docs: add legal issues doc

LLM_LEGAL.md

@@ -1,9 +1,26 @@
-# Legal issues on LLM in games
+# Information on legal issues of large language model (LLM) in games
 
-## 
+* [Government regulation](#government-regulation)
+* [Steam AI policy](#steam-ai-policy)
+* [Best practices](#best-practices)
+* [Articles](#articles)
+* [Communities](#communities)
 
-## Can you publish a game with LLM-generated content on Steam?
-Check this [Steam Article](https://store.steampowered.com/news/group/4145017/view/3862463747997849618). TLDR: you can, but you should report to Steam the measure you took to prevent  illegal contents, for both pre-generated text and live-generated text. This [reddit post] summarizes it as
+## Government regulation
+
+* [Large language models and copyright Wikipedia](https://en.wikipedia.org/wiki/Wikipedia:Large_language_models_and_copyright)
+    - Copyright law is slightly different in every country, AI generated contents may or may not be copyrightable
+    - AI generated contents can violate copyright law if it largely duplicates copyrighted materials
+* [European Artificial Intelligence Act](https://artificialintelligenceact.eu/) ([Wiki](https://en.wikipedia.org/wiki/Artificial_Intelligence_Act)):
+    - [High-level summary](https://artificialintelligenceact.eu/high-level-summary/): AI in game belongs to the `Minimal risk` category, it `is regulated...at least in 2021; this is changing with generative AI` (doesn't mean you can violate copyright though)
+    - Section 105 of the [Document](https://www.europarl.europa.eu/doceo/document/TA-9-2024-0138_EN.pdf): `Text and data mining techniques may be used extensively in this context for the retrieval and analysis of such content, which may be protected by copyright and related rights. Any use of copyright protected content requires the authorisation of the rightsholder concerned unless relevant copyright exceptions and limitations apply...Under these rules, rightsholders may choose to reserve their rights over their works or other subject matter to prevent text and data mining...`
+    - Exceptions in [Directive on Copyright in the Digital Single Market](https://eur-lex.europa.eu/eli/dir/2019/790/oj): `In the fields of research, innovation, education and preservation of cultural heritage...`
+* California [Generative AI Copyright Disclosure Act](https://en.wikipedia.org/wiki/Generative_AI_Copyright_Disclosure_Act)
+    - Status: introduced on April 9, 2024
+    - `The legislation requires the submission of a notice regarding the identity and the uniform resource locator (URL) address of the copyrighted works used in the training data to the Register of Copyrights at least 30 days before the public release of the new or updated version of the AI model`
+
+## Steam AI policy
+Check this [Steam Article](https://store.steampowered.com/news/group/4145017/view/3862463747997849618). TLDR: you can publish a game with AI generated contents on Steam, but you should report to Steam the measure you took to prevent  illegal contents, for both pre-generated text and live-generated text. This [reddit post](https://www.reddit.com/r/gamedev/comments/1adgxt3/is_the_use_of_openais_llm_allowed_by_steam/) summarizes it as
 ```
 you can have your game generate LMM content at runtime. There are two caveats:
 
@@ -15,4 +32,39 @@ you can have your game generate LMM content at runtime. There are two caveats:
 
     * (This implies you must write some sanity-checking code. A simple keyword blacklist on user input would probably suffice.)
 
-```
+```
+
+## Best practices
+
+* Even without all these legal issues, just relying on LLM-generated contents won't make your game stand out. Like many other video game technologies, LLM can be useful, but making a successful game is much more than being able to utilize a specific technology.
+* If you use pre-generated contents, double check your contents to make sure they are legal, e.g., search them on Google to see if it is too similar to other copyrighted materials
+* Live-generated contents are in general harder to control, but you can still pick an appropriate model, contrain the input prompt, or apply filters to generateds text to guard the generated contents
+
+### Selecting LLM models
+
+#### Fully open model
+
+Different LLM models have different degrees of openness. Many "open" LLM models are open in the sense that the trained models are permissively licensed, e.g., Phi-3 is under [MIT License](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/blob/main/LICENSE). The training data and the training data themselves remain closed. In contrast, models like [olmo](https://huggingface.co/allenai/OLMo-7B) and [MobileVLM](https://github.com/Meituan-AutoML/MobileVLM) open up their training data and code. Fully open model doesn't necessarily mean they are immune from copyright infringement, but it allows people to check whether there are copyrighted data being used that doesn't fall into the [fair use](https://en.wikipedia.org/wiki/Fair_use) case.
