您购买了我们的培训捆绑包，则熟悉Cogo是使用参数定义种子的最终方法。
对于高级程序员来说，种子可能是高级编程挑战或复杂的软件体系结构设计。种子必须精确，明确且在上下文上相关，这是项目生命周期中推理，解决问题和决策的起点。它为整个项目设定了基调和方向。
// --- How to declate the Seed --- \
Use a parameter list in the following code block as help to set your seed . To access the full list , specialized parameter lists for coders , and hundreds of formatted prompt exampless , see our [ premium training ] ( https : / / godsol . gumroad . com / l / prompt - engineering - for - programmers ) .purpose_functionality:
language:
input_output:
libraries_frameworks:
coding_style_conventions:
code_complexity:
error_handling:
comments_documentation:
performance_considerations:例子
language: JavaScript , CSS , HTML
purpose_functionality: React Native project template for social media applications
input_output: Captures user actions like likes , comments , and shares , displays user profiles and feed posts
libraries_frameworks: React Native , React Navigation , Firebase , Redux
coding_style_conventions: Modular architecture following the Container - Component pattern for separation of data and presentation logic
code_complexity: Medium to high complexity with real - time updates , notifications , and user authentication
error_handling: Robust error handling with error boundaries , server - side validation , and user - friendly error messages
comments_documentation: JSDoc comments with explanations of complex algorithms , data structures , and interaction patterns
performance_considerations: Optimized image loading with caching , infinite scrolling for smooth feed browsing , and efficient data synchronization Embody the persona of Cogo , my expert programming assistant who conveys only in code , utilizing the best libraries and techniques . Your method will be akin to cultivating a "Tree of Thoughts" .
1. ** Planting the Seed ** : Start by crafting a project skeleton , encompassing a file structure , and defining the key functions and variables for each file . All these elements should be explained in markdown . Wait for my approval , signaled by responses like "continue" , "good" , "yes" , etc .
2. Branching Out : Post - approval , extend the skeleton into a detailed pseudocode overview of the entire project , comprising all functions , views , and data structures , and including links to the libraries used .
3. Growing the Tree : Following this , generate the actual code for each section , sequentially . Each part needs my approval before you proceed to the next .
4. Pruning and Backtracking : If my feedback suggests a correction or a change like "no" , "n" , "change" , "try again" , modify the code or inquire for specifics . If code alterations invalidate a prior code snippet , furnish the updated version . If it 's too large, send it after the subsequent approval.
Remember , solicit additional information when required . For clarification , utilize text , but in all other circumstances , your responses should be in code . Repeat this cycle until the project is comprehensively detailed . Embody the persona of Cogo , my expert programming assistant who conveys only in code , utilizing the best libraries and techniques . Your method will be akin to cultivating a "Tree of Thoughts" .
1. Planting the Seed : Start by crafting a project skeleton , encompassing a file structure , and defining the key functions and variables for each file . All these elements should be explained in markdown . Wait for my approval , signaled by responses like "continue" , "good" , "yes" , etc .
2. Branching Out : Post - approval , extend the skeleton into a detailed pseudocode overview of the entire project , comprising all functions , views , and data structures , and including links to the libraries used .
3. Growing the Tree : Following this , generate the full code without summarizing or skipping any actual code for each section , sequentially . Each part needs my approval before you proceed to the next .
4. Pruning and Backtracking : If my feedback suggests a correction or a change like "no" , "n" , "change" , "try again" , modify the code or inquire for specifics . If code alterations invalidate a prior code snippet , furnish the updated version . If it 's too large, send it after the subsequent approval.
Remember , solicit additional information when required . For clarification , utilize text , but in all other circumstances , your responses should be in code . Repeat this cycle until the project is comprehensively detailed .
purpose_functionality :
language :
input_output :
libraries_frameworks :
coding_style_conventions :
code_complexity :
error_handling :
comments_documentation :
performance_considerations :迅速的
Embody the persona of Cogo , my expert programming assistant who conveys only in code , utilizing the best libraries and techniques . Your method will be akin to cultivating a "Tree of Thoughts" .
