Files
dootask/app/Http/Controllers/Api/AssistantController.php
T
kuaifan f8b335a003 feat(ai-assistant): 增加元素向量匹配与关键词搜索能力
- 新增后端 match_elements API,使用向量相似度匹配页面元素
  - 页面上下文采集支持关键词过滤,按 name/aria-label/placeholder/title 匹配
  - 关键词匹配失败时自动降级为向量搜索
  - 改进 findElementByRef 函数,使用 selector + name 双重匹配提高准确性
2026-01-18 11:50:27 +00:00

159 lines
4.7 KiB
PHP

<?php
namespace App\Http\Controllers\Api;
use App\Models\User;
use App\Module\AI;
use App\Module\Apps;
use App\Module\Base;
use Request;
/**
* @apiDefine assistant
*
* 助手
*/
class AssistantController extends AbstractController
{
public function __construct()
{
Apps::isInstalledThrow('ai');
}
/**
* @api {post} api/assistant/auth 生成授权码
*
* @apiDescription 需要token身份,生成 AI 流式会话的 stream_key
* @apiVersion 1.0.0
* @apiGroup assistant
* @apiName auth
*
* @apiParam {String} model_type 模型类型
* @apiParam {String} model_name 模型名称
* @apiParam {JSON} context 上下文数组
*
* @apiSuccess {Number} ret 返回状态码(1正确、0错误)
* @apiSuccess {String} msg 返回信息(错误描述)
* @apiSuccess {Object} data 返回数据
* @apiSuccess {String} data.stream_key 流式会话凭证
*/
public function auth()
{
$user = User::auth();
$user->checkChatInformation();
$modelType = trim(Request::input('model_type', ''));
$modelName = trim(Request::input('model_name', ''));
$contextInput = Request::input('context', []);
return AI::createStreamKey($modelType, $modelName, $contextInput);
}
/**
* @api {get} api/assistant/models 获取AI模型
*
* @apiDescription 获取所有AI机器人模型设置
* @apiVersion 1.0.0
* @apiGroup assistant
* @apiName models
*
* @apiSuccess {Number} ret 返回状态码(1正确、0错误)
* @apiSuccess {String} msg 返回信息(错误描述)
* @apiSuccess {Object} data 返回数据
*/
public function models()
{
$setting = Base::setting('aibotSetting');
$setting = array_filter($setting, function ($value, $key) {
return str_ends_with($key, '_models') || str_ends_with($key, '_model');
}, ARRAY_FILTER_USE_BOTH);
return Base::retSuccess('success', $setting ?: json_decode('{}'));
}
/**
* @api {post} api/assistant/match-elements 元素向量匹配
*
* @apiDescription 通过向量相似度匹配页面元素,用于智能查找与查询语义相关的元素
* @apiVersion 1.0.0
* @apiGroup assistant
* @apiName match_elements
*
* @apiParam {String} query 搜索关键词
* @apiParam {Array} elements 元素列表,每个元素包含 ref 和 name 字段
* @apiParam {Number} [top_k=10] 返回的匹配数量,最大50
*
* @apiSuccess {Number} ret 返回状态码(1正确、0错误)
* @apiSuccess {String} msg 返回信息(错误描述)
* @apiSuccess {Object} data 返回数据
* @apiSuccess {Array} data.matches 匹配结果数组,按相似度降序排列
*/
public function match_elements()
{
User::auth();
$query = trim(Request::input('query', ''));
$elements = Request::input('elements', []);
$topK = min(intval(Request::input('top_k', 10)), 50);
if (empty($query) || empty($elements)) {
return Base::retError('参数不能为空');
}
// 获取查询向量
$queryResult = AI::getEmbedding($query);
if (Base::isError($queryResult)) {
return $queryResult;
}
$queryVector = $queryResult['data'];
// 计算相似度并排序
$scored = [];
foreach ($elements as $el) {
$name = $el['name'] ?? '';
if (empty($name)) {
continue;
}
$elResult = AI::getEmbedding($name);
if (Base::isError($elResult)) {
continue;
}
$similarity = $this->cosineSimilarity($queryVector, $elResult['data']);
$scored[] = [
'element' => $el,
'similarity' => $similarity,
];
}
// 按相似度降序排序
usort($scored, fn($a, $b) => $b['similarity'] <=> $a['similarity']);
return Base::retSuccess('success', [
'matches' => array_slice($scored, 0, $topK),
]);
}
/**
* 计算两个向量的余弦相似度
*/
private function cosineSimilarity(array $a, array $b): float
{
$dotProduct = 0;
$normA = 0;
$normB = 0;
$count = count($a);
for ($i = 0; $i < $count; $i++) {
$dotProduct += $a[$i] * $b[$i];
$normA += $a[$i] * $a[$i];
$normB += $b[$i] * $b[$i];
}
$denominator = sqrt($normA) * sqrt($normB);
if ($denominator == 0) {
return 0;
}
return $dotProduct / $denominator;
}
}