从单 Agent 到 Coding Agent,它多了什么

import json
import os
import subprocess
import sys
from pathlib import Path
from openai import OpenAI

# 先完成第2篇的SDK和环境变量准备；仅使用专门的练习目录。
client = OpenAI(base_url=os.environ["LLM_BASE_URL"], api_key=os.environ["LLM_API_KEY"], timeout=30.0, max_retries=1)
MODEL = os.environ["LLM_MODEL"]
WORKSPACE = Path("coding-lab").resolve()
WORKSPACE.mkdir(exist_ok=True)

def checked_path(path):
    target = (WORKSPACE / path).resolve()
    if not target.is_relative_to(WORKSPACE):
        raise ValueError("只能访问练习目录")
    return target

def read_file(path):
    target = checked_path(path)
    if target.stat().st_size > 1_000_000:
        raise ValueError("文件过大，请先缩小范围")
    return target.read_text(encoding="utf-8")

def write_file(path, content):
    target = checked_path(path)
    if len(content.encode("utf-8")) > 1_000_000:
        raise ValueError("写入内容过大")
    target.parent.mkdir(parents=True, exist_ok=True)
    target.write_text(content, encoding="utf-8")
    return "ok"

def run(cmd):
    allowed = {"pytest": [sys.executable, "-m", "pytest", "-q"]}
    if cmd not in allowed:
        raise ValueError("只允许预先登记的pytest命令")
    result = subprocess.run(allowed[cmd], cwd=WORKSPACE, timeout=30, shell=False,
                            capture_output=True, text=True,
                            env={"PATH": os.environ.get("PATH", ""), "PYTHONIOENCODING": "utf-8"})
    return json.dumps({"returncode": result.returncode, "stdout": result.stdout[-2000:],
                       "stderr": result.stderr[-2000:]}, ensure_ascii=False)

TOOLS = {"read_file": read_file, "write_file": write_file, "run": run}

def tool_schema(name, description, names):
    return {"type": "function", "function": {"name": name, "description": description,
            "parameters": {"type": "object", "properties": {key: {"type": "string"} for key in names},
                           "required": names, "additionalProperties": False}}}

tools_schema = [
    tool_schema("read_file", "读取练习目录内的UTF-8文件", ["path"]),
    tool_schema("write_file", "写入练习目录内的UTF-8文件", ["path", "content"]),
    tool_schema("run", "运行登记的pytest命令，cmd只能是pytest", ["cmd"]),
]

def coding_agent(task, max_steps=15):
    messages = [
        {"role": "system", "content": "你是工程师。读代码→改代码→跑测试验证,通过了再结束。"},
        {"role": "user", "content": task},
    ]
    for _ in range(max_steps):                 # ← 一定要有步数上限
        msg = client.chat.completions.create(model=MODEL, messages=messages, tools=tools_schema).choices[0].message
        messages.append(msg.model_dump(exclude_none=True))
        if not msg.tool_calls:
            return msg.content                 # 模型说做完了
        for call in msg.tool_calls:
            try:
                args = json.loads(call.function.arguments)
                result = TOOLS[call.function.name](**args)   # 读/写/跑
            except Exception as e:
                result = f"工具出错: {e}"        # 错误也喂回去,让它自己修
            messages.append({"role": "tool", "tool_call_id": call.id, "content": str(result)[:4000]})
    return "达到步数上限"

# 在coding-lab中准备utils.py和对应测试，并安装pytest，再运行：
# print(coding_agent("修复 utils.py 里 add() 的 bug,并运行登记的pytest命令"))