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Merge pull request #27 from codelion/fix/check-dup-initialprogram
Fix/check dup initialprogram
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.github/workflows/python-test.yml

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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -e ".[dev]"
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pip install -e .
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# Install test dependencies
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pip install pytest numpy
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- name: Run unit tests
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env:
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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run: |
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python -m unittest discover -s tests -p "*.py"
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python -m unittest discover -s tests -p "test_*.py" -v

README.md

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See the `examples/` directory for complete examples of using OpenEvolve on various problems:
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### Symbolic Regression
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A comprehensive example demonstrating OpenEvolve's application to symbolic regression tasks using the LLM-SRBench benchmark. This example shows how OpenEvolve can evolve simple mathematical expressions (like linear models) into complex symbolic formulas that accurately fit scientific datasets.
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[Explore the Symbolic Regression Example](examples/symbolic_regression/)
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Key features:
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- Automatic generation of initial programs from benchmark tasks
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- Evolution from simple linear models to complex mathematical expressions
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- Evaluation on physics, chemistry, biology, and material science datasets
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- Competitive results compared to state-of-the-art symbolic regression methods
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### Circle Packing
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Our implementation of the circle packing problem from the AlphaEvolve paper. For the n=26 case, where one needs to pack 26 circles in a unit square we also obtain SOTA results.

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