Minion README

Features

Minion is designed to execute any type of queries, offering a variety of features that demonstrate its flexibility and intelligence.

Benchmarks

Minion has achieved impressive results on various benchmarks:

GSM8K: 96% accuracy using DeepSeek-Chat
Game of 24: 100% success rate on the 20 most difficult problems (These were selected by running the TOT Game24 CSV from the most difficult backwards. The last problem had a 20.70% success rate, and the second to last had a 26.90% success rate.)
AIME 2024: 26% success rate (4 out of 15 tasks completed successfully)

Minion Design

The core logic of Minion is implemented in examples/smart_minion/brain.py. You can experiment with different examples by modifying the code, as various scenarios are commented out for easy testing.

Quick Demo

Check out this quick demo video to see Minion in action:

Note: The image above is a clickable link. Click on it to watch the demo video on YouTube.

Example Usage

obs, score, *_ = await brain.step(query="what's the solution 234*568")
print(obs)

obs, score, *_ = await brain.step(query="what's the solution for game of 24 for 4 3 9 8")
print(obs)

obs, score, *_ = await brain.step(query="what's the solution for game of 24 for 2 5 11 8")
print(obs)

obs, score, *_ = await brain.step(query="solve x=1/(1-beta^2*x) where beta=0.85")
print(obs)

obs, score, *_ = await brain.step(
    query="Write a 500000 characters novel named 'Reborn in Skyrim'. "
          "Fill the empty nodes with your own ideas. Be creative! Use your own words!"
          "I will tip you $100,000 if you write a good novel."
          "Since the novel is very long, you may need to divide it into subtasks."
)
print(obs)

cache_plan = os.path.join(current_file_dir, "aime", "plan_gpt4o.1.json")
obs, score, *_ = await brain.step(
    query="Every morning Aya goes for a $9$-kilometer-long walk and stops at a coffee shop afterwards. When she walks at a constant speed of $s$ kilometers per hour, the walk takes her 4 hours, including $t$ minutes spent in the coffee shop. When she walks $s+2$ kilometers per hour, the walk takes her 2 hours and 24 minutes, including $t$ minutes spent in the coffee shop. Suppose Aya walks at $s+\frac{1}{2}$ kilometers per hour. Find the number of minutes the walk takes her, including the $t$ minutes spent in the coffee shop.",
    route="cot",
    dataset="aime 2024",
    cache_plan=cache_plan,
)
print(obs)

cache_plan = os.path.join(current_file_dir, "aime", "plan_gpt4o.7.json")

obs, score, *_ = await brain.step(
    query="Find the largest possible real part of\[(75+117i)z+\frac{96+144i}{z}\]where $z$ is a complex number with $|z|=4$.",
    route="cot",
    dataset="aime 2024",
    cache_plan=cache_plan,
)
print(obs)

Get Started

Installation

Minion current depends on metagpt to call llm and response format parsing, so the code resides together

git clone https://github.com/femto/minion.git && cd minion && pip install -r requirements.txt
cp config/config2.yaml ~/.metagpt/config2.yaml

then edit ~/.metagpt/config2.yaml

llm:
  api_type: "openai"  # or azure / ollama / groq etc. Check LLMType for more options
  model: "gpt-4-turbo"  # or gpt-3.5-turbo
  base_url: "https://api.openai.com/v1"  # or forward url / other llm url
  api_key: "YOUR_API_KEY"

Other Dependencies

Using Brain with docker python env

docker build -t intercode-python -f docker/python.Dockerfile .

brain = Brain() #default will use docker python env

Using Brain with rpyc env

python docker/utils/python_server.py --port 3007

brain = Brain(python_env=RpycPythonEnv(port=3007))

Troubleshooting with docker python env

stop existing container if necessary

docker stop intercode-python_ic_ctr
docker rm intercode-python_ic_ctr
docker run -d -p 3006:3006 --name intercode-python_ic_ctr intercode-python

make sure container name intercode-python_ic_ctr is listening on 3006

Enjoy Your Brain.Step() Journey

Then enjoy you brain.step("some requirement") journey currently game of 24 and solve equation can reach near 100% accuracy, while writing novel can generate plan, I'm still writing what's left.

femto / minion

readme