Minion is designed to execute any type of queries, offering a variety of features that demonstrate its flexibility and intelligence.
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)
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.
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.
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)git clone https://github.com/femto/minion.git && cd minion && pip install -r requirements.txt
cp config/config.yaml.example config/config.yaml
cp config/.env.example config/.env
then edit config/config.yaml
models:
"default":
api_type: "openai"
base_url: "${DEFAULT_BASE_URL}"
api_key: "${DEFAULT_API_KEY}"
model: "deepseek-chat"
temperature: 0
then config/.env
DEFAULT_API_KEY=sk-xxx
DEFAULT_BASE_URL=base_url
DEFAULT_MODEL=deepseek-chat
docker build -t intercode-python -f docker/python.Dockerfile .
brain = Brain() #default will use docker python env
python docker/utils/python_server.py --port 3007
brain = Brain(python_env=RpycPythonEnv(port=3007))
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
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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.