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熊潇 2025-06-21 16:31:00 +08:00
parent a150cbc533
commit ce7cd03cb3
18 changed files with 387 additions and 29 deletions
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2
.gitignore vendored
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@ -15,3 +15,5 @@ logs
.env*
!.env.example
.turbo

7
package.json
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@ -18,6 +18,7 @@
"build": "rimraf dist && bun run bun.config.mjs",
"test": "tsx test/**/*.ts",
"clean": "rm -rf dist",
"turbo:build": "turbo run build",
"pub": "npm run build && envision pack -p -u",
"cmd": "tsx cmd/index.ts "
},
@ -34,7 +35,7 @@
"access": "public"
},
"dependencies": {
"@kevisual/ai": "^0.0.6",
"@kevisual/ai": "^0.0.8",
"@kevisual/code-center-module": "0.0.23",
"@kevisual/context": "^0.0.3",
"@kevisual/router": "0.0.23",
@ -47,6 +48,7 @@
},
"devDependencies": {
"@kevisual/app-assistant": "workspace:*",
"@kevisual/logger": "^0.0.4",
"@kevisual/social-prompts": "workspace:*",
"@kevisual/types": "^0.0.10",
"@kevisual/use-config": "^1.0.19",
@ -56,7 +58,7 @@
"@types/formidable": "^3.4.5",
"@types/lodash-es": "^4.17.12",
"@types/node": "^24.0.3",
"bullmq": "^5.54.3",
"bullmq": "^5.55.0",
"commander": "^14.0.0",
"concurrently": "^9.1.2",
"cross-env": "^7.0.3",
@ -64,6 +66,7 @@
"inquire": "^0.4.8",
"ioredis": "^5.6.1",
"nodemon": "^3.1.10",
"openai": "^5.6.0",
"pg": "^8.16.2",
"rimraf": "^6.0.1",
"sequelize": "^6.37.7",

2
packages/xhs/package.json
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@ -6,7 +6,7 @@
"types": "app.d.ts",
"scripts": {
"build": "bun run bun.config.mjs",
"postbuild": "dts -i src/index.ts -o app.d.ts",
"postbuild2": "dts -i src/index.ts -o app.d.ts",
"cmd": "tsx src/test/command.ts ",
"dts": "dts -i src/index.js -o app.d.ts"
},

18
packages/xhs/src/routes/mentions/mention.ts
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@ -75,17 +75,31 @@ app
.define(async (ctx) => {
const { note_id, comment_id, content } = ctx.query;
const client = xhsServices.getClient();
// content 300个字内，超过cai fen
const textArr: string[] = [];
if (content.length > 300) {
const num = Math.ceil(content.length / 300);
for (let i = 0; i < num; i++) {
textArr.push(content.slice(i * 300, (i + 1) * 300));
}
} else {
textArr.push(content);
}
const resArr: any[] = [];
for (const text of textArr) {
const res = await client.postComment({
note_id: note_id,
comment_id: comment_id,
content,
content: text,
});
if (res.code === 0) {
ctx.body = res.data;
resArr.push(res.data);
} else {
console.log('添加评论失败', res.code);
ctx.throw(res.code, '添加评论失败');
}
}
ctx.body = resArr;
})
.addTo(app);
app

