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| import { execSync } from 'child_process';
import readline from 'readline';
// const MODEL = "minimax/minimax-m2.1";
const MODEL = 'deepseek/deepseek-v3.2-251201';
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout
});
const tools = [
{
"type": "function",
"function": {
name: "get_cameras",
description: "获取所有在线的网络摄像头",
}
},{
"type": "function",
"function": {
name: "check_camera",
description: "检查输入的指定摄像头的状态",
parameters: {
type: "object",
properties: {
url: { type: "string", description: "指定摄像头的RTSP地址" }
},
required: ["url"]
}
}
}
];
let messages = [
{ role: 'system', content: '你是 AI Agent，分析用户意图并决定要调用哪个工具。' }
];
async function runTool(action, params) {
if (action === "get_cameras") {
// 模拟 API
const cameras = [
{id:1, name:'门口', url:'rtsp://172.21.132.230/url1'},
{id:2, name:'办公室', url:'rtsp://172.21.132.230:554/rtp/32020000002000000003_32020000001320000020?originTypeStr=rtp_push'},
{id:3, name:'广场', url:'rtsp://172.21.132.230/url3'},
];
let resp = '';
cameras.forEach(cam => {
resp += `摄像头名称：${cam.name}，编号id:${cam.id}，RTSP播放地址:${cam.url}\r\n`;
})
return resp;
}else if (action === "check_camera") {
const url = params.url;
console.log(`执行命令：ffplay -loglevel debug '${url}'，3秒钟，并检查输出内容判断是否正常。`);
try {
const output = execSync(
`ffplay -t 3 -loglevel debug -i '${url}'`,
{
stdio: ['ignore', 'pipe', 'pipe'], // 捕获 stdout + stderr
encoding: 'utf8',
timeout: 3000 // 3 秒超时
}
);
console.log('ffplay output:\n', output);
return "ffplay执行输出：" + output;
} catch (err) {
// ffplay 被 Ctrl+C / SIGINT / 超时杀掉时也会走这里
console.error('ffplay exited');
return "ffplay命令执行失败："+err.stdout?.toString()+err.stderr?.toString();
}
}
return "未知工具";
}
async function sendMessage() {
while (true) {
const userInput = await new Promise(resolve => rl.question('用户输入: ', resolve));
if (userInput.toLowerCase() === 'exit') break;
messages.push({ role: 'user', content: userInput });
let done = false;
while (!done) {
console.log("ai 请求发送。。\r\n")
const response = await fetch('https://api.qnaigc.com/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: 'Bearer ' + process.env.OPENAI_API_KEY,
'Content-Type': 'application/json'
},
body: JSON.stringify({
stream: false,
model: MODEL,
messages: messages,
tools: tools,
tool_choice: 'auto'
})
});
const data = await response.json();
if(data.error){
console.error('Error:', data.error);
break;
}
console.log("token usage:%d", data.usage?.total_tokens);
const message = data.choices[0].message;
let aiReply;
if (message.tool_calls) {
let toolCall = message.tool_calls[0];
console.log(toolCall, message.content);
// 模型选择了工具
const action = toolCall.function.name;
const params = JSON.parse(toolCall.function.arguments);
// 这里可以调用对应工具
aiReply = await runTool(action, params);
messages.push({"role": "tool", "tool_call_id": toolCall.id, "content": aiReply})
}else if (message.content) {
// 普通文本
aiReply = message.content;
console.log('AI:', aiReply);
}
messages.push({"role": "assistant", "content": aiReply})
// 检查工具调用
const toolCalls = message.tool_calls || [];
if (toolCalls.length === 0) {
// console.log("\r\n -----DEBUG------");
// messages.forEach((item, i) => {
// console.log(`message ${i}:`, item);
// });
// console.log("\r\n -----DEBUG end------");
console.log("agent结束，等待下一个指令")
done = true;
break;
}else{
console.log("\r\n------\r\nagent下一步。。。\r\n")
messages.push({ role: 'user', content: "下一步。" });
}
}
}
rl.close();
}
sendMessage();
|