mirror of
https://github.com/shareAI-lab/analysis_claude_code.git
synced 2026-05-13 19:56:43 +08:00
feat: build an AI agent from 0 to 1 -- 11 progressive sessions
- 11 sessions from basic agent loop to autonomous teams - Python MVP implementations for each session - Mental-model-first docs in en/zh/ja - Interactive web platform with step-through visualizations - Incremental architecture: each session adds one mechanism
This commit is contained in:
141
docs/zh/s02-tool-use.md
Normal file
141
docs/zh/s02-tool-use.md
Normal file
@@ -0,0 +1,141 @@
|
||||
# s02: Tools (工具)
|
||||
|
||||
> 一个分发映射表 (dispatch map) 将工具调用路由到处理函数 -- 循环本身完全不需要改动。
|
||||
|
||||
## 问题
|
||||
|
||||
只有 `bash` 时, 智能体所有操作都通过 shell: 读文件、写文件、编辑文件。这能用但很脆弱。`cat` 的输出会被不可预测地截断。`sed` 替换遇到特殊字符就会失败。模型浪费大量 token 构造 shell 管道, 而一个直接的函数调用会简单得多。
|
||||
|
||||
更重要的是, bash 是一个安全攻击面。每次 bash 调用都能做 shell 能做的一切。有了专用工具如 `read_file` 和 `write_file`, 你可以在工具层面强制路径沙箱化, 阻止危险模式, 而不是寄希望于模型自觉回避。
|
||||
|
||||
关键洞察: 添加工具不需要修改循环。s01 的循环保持不变。你只需在工具数组中添加条目, 编写处理函数, 然后通过 dispatch map 把它们关联起来。
|
||||
|
||||
## 解决方案
|
||||
|
||||
```
|
||||
+----------+ +-------+ +------------------+
|
||||
| User | ---> | LLM | ---> | Tool Dispatch |
|
||||
| prompt | | | | { |
|
||||
+----------+ +---+---+ | bash: run_bash |
|
||||
^ | read: run_read |
|
||||
| | write: run_wr |
|
||||
+----------+ edit: run_edit |
|
||||
tool_result| } |
|
||||
+------------------+
|
||||
|
||||
The dispatch map is a dict: {tool_name: handler_function}
|
||||
One lookup replaces any if/elif chain.
|
||||
```
|
||||
|
||||
## 工作原理
|
||||
|
||||
1. 为每个工具定义处理函数。每个函数接受与工具 input_schema 对应的关键字参数, 返回字符串结果。
|
||||
|
||||
```python
|
||||
def run_read(path: str, limit: int = None) -> str:
|
||||
text = safe_path(path).read_text()
|
||||
lines = text.splitlines()
|
||||
if limit and limit < len(lines):
|
||||
lines = lines[:limit]
|
||||
return "\n".join(lines)[:50000]
|
||||
```
|
||||
|
||||
2. 创建 dispatch map, 将工具名映射到处理函数。
|
||||
|
||||
```python
|
||||
TOOL_HANDLERS = {
|
||||
"bash": lambda **kw: run_bash(kw["command"]),
|
||||
"read_file": lambda **kw: run_read(kw["path"], kw.get("limit")),
|
||||
"write_file": lambda **kw: run_write(kw["path"], kw["content"]),
|
||||
"edit_file": lambda **kw: run_edit(kw["path"], kw["old_text"],
|
||||
kw["new_text"]),
|
||||
}
|
||||
```
|
||||
|
||||
3. 在 agent loop 中, 按名称查找处理函数, 而不是硬编码。
|
||||
|
||||
```python
|
||||
for block in response.content:
|
||||
if block.type == "tool_use":
|
||||
handler = TOOL_HANDLERS.get(block.name)
|
||||
output = handler(**block.input)
|
||||
results.append({
|
||||
"type": "tool_result",
|
||||
"tool_use_id": block.id,
|
||||
"content": output,
|
||||
})
|
||||
```
|
||||
|
||||
4. 路径沙箱化防止模型逃逸出工作区。
|
||||
|
||||
```python
|
||||
def safe_path(p: str) -> Path:
|
||||
path = (WORKDIR / p).resolve()
|
||||
if not path.is_relative_to(WORKDIR):
|
||||
raise ValueError(f"Path escapes workspace: {p}")
|
||||
return path
|
||||
```
|
||||
|
||||
## 核心代码
|
||||
|
||||
dispatch 模式 (来自 `agents/s02_tool_use.py`, 第 93-129 行):
|
||||
|
||||
```python
|
||||
TOOL_HANDLERS = {
|
||||
"bash": lambda **kw: run_bash(kw["command"]),
|
||||
"read_file": lambda **kw: run_read(kw["path"], kw.get("limit")),
|
||||
"write_file": lambda **kw: run_write(kw["path"], kw["content"]),
|
||||
"edit_file": lambda **kw: run_edit(kw["path"], kw["old_text"],
|
||||
kw["new_text"]),
|
||||
}
|
||||
|
||||
def agent_loop(messages: list):
|
||||
while True:
|
||||
response = client.messages.create(
|
||||
model=MODEL, system=SYSTEM, messages=messages,
|
||||
tools=TOOLS, max_tokens=8000,
|
||||
)
|
||||
messages.append({"role": "assistant", "content": response.content})
|
||||
if response.stop_reason != "tool_use":
|
||||
return
|
||||
results = []
|
||||
for block in response.content:
|
||||
if block.type == "tool_use":
|
||||
handler = TOOL_HANDLERS.get(block.name)
|
||||
output = handler(**block.input) if handler \
|
||||
else f"Unknown tool: {block.name}"
|
||||
results.append({
|
||||
"type": "tool_result",
|
||||
"tool_use_id": block.id,
|
||||
"content": output,
|
||||
})
|
||||
messages.append({"role": "user", "content": results})
|
||||
```
|
||||
|
||||
## 相对 s01 的变更
|
||||
|
||||
| 组件 | 之前 (s01) | 之后 (s02) |
|
||||
|----------------|--------------------|----------------------------|
|
||||
| Tools | 1 (仅 bash) | 4 (bash, read, write, edit)|
|
||||
| Dispatch | 硬编码 bash 调用 | `TOOL_HANDLERS` 字典 |
|
||||
| 路径安全 | 无 | `safe_path()` 沙箱 |
|
||||
| Agent loop | 不变 | 不变 |
|
||||
|
||||
## 设计原理
|
||||
|
||||
dispatch map 模式可以线性扩展 -- 添加工具只需添加一个处理函数和一个 schema 条目。循环永远不需要改动。这种关注点分离 (循环 vs 处理函数) 是智能体框架能支持数十个工具而不增加控制流复杂度的原因。该模式还支持对每个处理函数进行独立测试, 因为处理函数是与循环无耦合的纯函数。任何超出 dispatch map 的智能体都是设计问题, 而非扩展问题。
|
||||
|
||||
## 试一试
|
||||
|
||||
```sh
|
||||
cd learn-claude-code
|
||||
python agents/s02_tool_use.py
|
||||
```
|
||||
|
||||
可以尝试的提示:
|
||||
|
||||
1. `Read the file requirements.txt`
|
||||
2. `Create a file called greet.py with a greet(name) function`
|
||||
3. `Edit greet.py to add a docstring to the function`
|
||||
4. `Read greet.py to verify the edit worked`
|
||||
5. `Run the greet function with bash: python -c "from greet import greet; greet('World')"`
|
||||
Reference in New Issue
Block a user