AI 编程提效从专业角度：把大模型嵌入研发流水线

import os, json, subprocess
from openai import OpenAI

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def get_diff(base="main"):
    return subprocess.check_output(
        ["git", "diff", f"{base}...HEAD"], text=True
    )

def review_code(diff):
    prompt = f"""你是资深工程师，请审查以下 git diff。
要求：
1. 只指出 bug、安全、性能、可维护性问题；
2. 按严重程度排序；
3. 输出 JSON 对象，字段：issues，数组元素含 file、line、severity、issue、suggestion。
diff:
{diff}
"""
    resp = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.2,
        response_format={"type": "json_object"}
    )
    return json.loads(resp.choices[0].message.content)

if __name__ == "__main__":
    diff = get_diff()
    if diff.strip():
        result = review_code(diff[:12000])  # 截断，避免超 token
        print(json.dumps(result, ensure_ascii=False, indent=2))

def build_test_prompt(func_code):
    return f"""为以下 Python 函数生成 pytest 单元测试。
要求：
- 覆盖正常、边界、异常；
- 使用 pytest.raises 处理异常；
- 不要过度 mock。
函数：
{func_code}
"""

# 调用大模型后，把结果保存为 test_generated.py
# 然后执行：
# pytest -q test_generated.py
# coverage run -m pytest && coverage report

name: ai-review
on: [pull_request]
jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0
      - uses: actions/setup-python@v5
        with:
          python-version: '3.12'
      - run: pip install openai pytest
      - run: pytest -q
      - run: python review.py
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}