《AI Agent 高级编程》4.2 smolagents：CodeAgent「代码即行动」重写子任务

import importlib.metadata as m
print(m.version("smolagents"))

1.26.0

import inspect
from smolagents import CodeAgent, ToolCallingAgent, tool
print(inspect.signature(CodeAgent.__init__))
print(inspect.signature(ToolCallingAgent.__init__))
print(inspect.signature(tool))

(self, tools: list[smolagents.tools.Tool], model: smolagents.models.Model, prompt_templates: smolagents.agents.PromptTemplates | None = None, additional_authorized_imports: list[str] | None = None, planning_interval: int | None = None, executor: smolagents.local_python_executor.PythonExecutor = None, executor_type: Literal['local', 'blaxel', 'e2b', 'modal', 'docker'] = 'local', executor_kwargs: dict[str, Any] | None = None, max_print_outputs_length: int | None = None, stream_outputs: bool = False, use_structured_outputs_internally: bool = False, code_block_tags: str | tuple[str, str] | None = None, **kwargs)
(self, tools: list[smolagents.Tool], model: smolagents.models.Model, prompt_templates: smolagents.agents.PromptTemplates | None = None, planning_interval: int | None = None, stream_outputs: bool = False, max_tool_threads: int | None = None, **kwargs)
(tool_function: 'Callable') -> 'Tool'

import inspect, smolagents.models as M
print(inspect.signature(M.Model.generate))
print("abstract:", sorted(M.Model.__abstractmethods__))

(self, messages: list[smolagents.models.ChatMessage], stop_sequences: list[str] | None = None, response_format: dict[str, str] | None = None, tools_to_call_from: list[smolagents.tools.Tool] | None = None, **kwargs) -> smolagents.models.ChatMessage
abstract: []

from smolagents.models import Model, ChatMessage
from smolagents import CodeAgent, tool


class ScriptedModel(Model):
    """本地假模型：按脚本逐步吐出 <code> 块，零网络、零凭据。"""

    def __init__(self, script):
        super().__init__(model_id="scripted-local")
        self.script = list(script)
        self.calls = []          # (当时的消息条数, 可见工具名)
        self.n = 0

    def generate(self, messages, stop_sequences=None, response_format=None,
                 tools_to_call_from=None, **kwargs):
        self.calls.append((len(messages), [t.name for t in (tools_to_call_from or [])]))
        code = self.script[min(self.n, len(self.script) - 1)]
        self.n += 1
        return ChatMessage(
            role="assistant",
            content=f"Thought: 第 {self.n} 步\n<code>\n{code}\n</code>",
        )


@tool
def search(query: str) -> str:
    """检索本地知识库。
    Args:
        query: 查询词。
    """
    return f"[hit] {query} => 本地知识库命中 3 条"


model = ScriptedModel([
    'res = search("smolagents")\nprint(res)',
    'final_answer("结论：CodeAgent 把工具调用写成了 Python 代码。")',
])
agent = CodeAgent(tools=[search], model=model, max_steps=5)
out = agent.run("用 search 查 smolagents，再给出结论")

print("=== RESULT ===")
print(out)
print("=== model.calls（消息条数, 可见工具名）===")
for c in model.calls:
    print("  ", c)

╭────────────────────────────────── New run ───────────────────────────────────╮
│ 用 search 查 smolagents，再给出结论                                          │
╰─ ScriptedModel - scripted-local ─────────────────────────────────────────────╯
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 1 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  res = search("smolagents")
  print(res)
 ──────────────────────────────────────────────────────────────────────────────
Execution logs:
[hit] smolagents => 本地知识库命中 3 条

Out: None
[Step 1: Duration 0.02 seconds]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Step 2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 ─ Executing parsed code: ─────────────────────────────────────────────────────
  final_answer("结论：CodeAgent 把工具调用写成了 Python 代码。")
 ──────────────────────────────────────────────────────────────────────────────
Final answer: 结论：CodeAgent 把工具调用写成了 Python 代码。
[Step 2: Duration 0.00 seconds]
=== RESULT ===
结论：CodeAgent 把工具调用写成了 Python 代码。
=== model.calls（消息条数, 可见工具名）===
   (2, [])
   (5, [])

ToolCallingAgent 的 model.calls：
   (2, ['search', 'final_answer'])
   (5, ['search', 'final_answer'])

import smolagents.local_python_executor as E
print("DANGEROUS_MODULES", sorted(E.DANGEROUS_MODULES))
print("DANGEROUS_FUNCTIONS", sorted(E.DANGEROUS_FUNCTIONS))
print("MAX_OPERATIONS", E.MAX_OPERATIONS, "MAX_EXECUTION_TIME_SECONDS", E.MAX_EXECUTION_TIME_SECONDS)
print("BASE_BUILTIN_MODULES", sorted(E.BASE_BUILTIN_MODULES))

DANGEROUS_MODULES ['builtins', 'io', 'multiprocessing', 'os', 'pathlib', 'pty', 'shutil', 'socket', 'subprocess', 'sys']
DANGEROUS_FUNCTIONS ['builtins.__import__', 'builtins.compile', 'builtins.eval', 'builtins.exec', 'builtins.globals', 'builtins.locals', 'os.popen', 'os.system', 'posix.system']
MAX_OPERATIONS 10000000 MAX_EXECUTION_TIME_SECONDS 30
BASE_BUILTIN_MODULES ['collections', 'datetime', 'itertools', 'math', 'queue', 'random', 're', 'stat', 'statistics', 'time', 'unicodedata']

model = ScriptedModel([
    'hits = [search(q) for q in ["smolagents", "CodeAgent", "tool calling"]]\n'
    'merged = " | ".join(hits)\nprint(merged)',
    'final_answer("汇总：" + merged)',
])
agent = CodeAgent(tools=[search], model=model, max_steps=5)
print(agent.run("检索三个关键词并汇总"))