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tougao/application/common/service/LocalModelService.php
2026-06-10 15:31:10 +08:00

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<?php
namespace app\common\service;
use think\Env;
/**
* 本地模型服务:按上下文长度自动选择模型
*
* - 短上下文 -> 小模型(显存为大模型一半),对应 base.model_url1
* - 长上下文 -> 大模型,对应 base.model_url
*
* 选择规则:上下文字符数 <= 阈值 用小模型;超过阈值 用大模型。
* 两个端点模型名相同base.model
*
* 用法:
* $svc = new LocalModelService();
* $res = $svc->chat([
* ['role' => 'system', 'content' => '...'],
* ['role' => 'user', 'content' => '...'],
* ]);
* // $res['ok'], $res['content'], $res['tier'](small|large), $res['context_len']
*
* // 只要文本结果:
* $text = $svc->complete($systemPrompt, $userPrompt);
*/
class LocalModelService
{
/** 上下文长度阈值(字符数):<= 用小模型,> 用大模型 */
const CONTEXT_THRESHOLD = 1000;
/** 请求超时(秒) */
const TIMEOUT = 120;
/** 小模型端点(短上下文,显存一半) */
private $smallUrl;
/** 大模型端点(长上下文) */
private $largeUrl;
/** 模型名(两端点相同) */
private $model;
/** 上下文长度阈值(字符数) */
private $threshold;
public function __construct()
{
// 小模型 -> base.model_url1大模型 -> base.model_url模型名同为 base.model
$this->smallUrl = $this->normalizeChatUrl((string)Env::get('base.model_url1', ''));
$this->largeUrl = $this->normalizeChatUrl((string)Env::get('base.model_url', ''));
$this->model = trim((string)Env::get('base.model', ''));
$this->threshold = self::CONTEXT_THRESHOLD;
}
/**
* 发起一次对话,按上下文长度自动选模型。
*
* @param array $messages OpenAI 格式 messages
* @param array $options 可选:
* - temperature (float, 默认 0.2)
* - max_tokens (int, 可选)
* - force_tier ('small'|'large') 强制指定模型,跳过长度判断
* - extra (array) 透传到请求体的额外字段
* @return array{ok:bool, content:string, tier:string, model:string, url:string, context_len:int, error:string}
*/
public function chat(array $messages, array $options = [])
{
$contextLen = $this->measureMessages($messages);
$tier = isset($options['force_tier']) && in_array($options['force_tier'], ['small', 'large'], true)
? $options['force_tier']
: $this->pickTier($contextLen);
$endpoint = $this->resolveEndpoint($tier);
$result = [
'ok' => false,
'content' => '',
'tier' => $tier,
'model' => $endpoint['model'],
'url' => $endpoint['url'],
'context_len' => $contextLen,
'error' => '',
];
if ($endpoint['url'] === '' || $endpoint['model'] === '') {
$result['error'] = $tier . ' 模型未配置(检查 .env [base] model_url / model_url1 / model';
return $result;
}
$payload = [
'model' => $endpoint['model'],
'temperature' => isset($options['temperature']) ? (float)$options['temperature'] : 0.2,
'messages' => $messages,
];
if (isset($options['max_tokens']) && intval($options['max_tokens']) > 0) {
$payload['max_tokens'] = intval($options['max_tokens']);
}
if (isset($options['extra']) && is_array($options['extra'])) {
$payload = array_merge($payload, $options['extra']);
}
$content = $this->postChat($endpoint['url'], $payload, $err);
if ($content === null) {
$result['error'] = $err !== '' ? $err : 'LLM 请求失败';
return $result;
}
$result['ok'] = true;
$result['content'] = $content;
return $result;
}
/**
* 便捷方法:传 system + user返回纯文本内容失败返回空字符串
*/
public function complete($systemPrompt, $userPrompt, array $options = [])
{
$messages = [];
if (trim((string)$systemPrompt) !== '') {
$messages[] = ['role' => 'system', 'content' => (string)$systemPrompt];
}
$messages[] = ['role' => 'user', 'content' => (string)$userPrompt];
$res = $this->chat($messages, $options);
return $res['ok'] ? $res['content'] : '';
}
/**
* 根据上下文长度选择 tier。
*/
public function pickTier($contextLen)
{
return $contextLen > $this->threshold ? 'large' : 'small';
}
/**
* 统计 messages 的上下文长度(所有 content 字符数之和)。
*/
public function measureMessages(array $messages)
{
$len = 0;
foreach ($messages as $m) {
if (isset($m['content']) && is_string($m['content'])) {
$len += mb_strlen($m['content']);
}
}
return $len;
}
/**
* 返回某 tier 的端点配置(模型名两端点相同)。
*/
private function resolveEndpoint($tier)
{
$url = $tier === 'large' ? $this->largeUrl : $this->smallUrl;
return ['url' => $url, 'model' => $this->model];
}
private function postChat($url, array $payload, &$err = '')
{
$err = '';
$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, $url);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload, JSON_UNESCAPED_UNICODE));
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false);
curl_setopt($ch, CURLOPT_CONNECTTIMEOUT, 15);
curl_setopt($ch, CURLOPT_TIMEOUT, self::TIMEOUT);
$headers = ['Content-Type: application/json'];
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$raw = curl_exec($ch);
if ($raw === false) {
$err = 'curl error: ' . curl_error($ch);
curl_close($ch);
return null;
}
$httpCode = intval(curl_getinfo($ch, CURLINFO_HTTP_CODE));
curl_close($ch);
if ($httpCode < 200 || $httpCode >= 300) {
$err = 'http ' . $httpCode . ': ' . mb_substr((string)$raw, 0, 300);
return null;
}
$data = json_decode($raw, true);
if (!is_array($data)) {
$err = 'invalid json response';
return null;
}
if (isset($data['choices'][0]['message']['content'])) {
return (string)$data['choices'][0]['message']['content'];
}
if (isset($data['content'])) {
return (string)$data['content'];
}
$err = 'no content in response: ' . mb_substr((string)$raw, 0, 300);
return null;
}
/**
* 根地址自动补 /v1/chat/completions。
*/
private function normalizeChatUrl($url)
{
$url = trim((string)$url);
if ($url === '') {
return '';
}
if (stripos($url, 'chat/completions') !== false) {
return $url;
}
return rtrim($url, '/') . '/v1/chat/completions';
}
}