+
+#### Models that emphasize on being ethical
+
+If a company put sufficient efforts into filtering, cleaning, and synthesizing the data, and the model is carefully tested, one may trust the ethicality of the output from the model.
+
+* [Microsoft Responsible AI Standard](https://www.microsoft.com/en-us/ai/principles-and-approach/) and see "Safety-first model design" in [Introducing Phi-3: Redefining what’s possible with SLMs](https://azure.microsoft.com/en-us/blog/introducing-phi-3-redefining-whats-possible-with-slms/)
+* [Our responsible approach to Meta AI and Meta Llama 3](https://ai.meta.com/blog/meta-llama-3-meta-ai-responsibility/)
+
+
+#### Considering using a safeguard
+
+There are many ways to safeguard LLM-genrated contents, such as constraining the format and words filtering. Meta even published a [Llama Guard 2](https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-guard-2/) model to identify issues in user input and generated output, and yes it has a [GGUF version](https://huggingface.co/neopolita/meta-llama-guard-2-8b-gguf/tree/main) that can be used in inference.
+
+
+
+## Articles
+
+* [Large Language Models and Games: A Survey and Roadmap](https://arxiv.org/html/2402.18659v1)
+* [How ChatGPT and our language models are developed](https://help.openai.com/en/articles/7842364-how-chatgpt-and-our-language-models-are-developed) from OpenAI
+
+## Communities
+
+* [aiwars reddit](https://www.reddit.com/r/aiwars/): `Following news and developments on ALL sides of the AI art debate (and more)`

README.md

@@ -1,8 +1,7 @@
 # Godot LLM
-Isn't it cool to utilize large language model (LLM) to generate contents for your game? LLM has great potential in NPC models, game mechanics and design assisting. Thanks for technology like [llama.cpp](https://github.com/ggerganov/llama.cpp), "small" LLM, such as [llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B), run reasonably well locally on lower-end machine without a good GPU.
-I want to experiment LLM in Godot but I couldn't find any good library, so I decided to create one here.
+Isn't it cool to utilize large language model (LLM) to generate contents for your game? LLM has great potential in NPC models, game mechanics and design assisting. Thanks for technology like [llama.cpp](https://github.com/ggerganov/llama.cpp), "small" LLM, such as [llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B), run reasonably well locally on lower-end machine without a good GPU. I want to experiment LLM in Godot but I couldn't find any good library, so I decided to create one here.
 
-⚠ While LLM is less controversial than image generation models, there can be legal issues when LLM is integrated in games, I have created another [document](./LLM_LEGAL.md) to document some relevant information
+⚠ While LLM is less controversial than image generation models, there can still be legal issues when LLM contents are integrated in games, I have created another [page](./LLM_LEGAL.md) to document some relevant information
 
 # Table of Contents
 1. [Quick start](#quick-start)
@@ -13,7 +12,7 @@ I want to experiment LLM in Godot but I couldn't find any good library, so I dec
     - [Vector Database: LlmDB node](#vector-database-llmdb-node)
     - [Template/Demo](#templatedemo)
 2. [Retrieval Augmented Generation (RAG)](#retrieval-augmented-generation-rag)
-3. [Features](#features)
+3. [Roadmap](#roadmap)
 4. [Documentation](#documentation)
     - [Inspector Properties: GDLlama, GDEmbedding, and GDLlava](#inspector-properties-gdllama-gdembedding-and-gdllava)
     - [GDLlama Functions and Signals](#gdllama-functions-and-signals)
@@ -210,8 +209,9 @@ Question:
 
 ![](https://upload.wikimedia.org/wikipedia/commons/3/37/RAG_schema.svg)
 
-# Features
-## Already working
+# Roadmap
+
+## Features
 * Platform (backend): windows (cpu, vulkan), macOS(cpu, metal), Linux (cpu, vulkan), Android (cpu)
     - macOS support is on best effort basis since I don't have a mac myself
 * [llama.cpp](https://github.com/ggerganov/llama.cpp)-based features
@@ -227,6 +227,7 @@ Question:
 ## TODO
 * iOS: build should be trivial, but an apple developer ID is needed to run thhe build
 * Add in-editor documentation, waiting for proper support in Godot 4.3
+* Add utility functions to generate useful prompts, such as llama guard 2
 * Download models directly from huggingface
 * Automatically generate json schema from data classes in GDSCript
 * More [llama.cpp](https://github.com/ggerganov/llama.cpp) features