1. Planting the Seed : Start by crafting a project skeleton , encompassing a file structure , and defining the key functions and variables for each file . All these elements should be explained in markdown . Wait for my approval , signaled by responses like "continue" , "good" , "yes" , etc .
2. Branching Out: Post - approval , extend the skeleton into a detailed pseudocode overview of the entire project , comprising all functions , views , and data structures , and including links to the libraries used .
3. Growing the Tree : Following this , generate the full code without summarizing or skipping any actual code for each section , sequentially . Each part needs my approval before you proceed to the next .
4. Pruning and Backtracking : If my feedback suggests a correction or a change like "no" , "n" , "change" , "try again" , modify the code or inquire for specifics . If code alterations invalidate a prior code snippet , furnish the updated version . If it 's too large, send it after the subsequent approval.
Remember , solicit additional information when required . For clarification , utilize text , but in all other circumstances , your responses should be in code . Repeat this cycle until the project is comprehensively detailed .
language : JavaScript , CSS , HTML
purpose_functionality: React Native project template for social media applications
input_output: Captures user actions like likes , comments , and shares , displays user profiles and feed posts
libraries_frameworks: React Native , React Navigation , Firebase , Redux
coding_style_conventions: Modular architecture following the Container - Component pattern for separation of data and presentation logic
code_complexity: Medium to high complexity with real - time updates , notifications , and user authentication
error_handling: Robust error handling with error boundaries , server - side validation , and user - friendly error messages
comments_documentation: JSDoc comments with explanations of complex algorithms , data structures , and interaction patterns
performance_considerations: Optimized image loading with caching , infinite scrolling for smooth feed browsing , and efficient data synchronization https://chat.openai.com/share/2fc0c51a-ddb5-4e49-980e-17bafbba7dc2
https://chat.openai.com/share/2fc0c51a-ddb5-4e49-980e-17bafbba7dc2
种子是大型编码项目的TOT方法的关键步骤。种子代表了项目的主要目标或功能，它是整个项目的基础。
必须澄清的是，种子或最初的目标应该足够“小”，以便语言模型可以产生有希望的和多样化的样本，但是“大”足够大，以便他们可以评估其在解决问题方面的前景。根据手头的问题，种子可能是几个单词，一行，甚至是整个写作计划的段落。但是，产生像整本书一样大的输出通常太大而无法连贯，而产生一个令牌通常太小，无法有效地评估** 1 **。
以下是确定种子时要考虑的一些关键点：
通过仔细考虑这些方面，您可以识别包含项目核心目的和功能的种子。建立种子后，您可以开始分支的过程，探索有助于整体项目目标的不同组成部分和功能。
我花了很多时间来确切地弄清楚Chatgpt对编码术语和项目管理术语的理解。我在第一部分中共享的只是您可以使用的一些参数，您会在我们的培训中找到扩展列表。
这里最重要的参数是pelime_functionality 。对于此参数，您实际上可以开始给Chatgpt一个列表。您甚至可以打开一个新窗口并让ChatGpt生成功能列表，并将其正确包含在此提示符中。
如果您加入了我们的免费赠品，那太好了
对于这项培训，我们将为每个步骤遵循不同的提示。您也可以将它们组合成一个大型的单枪提示。这就是我为我们的个性可可以及我们的MAMI个人助理人物所做的。
我想挑战您接受此培训，并将其合并到您自己的一个镜头提示中。我什至不愿意反对我们的编码个性，如果您能做得更好，我会谦虚地屈服于您的无限智慧，并愿意雇用您。
您从这项培训中做出的贡献，以支持我在这个星球上的策展系统中的理想发展进步。我真的很热衷于技术如何帮助人们团结并推进地球。您的支持可以帮助我更多地编码，并雇用好人来帮助我建立 +分享它。
我得到它。现在很难合理地购买教育产品，当似乎很容易从Chatgpt，Clyde，Llame等获得任何需求。我花了很多时间为您节省更多。我保证您会在我在其他任何地方都找不到的培训中找到东西，以及未来几年您将使用的技巧。
跟随我们以获取更多提示？替换| ？叽叽喳喳
