LLM - Tool Use

// 调用栈
handleSendMessage
new Cline
this.startTask
this.initiateTaskLoop
this.recursivelyMakeClineRequests
this.attemptApiRequest
	- mcpHub connect
	// 指定工具调用格式 <read_file> <path>/xx.txt</path> </read_file>
	- SYSTEM_PROMPT
	- this.api.createMessage // send llm api
parseAssistantMessage // 解析 llm 输出 - 简单的语法解析
this.presentAssistantMessage
	- 检查工具使用 tool_use
		- write_to_file
		- replace_in_file
		- read_file: extractTextFromFile // nodejs fs.readFile
		- list_files
		- search_files
		- use_mcp_tool
		- execute_command
	- 回传消息给 llm

<task>
自行读取当前目录下的 rfc.md 文件，按照要求完成各项任务
</task>

<environment_details>

# VSCode Visible Files

lua/avante/suggestion.lua

# VSCode Open Tabs

lua/avante/suggestion.lua

# Current Time

3/5/2025, 11:08:18 PM (Asia/Shanghai, UTC+8:00)

# Current Working Directory (/home/avante.nvim) Files

${git ls-files}
</environment_details>

## read_file

Description: Request to read the contents of a file at the specified path. Use this when you need to examine the contents of an existing file you do not know the contents of, for example to analyze code, review text files, or extract information from configuration files. Automatically extracts raw text from PDF and DOCX files. May not be suitable for other types of binary files, as it returns the raw content as a string.
Parameters:

- path: (required) The path of the file to read (relative to the current working directory ${cwd.toPosix()})
  Usage:
  <read_file>
  <path>File path here</path>
  </read_file>

if (llm_stream_message.endsWith('<read_file>)) {
	currentToolUse = {
		type: "tool_use",
		name: 'read_file',
		params: {}
	}
}

if (type === 'tool_use') {
  switch (name) {
	case "read_file":
		// nodejs 读取文件
		await fs.readFile(params.path, "utf8")
		break
	case "write_to_file":
	case "replace_in_file":
	case "list_files":
	case "search_files":
	case "use_mcp_tool":
	case "execute_command":
  }
}

# Tools Use

## read_file
Parameters:
- path: (required) The path of the file to read (relative to the current working directory ${cwd.toPosix()})
Usage:
<read_file>
<path>File path here</path>
</read_file>

<task>
帮我读取当前目录下的 rfc.md 文件
</task>

import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-3-7-sonnet-20250219",
    max_tokens=1024,
    tools=[
        {
            "name": "get_weather",
            "description": "Get the current weather in a given location",
            "input_schema": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "The city and state, e.g. San Francisco, CA",
                    }
                },
                "required": ["location"],
            },
        }
    ],
    messages=[{"role": "user", "content": "What's the weather like in San Francisco?"}],
)
print(response)

{
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "<thinking>To answer this question, I will: 1. Use the get_weather tool to get the current weather in San Francisco. 2. Use the get_time tool to get the current time in the America/Los_Angeles timezone, which covers San Francisco, CA.</thinking>"
    },
    {
      "type": "tool_use",
      "id": "toolu_01A09q90qw90lq917835lq9",
      "name": "get_weather",
      "input": {"location": "San Francisco, CA"}
    }
  ]
}

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"

const server = new McpServer({ name: "weather", version: "1.0.0", });

// Register tools
server.tool(
  // 工具名称
  "read_file",
  // 工具说明
  "Get file content",
  // 工具参数
  {
    path: z.string().describe("file path"),
  },
  // 工具被调用时具体的处理逻辑
  async ({ path }) => {
    const content = await fs.readFile(path, "utf8");
    return {
      content: [
        {
          type: "text",
          text: alertsText,
        },
      ],
    };
  },
);

// 启动服务，localhost:12345
await server.connect()

{
  "mcpServers": {
    "filesystem": {
      "command": "node",
      "args": ["$MCP_PATH/fs/dist/index.js"]
    }
  }
}