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11 changes: 11 additions & 0 deletions Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,17 @@ PYTHON := $(VENV_DIR)/bin/python
PIP := $(VENV_DIR)/bin/pip

# Default target
.PHONY: help
help:
@echo "Available targets:"
@echo " all - Install dependencies and run tests"
@echo " venv - Create a virtual environment"
@echo " install - Install Python dependencies"
@echo " lint - Run Black code formatting"
@echo " test - Run tests"
@echo " docker-build - Build the Docker image"
@echo " docker-run - Run the Docker container with the example"

.PHONY: all
all: install test

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6 changes: 3 additions & 3 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ pip install -e .
### Quick Start

We use the OpenAI SDK, so you can use any LLM or provider that supports an OpenAI compatible API. Just set the `OPENAI_API_KEY` environment variable
and update the `api_base` in config.yaml if you are using a provider other than OpenAI. For local models, you can use
and update the `api_base` in config.yaml if you are using a provider other than OpenAI. For local models, you can use
an inference server like [optillm](https://github.com/codelion/optillm).

```python
Expand Down Expand Up @@ -133,7 +133,7 @@ cat checkpoints/checkpoint_*/best_program_info.json | grep -A 10 metrics
You can also install and execute via Docker:
```bash
docker build -t openevolve .
docker run --rm -v .:/app openevolve examples/function_minimization/initial_program.py examples/function_minimization/evaluator.py --config examples/function_minimization/config.yaml --iterations 1000
docker run --rm -v $(pwd):/app openevolve examples/function_minimization/initial_program.py examples/function_minimization/evaluator.py --config examples/function_minimization/config.yaml --iterations 1000
```

## Configuration
Expand Down Expand Up @@ -183,7 +183,7 @@ We have sucessfully replicated the results from the AlphaEvolve paper, below is

![alpha-evolve-replication](https://github.com/user-attachments/assets/00100f9e-2ac3-445b-9266-0398b7174193)

This is exactly the packing reported by AlphaEolve in their paper (Figure 14):
This is exactly the packing reported by AlphaEvolve in their paper (Figure 14):

![alpha-evolve-results](https://github.com/user-attachments/assets/0c9affa5-053d-404e-bb2d-11479ab248c9)

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