总结expert领域的功能

application/common/ExpertFieldAiService.php

@@ -2,6 +2,7 @@
 
 namespace app\common;
 
+use app\common\service\LocalModelService;
 use think\Db;
 use think\Env;
 use think\Exception;
@@ -27,9 +28,17 @@ class ExpertFieldAiService
 
     private $logFile;
 
+    /** @var bool|null */
+    private static $schemaReady = null;
+
     public function __construct()
     {
         $this->logFile = ROOT_PATH . 'runtime' . DS . 'expert_field_ai.log';
+        try {
+            $this->ensureSchema();
+        } catch (\Throwable $e) {
+            $this->log('[ExpertFieldAi] ensureSchema fail: ' . $e->getMessage());
+        }
     }
 
     // ===================== 链式队列 =====================
@@ -366,10 +375,16 @@ class ExpertFieldAiService
         $papers = array_slice($papers, 0, $maxPapers);
         $searchKeywords = array_values(array_unique(array_filter($searchKeywords)));
 
-        $countryName = '';
+        // t_expert.country 已存国家英文名，无需再查 country 表
+        $countryName = trim((string)($expert['country'] ?? ''));
+        if ($countryName === '') {
             $countryId = intval($expert['country_id'] ?? 0);
             if ($countryId > 0) {
-            $countryName = (string)Db::name('country')->where('country_id', $countryId)->value('title');
+                $row = Db::name('country')->where('country_id', $countryId)->find();
+                if ($row) {
+                    $countryName = (string)($row['en_name'] ?? ($row['zh_name'] ?? ''));
+                }
+            }
         }
 
         return [
@@ -453,69 +468,27 @@ class ExpertFieldAiService
 
     private function summarizeWithLlm(array $context)
     {
-        $url = $this->resolveLlmChatUrl();
-        $model = $this->resolveLlmModel();
-        $apiKey = trim((string)Env::get(
-            'expert_field_ai.chat_api_key',
-            Env::get('user_field_ai.chat_api_key', Env::get('expert_country_chat_api_key', Env::get('citation_chat_api_key', '')))
-        ));
-
-        if ($url === '' || $model === '') {
-            throw new Exception('LLM not configured (set base.model_url / expert_field_ai.chat_model)');
-        }
-
         $payloadJson = json_encode($context, JSON_UNESCAPED_UNICODE | JSON_UNESCAPED_SLASHES);
-        $messages = [
+        $systemPrompt = '你是学术领域分类助手。根据专家的单位、论文标题与 PubMed 检索上下文，用简体中文总结该专家最主要的研究领域。'
-            [
-                'role'    => 'system',
-                'content' => '你是学术领域分类助手。根据专家的单位、论文标题与 PubMed 检索上下文，用简体中文总结该专家最主要的研究领域。'
             . '注意：search_keywords 只是检索词，不可直接当作领域结论，应结合 paper 标题与 affiliation 判断。'
             . '要求：精确、简洁，1～3 个中文领域词或短短语，用顿号分隔；不要解释、不要英文。'
-                    . '只输出 JSON：{"field_ai":"..."}。',
+            . '只输出 JSON：{"field_ai":"..."}。';
-            ],
+        $userPrompt = "请根据以下 JSON 资料总结该专家的主要研究领域：\n" . $payloadJson;
-            [
-                'role'    => 'user',
-                'content' => "请根据以下 JSON 资料总结该专家的主要研究领域：\n" . $payloadJson,
-            ],
-        ];
 
-        $body = [
+        // 按上下文长度动态选模型（小: base.model_url1 / 大: base.model_url）
-            'model'       => $model,
+        $svc = new LocalModelService();
-            'temperature' => 0.2,
+        $res = $svc->chat([
-            'messages'    => $messages,
+            ['role' => 'system', 'content' => $systemPrompt],
-        ];
+            ['role' => 'user',   'content' => $userPrompt],
+        ], ['temperature' => 0.2]);
 