43
pnpm-lock.yaml generated
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@ -9,8 +9,8 @@ importers:
.:
dependencies:
'@kevisual/ai':
specifier: ^0.0.6
version: 0.0.6
specifier: ^0.0.8
version: 0.0.8
'@kevisual/code-center-module':
specifier: 0.0.23
version: 0.0.23(dotenv@16.5.0)
@ -42,6 +42,9 @@ importers:
'@kevisual/app-assistant':
specifier: workspace:*
version: link:packages/app-assistant
'@kevisual/logger':
specifier: ^0.0.4
version: 0.0.4
'@kevisual/social-prompts':
specifier: workspace:*
version: link:packages/social-prompts
@ -67,8 +70,8 @@ importers:
specifier: ^24.0.3
version: 24.0.3
bullmq:
specifier: ^5.54.3
version: 5.54.3
specifier: ^5.55.0
version: 5.55.0
commander:
specifier: ^14.0.0
version: 14.0.0
@ -90,6 +93,9 @@ importers:
nodemon:
specifier: ^3.1.10
version: 3.1.10
openai:
specifier: ^5.6.0
version: 5.6.0(ws@8.18.1)(zod@3.25.67)
pg:
specifier: ^8.16.2
version: 8.16.2
@ -215,8 +221,8 @@ packages:
'@jridgewell/sourcemap-codec@1.5.0':
resolution: {integrity: sha512-gv3ZRaISU3fjPAgNsriBRqGWQL6quFx04YMPW/zD8XMLsU32mhCCbfbO6KZFLjvYpCZ8zyDEgqsgf+PwPaM7GQ==}
'@kevisual/ai@0.0.6':
resolution: {integrity: sha512-khTCGsDMjGL9VN8ZB2HzEPUXcSTHu1fHXKBRmyojxy9gt+lMCx7JFgqLKiENkekOUwS2Xg6Fe5jwQDNJRwGwDA==}
'@kevisual/ai@0.0.8':
resolution: {integrity: sha512-MvK4U1iWf8hz7lj/+YBQV3qWRRDy42VH8fInKFVxjpEGPGaxfXOMP73C85T4Cf82OGU/fxOayiR0xLi2SyBTLw==}
'@kevisual/auth@1.0.5':
resolution: {integrity: sha512-GwsLj7unKXi7lmMiIIgdig4LwwLiDJnOy15HHZR5gMbyK6s5/uJiMY5RXPB2+onGzTNDqFo/hXjsD2wkerHPVg==}
@ -574,8 +580,8 @@ packages:
bullmq@5.51.1:
resolution: {integrity: sha512-JEZokH5Sb6p66HRjbfQjPNYuSilDRcB8UREmJzOBqTTaJFza8I92vsBF3J/zmtzd7KVv3dxhZyH9CYSLOJALRA==}
bullmq@5.54.3:
resolution: {integrity: sha512-MVK2pOkB3hvrIcubwI8dS4qWHJLNKakKPpgRBTw91sIpPZArmvZ4t2hvryyEaJXJbAS/JHd6pKYOUd+RGRkWQQ==}
bullmq@5.55.0:
resolution: {integrity: sha512-LKaQZroyXBYSQd/SNP9EcmCZgiZjIImtQHBlnupUvhX1GmmJfIXjn0bf8lek3bvajMUbvVf8FrYdFD0ajAuy0g==}
bun-types@1.2.16:
resolution: {integrity: sha512-ciXLrHV4PXax9vHvUrkvun9VPVGOVwbbbBF/Ev1cXz12lyEZMoJpIJABOfPcN9gDJRaiKF9MVbSygLg4NXu3/A==}
@ -1458,6 +1464,18 @@ packages:
once@1.4.0:
resolution: {integrity: sha512-lNaJgI+2Q5URQBkccEKHTQOPaXdUxnZZElQTZY0MFUAuaEqe1E+Nyvgdz/aIyNi6Z9MzO5dv1H8n58/GELp3+w==}
openai@5.6.0:
resolution: {integrity: sha512-jNH5z+hYAdOMZXyEt0yZ7246s+UZjg2AwFQqkAhZIPPjxNtHHO5mykOefau6FkOqj16aC94MOdJl/rZBcKj/cQ==}
hasBin: true
peerDependencies:
ws: ^8.18.0
zod: ^3.23.8
peerDependenciesMeta:
ws:
optional: true
zod:
optional: true
own-keys@1.0.1:
resolution: {integrity: sha512-qFOyK5PjiWZd+QQIh+1jhdb9LpxTF0qs7Pm8o5QHYZ0M3vKqSqzsZaEB6oWlxZ+q2sJBMI/Ktgd2N5ZwQoRHfg==}
engines: {node: '>= 0.4'}
@ -2182,7 +2200,7 @@ snapshots:
'@jridgewell/sourcemap-codec@1.5.0': {}
'@kevisual/ai@0.0.6':
'@kevisual/ai@0.0.8':
dependencies:
'@kevisual/logger': 0.0.4
@ -2550,7 +2568,7 @@ snapshots:
transitivePeerDependencies:
- supports-color
bullmq@5.54.3:
bullmq@5.55.0:
dependencies:
cron-parser: 4.9.0
ioredis: 5.6.1
@ -3629,6 +3647,11 @@ snapshots:
dependencies:
wrappy: 1.0.2
openai@5.6.0(ws@8.18.1)(zod@3.25.67):
optionalDependencies:
ws: 8.18.1
zod: 3.25.67
own-keys@1.0.1:
dependencies:
get-intrinsic: 1.2.7

