AI-Scientist颠覆传统科研模式：AI Scientist如何利用迭代实验和自动化系统，开创学术研究新纪元

conda create -n ai_scientist1 python=3.11
conda activate ai_scientist1

# LLM APIs
pip install anthropic aider-chat backoff openai
# Viz
pip install matplotlib pypdf pymupdf4llm
# Install pdflatex
sudo apt-get install texlive-full

# Common Requirements
pip install torch numpy transformers datasets tiktoken wandb tqdm

export OPENAI_API_KEY="sk-proj-"


git clone https://github.com/SakanaAI/AI-Scientist.git


# 准备NanoGPT数据
python data/enwik8/prepare.py
python data/shakespeare_char/prepare.py
python data/text8/prepare.py


# 创建NanoGPT基线运行 训练NanoGPT模型建立一个基准
cd templates/nanoGPT
python experiment.py --out_dir run_0
python plot.py
cd ../..

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使用claude接口

export ANTHROPIC_API_KEY="sk-proj-"

python launch_scientist.py --model "claude-3-5-sonnet-20240620" --experiment nanoGPT --num-ideas 5

# --num-ideas 5表示生成5个研究想法

使用openai接口

export OPENAI_API_KEY="sk-proj-"

python launch_scientist.py --model "gpt-4o-2024-05-13" --experiment nanoGPT --num-ideas 5

获取论文审查

#export OPENAI_API_KEY="sk-proj-"

import openai
from ai_scientist.perform_review import load_paper, get_llm_review

client = openai.OpenAI()
model = "gpt-4o-2024-05-13"

paper_txt = load_paper("path_to_your_generated_paper.pdf")
review = get_llm_review(
    paper_txt,
    model,
    client,
    num_reflections=5,
    num_fs_examples=1,
    num_reviews_ensemble=5,
    temperature=0.1,
)

print(review["Overall"])  # 总体评分
print(review["Decision"])  # 接受或拒绝
print(review["Weaknesses"])  # 弱点列表

运行批量分析

cd review_iclr_bench
python iclr_analysis.py --num_reviews 500  --batch_size 100 --num_fs_examples 1 --num_reflections 5 --temperature 0.1 --num_reviews_ensemble 5

2D扩散

cd templates/2d_diffusion && python experiment.py --out_dir run_0 && python plot.py

Grokking

cd templates/grokking && python experiment.py --out_dir run_0 && python plot.py