-        $ch = curl_init();
+        if (empty($res['ok'])) {
-        curl_setopt_array($ch, [
+            throw new Exception('LLM error: ' . (string)($res['error'] ?? 'unknown'));
-            CURLOPT_URL            => $url,
-            CURLOPT_POST           => true,
-            CURLOPT_POSTFIELDS     => json_encode($body, JSON_UNESCAPED_UNICODE),
-            CURLOPT_RETURNTRANSFER => true,
-            CURLOPT_CONNECTTIMEOUT => 15,
-            CURLOPT_TIMEOUT        => max(30, (int)Env::get('expert_field_ai.timeout', Env::get('user_field_ai.timeout', 90))),
-            CURLOPT_HTTPHEADER     => array_filter([
-                'Content-Type: application/json',
-                $apiKey !== '' ? 'Authorization: Bearer ' . $apiKey : null,
-            ]),
-        ]);
-        $raw = curl_exec($ch);
-        $code = (int)curl_getinfo($ch, CURLINFO_HTTP_CODE);
-        $err = curl_error($ch);
-        curl_close($ch);
-
-        if ($raw === false) {
-            throw new Exception('LLM curl error: ' . $err);
-        }
-        if ($code < 200 || $code >= 300) {
-            throw new Exception('LLM HTTP ' . $code . ': ' . mb_substr((string)$raw, 0, 400));
         }
 
-        $data = json_decode($raw, true);
+        $this->log('[ExpertFieldAi] llm tier=' . ($res['tier'] ?? '') . ' ctx_len=' . ($res['context_len'] ?? 0) . ' url=' . ($res['url'] ?? ''));
-        $content = '';
-        if (is_array($data) && isset($data['choices'][0]['message']['content'])) {
-            $content = trim((string)$data['choices'][0]['message']['content']);
-        }
 
+        $content = trim((string)($res['content'] ?? ''));
         $fieldAi = $this->parseFieldAiFromContent($content);
         if ($fieldAi === '' && $content !== '') {
             $fieldAi = $this->cleanFieldAiText($content);
@@ -523,44 +496,6 @@ class ExpertFieldAiService
         return $fieldAi;
     }
 
-    private function resolveLlmChatUrl()
-    {
-        $candidates = [
-//            Env::get('expert_field_ai.chat_url', ''),
-//            Env::get('user_field_ai.chat_url', ''),
-            Env::get('base.model_url1', ''),
-        ];
-        foreach ($candidates as $u) {
-            $u = trim((string)$u);
-            if ($u === '') {
-                continue;
-            }
-            if (stripos($u, 'chat/completions') !== false) {
-                return $u;
-            }
-            return rtrim($u, '/') . '/v1/chat/completions';
-        }
-        return '';
-    }
-
-    private function resolveLlmModel()
-    {
-        $candidates = [
-            Env::get('expert_field_ai.chat_model', ''),
-            Env::get('user_field_ai.chat_model', ''),
-            Env::get('base.model', ''),
-            Env::get('expert_country_chat_model', ''),
-            'gpt-4.1',
-        ];
-        foreach ($candidates as $m) {
-            $m = trim((string)$m);
-            if ($m !== '' && strtolower($m) !== 'your-model-name') {
-                return $m;
-            }
-        }
-        return '';
-    }
-
     private function parseFieldAiFromContent($content)
     {
         $content = trim((string)$content);
@@ -637,18 +572,73 @@ class ExpertFieldAiService
 
     private function updateFieldAi($expertId, $fieldAi, $status, $source, $note)
     {
+        $this->ensureSchema();
+
         $data = [
             'field_ai'        => mb_substr(trim((string)$fieldAi), 0, 512),
             'field_ai_status' => intval($status),
             'field_ai_utime'  => time(),
-            'field_ai_source' => mb_substr(trim((string)$source), 0, 32),
         ];
+        if ($this->hasColumn('field_ai_source')) {
+            $data['field_ai_source'] = mb_substr(trim((string)$source), 0, 32);
+        }
+
         Db::name('expert')->where('expert_id', intval($expertId))->update($data);
         if ($note !== '') {
             $this->log('[ExpertFieldAi] expert_id=' . $expertId . ' status=' . $status . ' note=' . $note);
         }
     }
 