3
src/agent/agent.ts Normal file
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@ -0,0 +1,3 @@
import { QueryRouterServer } from '@kevisual/router';
export const agent = new QueryRouterServer();

16
src/agent/ai.ts Normal file
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@ -0,0 +1,16 @@
import { SiliconFlowProvider } from '@kevisual/ai';
import { config } from '../modules/config.ts';
export const ai = new SiliconFlowProvider({
model: 'Qwen/Qwen3-32B',
// model: 'Pro/deepseek-ai/DeepSeek-R1',// 只有充值能用
apiKey: config.SILICONFLOW_API_KEY,
});
ai.getUsageInfo()
.then((usage) => {
console.log('AI usage info:', usage);
})
.catch((res) => {
console.error('Error fetching AI usage info:', res.status);
});

95
src/agent/analyze/content.ts Normal file
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@ -0,0 +1,95 @@
import { agent } from '@/agent/agent.ts';
import { ai } from '../ai.ts';
import { logger } from '@/agent/logger.ts';
const getJsonFromString = (str: string) => {
// 尝试从字符串中提取JSON对象
try {
const jsonMatch = str.match(/```json\s*([\s\S]*?)\s*```/);
if (jsonMatch && jsonMatch[1]) {
return JSON.parse(jsonMatch[1]);
}
} catch (error) {
console.error('Error parsing JSON from string:', error);
}
return null;
};
agent
.route({
path: 'analyze',
key: 'content',
description: '分析文本内容,意图分析，判断是否需要获取上下文包函小红书的图片，视频，文本。',
})
.define(async (ctx) => {
const text = ctx.query?.text || '';
let result = {
image: false,
video: false,
text: false,
comment: false,
};
const prompt = `
请分析<context>包函的内容，判断是否需要包含小红书的图片、视频或文本信息，返回一个JSON对象，包含三个布尔值：image（是否包含图片）、video（是否包含视频）、text（是否包含小红书文本），comment（是否是评论信息）。
如果文本中提到图片或视频，请返回true，否则返回false。
文本示例：
1. "解答一下这个笔记。" , text为true
2. "分析一下这个图片。", image为true
3. "这个视频介绍的是什么。", video为true
4. "评价一下这个评论。", comment为true
返回内容示例：
\`\`\`json
{
"image": true,
"video": false,
"text": true,
"comment": false
}
\`\`\`
分析的文本的内容是:
<context>
${text}
</context>
`;
const now = Date.now();
console.log('start');
const res = await ai
.chat(
[
{
role: 'user',
content: prompt,
},
],
{
// @ts-ignore
enable_thinking: false,
},
)
.catch((err) => {
console.log('AI service error:', err.status);
ctx.throw(500, 'AI service error: ' + err.status);
return err;
});
console.log('end', Date.now() - now, 'ms');
const ans = res.choices[0]?.message?.content || '';
if (!ans) {
logger.error('Empty response from AI:', res);
}
const json = getJsonFromString(ans);
if (!json) {
logger.error('Invalid JSON format in response:', ans);
ctx.throw(400, 'Invalid JSON format in response');
}
result = {
image: json.image || false,
video: json.video || false,
text: json.text || false,
comment: json.comment || false,
};
ctx.body = result;
})
.addTo(agent);

