Evaluate LLMs in real time with Street Fighter III

Make LLM fight each other in real time in Street Fighter III.

Which LLM will be the best fighter ?

Our criterias 🔥

They need to be:

Fast: It is a real time game, fast decisions are key
Smart: A good fighter thinks 50 moves ahead
Out of the box thinking: Outsmart your opponent with unexpected moves
Adaptable: Learn from your mistakes and adapt your strategy
Resilient: Keep your RPS high for an entire game

Let the fight begin 🥷

1 VS 1: Mistral 7B vs Mistral 7B

slow-v1.mp4

1 VS 1 X 6 : Mistral 7B vs Mistral 7B

6v6-fast.mp4

A new kind of benchmark ?

Street Fighter III assesses the ability of LLMs to understand their environment and take actions based on a specific context. As opposed to RL models, which blindly take actions based on the reward function, LLMs are fully aware of the context and act accordingly.

Results

Our experimentations (314 fights so far) led to the following leader board. Each LLM has an ELO score based on its results

Ranking

ELO ranking

Model	Rating
🥇claude_3_haiku	1613
🥈claude_3_sonnet	1557
🥉claude_2	1554
claude_instant	1548
cohere_light	1527
cohere_command	1511
titan_express	1502
mistral_7b	1490

Win rate matrix

Explanation

Each player is controlled by an LLM. We send to the LLM a text description of the screen. The LLM decide on the next moves its character will make. The next moves depends on its previous moves, the moves of its opponents, its power and health bars.

Agent based
Multithreading
Real time

Prerequisites

Install Docker
Model Access in Amazon Bedrock fo us-east-1 and us-west-2. Details here

Installation

Follow instructions in https://docs.diambra.ai/#installation
Download the ROM and put it in ~/.diambra/roms
Install with pip3 install -r requirements
Create a .env file and fill it with the content like in the .env.example file
Start Docker Diambra container

docker run -d -v $HOME/.diambra/credentials:/tmp/.diambra/credentials   -v /Users/$USER/.diambra/roms:/opt/diambraArena/roms -p 50051:50051 docker.io/diambra/engine:latest

Run with make run

Demo mode

Run with make demo

Endless mode

Run with make go

Test mode

To disable the LLM calls, set DISABLE_LLM to True in the .env file. It will choose the action randomly.

Logging

Change the logging level in the script.py file.

How to make my own LLM model play? Can I improve the prompts?

The LLM is called in Robot.call_llm() method of the agent/robot.py file.

    def call_llm(
        self,
        temperature: float = 0.7,
        max_tokens: int = 50,
        top_p: float = 1.0,
    ) -> str:
        """
        Make an API call to the language model.

        Edit this method to change the behavior of the robot!
        """

        # Generate the prompts
        move_list = "- " + "\n - ".join([move for move in META_INSTRUCTIONS])
        system_prompt = f"""You are the best and most aggressive Street Fighter III 3rd strike player in the world.
Your character is {self.character}. Your goal is to beat the other opponent. You respond with a bullet point list of moves.
{self.context_prompt()}
The moves you can use are:
{move_list}
----
Reply with a bullet point list of moves. The format should be: `- <name of the move>` separated by a new line.
Example if the opponent is close:
- Move closer
- Medium Punch

Example if the opponent is far:
- Fireball
- Move closer"""

        prompt = "Your next moves are:"

        start_time = time.time()

        logger.debug(f"LLM call to {self.model}: {system_prompt}")
        logger.debug(f"LLM call to {self.model}: {time.time() - start_time}s")

        print(system_prompt + "\n" + prompt)
        if self.player_nb == "1":
            bedrock_runtime = bedrock_runtime_east
        else:
            bedrock_runtime = bedrock_runtime_west

        llm_response = call_bedrock_model(self.model, system_prompt, prompt, bedrock_runtime)
        print(f"{self.model} making move {llm_response}")
        return llm_response

To use another model or other prompts, make a call to another client in this function, change the system prompt, or make any fancy stuff.

Submit your model

Create a new class herited from Robot that has the changes you want to make and open a PR.

We'll do our best to add it to the ranking!

Credits

Made with ❤️ by the OpenGenerativeAI team from phospho (@oulianov @Pierre-LouisBJT @Platinn) and Quivr (@StanGirard) during Mistral Hackathon 2024 in San Francisco

BSharapov/llm-colosseum