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Hey guys,

 

Has anyone of you tried feeding metin2 game/server source to some kind of LLM yet?

I think best use case would be finding exploits / memory leaks.

Gemini 1.5 Pro seems especially interesting because it has a large amount of tokens.

 

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I had tried something similar before through custom GPT via ChatGPT, but instead of searching for bugs/exploits, I attempted to create a simple ping/pong system by providing all the details just to see what it could do for experimental purposes. However, speaking for ChatGPT, it doesn't automatically scan the entire content due to the large number of files. It only makes heuristic-based guesses based on the names or scans the files if specified. Even if it processes the entire content correctly, the whole processing takes a long time, so it starts skipping parts after a while until the main command is given. Additionally, even if you manage to achieve the desired result once, due to temperature imbalances, getting completely unrelated results in subsequent attempts is possible. Therefore, in summary, obtaining efficient results is not quite achievable. It's quite useful for conducting research on specific topics in specific parts rather than scanning the entire content. However, for now fully automating it is not very feasible, at least for ChatGPT.

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2 hours ago, Koray said:

I had tried something similar before through custom GPT via ChatGPT, but instead of searching for bugs/exploits, I attempted to create a simple ping/pong system by providing all the details just to see what it could do for experimental purposes. However, speaking for ChatGPT, it doesn't automatically scan the entire content due to the large number of files. It only makes heuristic-based guesses based on the names or scans the files if specified. Even if it processes the entire content correctly, the whole processing takes a long time, so it starts skipping parts after a while until the main command is given. Additionally, even if you manage to achieve the desired result once, due to temperature imbalances, getting completely unrelated results in subsequent attempts is possible. Therefore, in summary, obtaining efficient results is not quite achievable. It's quite useful for conducting research on specific topics in specific parts rather than scanning the entire content. However, for now fully automating it is not very feasible, at least for ChatGPT.

ChatGPT is obsolete today honestly. I use claude-3-opus LLM daily for commercial programming and it exceeds chatgpt by a mile.
When it comes to token size it's like you said, not possible straight away with chatgpt. There's however a way to go around this with some additional layers of complexity like Cursor Editor although be warned its closed source. It's basically a fork of vscode that let's you ask LLMs about your code. Also you can ask it to write anything and it has the context of your entire codebase.

I tested it a few months back and it wasn't bad honestly. I told it to explain some shit-code written by ymir that I didn't understand and it did quite well.

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You don't need to train it on your source code. You just need to take a good model and give it more context. For example I use Github Copilot to help me with some trivial task while coding. If I need info about the whole source I just use @workspace in the chat when I ask it a question and then he has more context about the source. 

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There's no LLM atm that can "remember" as many tokens as a full game source requires, even gemini, it will only mean it has a long input stream, not that it remembers much of it, so we'll still have to wait

Anyhow llms are definitelly good, for me gpts was the best at cpp for example

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Well, well, well 2 years later and claude code (opus 4.6) is doing magic 🙂 1M tokens of context and its able to do things like rewriting the entire networking stack of my pserver, or inventing new packers to replace old eterpack as well as fix literally any bug. Interesting times we're living in...

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On 3/30/2026 at 1:18 PM, Metin2Forum said:

AI is shit

After like 10 minutes of self training it produces like 99% more quality code that any other "DEV"s around here.

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🖥️ SysAdmin — Government (HU)
🛠️ Freelance Metin2 Dev • DevOps
🐧 FreeBSD / Linux | 🛡️ Security & WAF | 🚀 Performance | 🔥 Firewalls | ⚙ Automation
Open to work - Contact me on Discord @matteo_r

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Firstly, Claude tends to perform better on tasks like this. It’s not just about token limits; it has stronger reasoning capabilities when dealing with complex code.

Secondly, giving an LLM the entire Metin2 source code, similar to providing the full codebase of GTA or Linux, is not particularly useful. It can also introduce noise rather than meaningfully enriching the context. There is already a raw Metin2 source that has been carefully optimized and secured. The core itself is usually not the issue; bugs and problems arise from added or integrated systems.

Therefore, it is more effective to select and provide only the files related to a specific system or feature rather than sharing the entire source. Claude is already trained on C++ logic and can handle its complexity. You can then use it for targeted tasks. However, even Claude often produces non-optimized code, so you still need solid expertise to properly evaluate and adapt the solution, even if it appears to be working and functional.

Edited by yassineland

 

 

Dr. Mohamed Yassine Landolsi

// Assistant Professor · Computer Science

My Scientific Research


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big experience

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