64
src/agent/fix/prompt.ts Normal file
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@ -0,0 +1,64 @@
import { agent } from '@/agent/agent.ts';
import { ai } from '../ai.ts';
import { logger } from '@/agent/logger.ts';
const getTagContent = (text: string) => {
const match = text.match(/<content>([\s\S]*?)<\/content>/);
return match ? match[1].trim() : text;
};
agent
.route({
path: 'fix',
key: 'xhs',
description: '对小红书的提示词进行修正和优化',
})
.define(async (ctx) => {
const text = ctx.query?.text || '';
const now = Date.now();
console.log('start');
const res = await ai
.chat(
[
{
role: 'user',
content: `
你是一个提示词优化的专家，请根据用户提供的提示词进行修正和优化，其中用户的提示词返回的要求如果没有或者不明确，请你都修正为要求返回的文本在500字以内，且内容是纯文本格式，不能是markdown模式，也不包含任何HTML标签或其他格式化内容。
只对提示词进行优化，并且不需要对内容进行分析或总结。
示例1. 用户提示词
<content>总结笔记</content>
优化后的提示词
<content>请总结一下这个笔记，要求返回的内容是纯文本格式，字数不超过500字。</content>
示例2. 用户提示词
<content>分析一下这个图片</content>
优化后的提示词
<content>请分析一下这个图片，要求返回的内容是纯文本格式，字数不超过500字。</content>
用户的提示词是
<content>
${text}
</content>
`,
},
],
{
// @ts-ignore
enable_thinking: false,
},
)
.catch((err) => {
console.log('AI service error:', err.status);
ctx.throw(500, 'AI service error: ' + err.status);
return err;
});
console.log('end', Date.now() - now, 'ms');
const ans = res.choices[0]?.message?.content || '';
if (!ans) {
logger.error('Empty response from AI:', res);
}
ctx.body = getTagContent(ans)
})
.addTo(agent);

7
src/agent/index.ts Normal file
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@ -0,0 +1,7 @@
import { agent } from './agent.ts';
import './analyze/content.ts';
import './fix/prompt.ts';
import './xhs.ts';
export { agent };

3
src/agent/logger.ts Normal file
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@ -0,0 +1,3 @@
import { Logger } from '@kevisual/logger';
export const logger = new Logger();

19
src/agent/test/analyze.ts Normal file
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@ -0,0 +1,19 @@
import { agent } from '../index.ts';
const main = async () => {
const text1 = '解答一下这个笔记。';
const text2 = '分析一下这个图片';
const text3 = '这个视频介绍的是什么';
const text4 = '评价一下这个评论。';
const text5 = '关于这个评论。';
const text6 = '1+1=';
const res = await agent.call({
path: 'analyze',
key: 'content',
payload: {
text: text6,
},
});
console.log('analyze content res', res.code, 'content', res.body);
};
main();

0
src/agent/test/common.ts Normal file
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18
src/agent/test/prompt-fix.ts Normal file
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@ -0,0 +1,18 @@
// 其中回复的要求是以纯文本，具体的内容在<content></content>当中
import { agent } from '../index.ts';
const main = async () => {
const text = '请总结一下这个笔记。';
const text2 = '告诉我1+1的值';
const text3 = 'html和css的大纲是什么？';
const text4 = '1+1=';
const res = await agent.call({
path: 'fix',
key: 'xhs',
payload: {
text: text4,
},
});
console.log('fix xhs res', res.code, 'content', res.body);
};
main();

