Alternative Framework Learning Methods
In addition to the official documentation, there are other ways to learn the framework, which will be discussed here in relation to the HLEB2 framework.
#Self-Study Without Documentation
Some developers learn how code works through trial and error. If you prefer this approach, this framework contains extensive code comments that will assist you. Check your IDE's capabilities for quick access to these comments.
The next section notes that the framework repository contains a text version of the documentation, so you can find the examples you need simply by searching through the project.
#LLM Assistance in Code Writing
HLEB2 is a relatively young framework, so there isn't yet sufficient publicly available information for training general-purpose neural networks.
However, if you want to learn the framework with the help of AI, you might find the unified text version of this guide in Markdown format useful. For example, the deepwiki service allows you to ask questions about the code based on this information.
Because all the framework's core code is located in a single repository, and a compact version of this documentation has been added to it, the deepwiki service easily generates responses based on the current version's code and produces decent results, though they should be verified, unlike examples from the official documentation.
For example, here's how this service responds to the following questions:
How to create a website page with routing, controller, template, and model?
How to send a 404 error to the user in a controller?
You don't need to specify the framework name, as this section of the service is specifically trained to work with this particular repository.
#Tips for Crafting LLM Prompts
To get the most relevant answer on the first try, it's recommended to specify in your question:
QUESTION - (a concise question here, pointing to a request for specific information, without vague wording).
ROLE - from what position the neural network will respond. For example, "as an expert on the HLEB2 framework".
FORMAT - for example, "3-5 practical examples with explanations in the style of official documentation".
SCOPE - for example, "400-600 words + code".
REQUIREMENTS - consider advantages; common mistakes; comparison of approaches (if there are several); mention XSS, CSRF, SQL-injection and others when necessary.
LEVEL - what audience the answer is intended for. For example: junior, middle or senior (one specific type).
EXCLUSIONS - a list of what you do NOT want to see in the answer.
IMPORTANCE - you can indicate whether this is for personal learning or for a public project of planetary scale capable of making this world a better place. There's an opinion that in the second case a more accurate answer will be given.
Neural network responses cannot be trusted 100%, and without your own knowledge of the framework it will be difficult to verify their answers. This documentation provides examples of its operation in a simple form, manually verified and the core principles of the framework, compiled directly by the author.
← Preface to using the documentation