+    /**
+     * 自动补全 t_expert 上缺失的 field_ai 字段（可重复执行）。
+     */
+    public function ensureSchema()
+    {
+        if (self::$schemaReady === true) {
+            return;
+        }
+
+        $table = config('database.prefix') . 'expert';
+        $columns = Db::query('SHOW COLUMNS FROM `' . $table . '`');
+        $existing = [];
+        foreach ($columns as $col) {
+            $existing[$col['Field']] = true;
+        }
+
+        $alters = [];
+        if (!isset($existing['field_ai'])) {
+            $alters[] = "ADD COLUMN `field_ai` VARCHAR(512) NOT NULL DEFAULT '' COMMENT 'AI总结的主要研究领域(中文)' AFTER `affiliation`";
+            $existing['field_ai'] = true;
+        }
+        if (!isset($existing['field_ai_status'])) {
+            $alters[] = "ADD COLUMN `field_ai_status` TINYINT NOT NULL DEFAULT 0 COMMENT '0待处理 1已生成 2资料不足 3失败 4无user待AI' AFTER `field_ai`";
+            $existing['field_ai_status'] = true;
+        }
+        if (!isset($existing['field_ai_utime'])) {
+            $alters[] = "ADD COLUMN `field_ai_utime` INT NOT NULL DEFAULT 0 COMMENT 'field_ai更新时间' AFTER `field_ai_status`";
+            $existing['field_ai_utime'] = true;
+        }
+        if (!isset($existing['field_ai_source'])) {
+            $alters[] = "ADD COLUMN `field_ai_source` VARCHAR(32) NOT NULL DEFAULT '' COMMENT '来源: user_link / ai' AFTER `field_ai_utime`";
+            $existing['field_ai_source'] = true;
+        }
+
+        if (!empty($alters)) {
+            Db::execute('ALTER TABLE `' . $table . '` ' . implode(', ', $alters));
+            $this->log('[ExpertFieldAi] schema patched: ' . implode('; ', $alters));
+        }
+
+        self::$schemaReady = true;
+    }
+
+    private function hasColumn($column)
+    {
+        $this->ensureSchema();
+        $table = config('database.prefix') . 'expert';
+        $columns = Db::query('SHOW COLUMNS FROM `' . $table . '` LIKE \'' . addslashes($column) . '\'');
+        return !empty($columns);
+    }
+
     public function statusLabel($status)
     {
         $map = [

application/common/service/LocalModelService.php

@@ -0,0 +1,219 @@
+<?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 = 3000;
+
+    /** 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';
+    }
+}

sql/add_field_ai_source_to_expert.sql

@@ -0,0 +1,3 @@
+-- 若已执行过 add_field_ai_to_expert.sql 但缺少 field_ai_source，单独补这一列
+ALTER TABLE `t_expert`
+  ADD COLUMN `field_ai_source` VARCHAR(32) NOT NULL DEFAULT '' COMMENT '来源: user_link / ai' AFTER `field_ai_utime`;

sql/patch_expert_field_ai_columns.php

@@ -0,0 +1,46 @@
+<?php
+/**
+ * 补全 t_expert 缺失的 field_ai 相关字段（可重复执行）
+ * 用法: php sql/patch_expert_field_ai_columns.php
+ */
+$config = require __DIR__ . '/../application/database.php';
+
+$dsn = sprintf(
+    'mysql:host=%s;port=%s;dbname=%s;charset=%s',
+    $config['hostname'],
+    $config['hostport'],
+    $config['database'],
+    $config['charset']
+);
+$pdo = new PDO($dsn, $config['username'], $config['password'], [
+    PDO::ATTR_ERRMODE => PDO::ERRMODE_EXCEPTION,
+]);
+
+$table = $config['prefix'] . 'expert';
+$cols = $pdo->query("SHOW COLUMNS FROM `{$table}`")->fetchAll(PDO::FETCH_COLUMN, 0);
+$colSet = array_flip($cols);
+
+$alters = [];
+if (!isset($colSet['field_ai'])) {
+    $alters[] = "ADD COLUMN `field_ai` VARCHAR(512) NOT NULL DEFAULT '' COMMENT 'AI总结的主要研究领域(中文)' AFTER `affiliation`";
+}
+if (!isset($colSet['field_ai_status'])) {
+    $after = isset($colSet['field_ai']) || !empty($alters) ? 'field_ai' : 'affiliation';
+    $alters[] = "ADD COLUMN `field_ai_status` TINYINT NOT NULL DEFAULT 0 COMMENT '0待处理 1已生成 2资料不足 3失败 4无user待AI' AFTER `{$after}`";
+}
+if (!isset($colSet['field_ai_utime'])) {
+    $alters[] = "ADD COLUMN `field_ai_utime` INT NOT NULL DEFAULT 0 COMMENT 'field_ai更新时间' AFTER `field_ai_status`";
+}
+if (!isset($colSet['field_ai_source'])) {
+    $alters[] = "ADD COLUMN `field_ai_source` VARCHAR(32) NOT NULL DEFAULT '' COMMENT '来源: user_link / ai' AFTER `field_ai_utime`";
+}
+
+if (empty($alters)) {
+    echo "OK: all field_ai columns exist on {$table}\n";
+    exit(0);
+}
+
+$sql = "ALTER TABLE `{$table}` " . implode(', ', $alters);
+echo "Running: {$sql}\n";
+$pdo->exec($sql);
+echo "Done.\n";