53
src/agent/xhs.ts Normal file
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@ -0,0 +1,53 @@
import { nanoid } from 'nanoid';
import { agent } from './agent.ts';
import { ai } from './ai.ts';
/**
* 清除文本中的@信息
* @param text
*/
const clearAtInfo = (text: string = '') => {
const newText = text.replace(/@[\u4e00-\u9fa5\w]+/g, '').replace(/#.*?#/g, '');
return newText.trim();
};
agent
.route({
path: 'xhs',
})
.define(async (ctx) => {
const { text = '' } = ctx.query || {};
const id = nanoid();
const no_at_text = clearAtInfo(text);
const resFix = await agent.call({
path: 'fix',
key: 'xhs',
payload: {
text: no_at_text,
},
});
if (resFix.code !== 200) {
ctx.throw(500, 'AI 小红书prompt优化错误: ' + resFix.message);
return;
} else {
console.log('小红书优化的文本', resFix.body);
}
const prompt_text = resFix.body || '';
const res = await ai
.chat(
[
{
role: 'user',
content: prompt_text,
},
],
{
// @ts-ignore
enable_thinking: false,
},
)
.catch((error) => {
ctx.throw(500, 'AI 服务错误: ' + error.status);
return error;
});
ctx.body = res.choices?.[0]?.message?.content || '';
})
.addTo(agent);

3
src/modules/notify.ts Normal file
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@ -0,0 +1,3 @@
export const notify = () => {
//
};

25
src/task/routes/mention.ts
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@ -1,3 +1,4 @@
import { agent } from '@/agent/index.ts';
import { taskApp, queue, xhsApp } from '../task.ts';
import { random, omit } from 'lodash-es';
import util from 'node:util';
@ -10,6 +11,7 @@ taskApp
.route({
path: 'task',
key: 'getUnread',
description: '获取未读提及消息',
})
.define(async (ctx) => {
const res = await xhsApp.call({
@ -50,6 +52,7 @@ taskApp
.route({
path: 'task',
key: 'getMention',
description: '获取提及消息',
})
.define(async (ctx) => {
const { unread_count } = ctx.query;
@ -61,11 +64,9 @@ taskApp
num: unread_count,
},
});
console.log('mentionRes', mentionRes.body);
if (mentionRes.code === 200) {
let data = mentionRes.body || [];
// data = data.map((item) => omit(item, 'mention'));
console.log('queryMention', util.inspect(data, { depth: 10 }));
for (let i = 0; i < data.length; i++) {
const item = data[i];
queue.add(
@ -86,7 +87,6 @@ taskApp
},
},
);
console.log('add mention task', item);
await sleep(200);
}
}
@ -94,9 +94,7 @@ taskApp
path: 'mention',
key: 'postRead',
});
console.log('postRead', postRead.body);
}
await sleep(1000);
ctx.body = {
job: unread_count,
};
@ -109,7 +107,7 @@ taskApp
key: 'ai',
})
.define(async (ctx) => {
const data = ctx.query.data;
const data = ctx.query.data; // 为提及的相关信息
const note_id = data.note_id;
const xsec_token = data.xsec_token;
const comment_id = data.comment.comment_id;
@ -119,6 +117,21 @@ taskApp
content,
comment_id,
};
const resAgent = await agent.call({
path: 'xhs',
payload: {
text: content,
},
});
let responseText = '';
let errorText = '';
if (resAgent.code !== 200) {
errorText = '【调用错误】';
responseText = `${resAgent.message}`;
} else {
responseText = resAgent.body;
}
postData.content = responseText;
const res = await xhsApp.call({
path: 'mention',
key: 'addComment',

22
turbo.json Normal file
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@ -0,0 +1,22 @@
{
"$schema": "https://turbo.build/schema.json",
"tasks": {
"build": {
"dependsOn": [
"^build"
],
"outputs": [
"dist/**"
]
},
"dev:lib": {
"persistent": true,
"cache": true
},
"build:lib": {
"dependsOn": [
"^build:lib"
]
}
}
}