修改自动推广的相关任务

.env

@@ -24,6 +24,7 @@ PROMOTION_LLM_URL=http://chat.taimed.cn/v1/chat/completions
 PROMOTION_LLM_MODEL=your-model-name
 PROMOTION_LLM_TIMEOUT=30
 PROMOTION_LLM_FALLBACK=""
+PROMOTION_LLM_ADVISED_FALLBACK=""
 
 [journal]
 ;官网服务器地址

application/common/PromotionLlmService.php

@@ -7,20 +7,24 @@ use think\Env;
 /**
  * 推广邮件 LLM 服务
  *
- * 作用：基于 expert 的代表作 (paper_title) + 期刊信息 (name / scope 等)，
+ * 作用：基于 expert 的代表作 (paper_title)、expert 的研究领域、期刊信息 (name / scope / fields 等)，
- * 生成一段 2-3 句的个性化描述，用于邮件模板变量 {{llm_description}}。
+ *      通过一次 LLM 调用同时生成两段邮件内容：
+ *        - description    个性化赞美 + 邀稿段落（对应模板变量 {{ai_content_analysis}} / {{llm_description}}）
+ *        - advised_topics "我们特别关注 X / Y / Z 领域" 段落（对应模板变量 {{ai_advised_topics}}）
+ *
+ * 单次调用返回 JSON，避免两次 LLM 请求导致的延迟翻倍；任一段失败可独立兜底。
  *
  * 配置（.env 的 [promotion] 段）：
- *   PROMOTION_LLM_URL      chat/completions 接口地址
+ *   PROMOTION_LLM_URL               chat/completions 接口地址
- *   PROMOTION_LLM_MODEL    模型名
+ *   PROMOTION_LLM_MODEL             模型名
- *   PROMOTION_LLM_TIMEOUT  超时时间(秒)，默认 30
+ *   PROMOTION_LLM_TIMEOUT           超时时间(秒)，默认 30
- *   PROMOTION_LLM_FALLBACK 兜底描述（LLM 不可用 / 调用失败时使用）
+ *   PROMOTION_LLM_FALLBACK          description 兜底文案
+ *   PROMOTION_LLM_ADVISED_FALLBACK  advised_topics 兜底文案
  *
- * 返回约定：
+ * 状态约定：
- *   ['status' => 1|2|3, 'text' => string]
+ *   1 = LLM 成功生成
- *     1 = LLM 成功生成
+ *   2 = LLM 调用失败 / 解析失败，使用兜底
- *     2 = LLM 调用失败，text = 兜底文案
+ *   3 = 前置条件不足（缺代表作、缺交集等），使用兜底
- *     3 = 跳过（缺少代表作等前置条件），text = 兜底文案
  */
 class PromotionLlmService
 {
@@ -29,6 +33,7 @@ class PromotionLlmService
     private $timeout;
     private $apiKey;
     private $fallback;
+    private $advisedFallback;
 
     public function __construct()
     {
@@ -38,27 +43,54 @@ class PromotionLlmService
         $this->apiKey   = trim((string)Env::get('promotion.promotion_llm_api_key', ''));
         $this->fallback = trim((string)Env::get('promotion.promotion_llm_fallback',
             'Your recent work aligns closely with the scope of our journal, and we would be honored to consider a contribution from you.'));
+        $this->advisedFallback = trim((string)Env::get('promotion.promotion_llm_advised_fallback',
+            'We are especially interested in the research directions that align with your expertise, and warmly welcome your future submissions in these areas.'));
     }
 
     /**
-     * 生成个性化描述
+     * 一次 LLM 调用生成邮件两段内容。
      *
-     * @param array $expert  至少包含 name / representative_work_title / fields / affiliation
+     * @param array $expert         expert 行（含 name / representative_work_title / fields 等）
-     * @param array $journal 至少包含 title (name) / aims (可选) / databases (可选)
+     * @param array $journal        journal 行（含 title / aims / databases 等）
-     * @return array ['status' => 1|2|3, 'text' => string]
+     * @param array $overlapFields  预先计算的 expert & journal 领域交集（可能为空）
+     * @param array $journalFields  journal（或 task/工厂）的目标领域
+     * @param array $expertFields   expert 的研究领域
+     * @return array [
+     *   'description'            => string,
+     *   'description_status'     => 1|2|3,
+     *   'advised_topics'         => string,
+     *   'advised_topics_status'  => 1|2|3,
+     * ]
      */
-    public function generateDescription(array $expert, array $journal): array
+    public function generateEmailContent(
-    {
+        array $expert,
+        array $journal,
+        array $overlapFields = [],
+        array $journalFields = [],
+        array $expertFields = []
+    ): array {
         $paperTitle  = trim((string)($expert['representative_work_title'] ?? ''));
         $expertName  = trim((string)($expert['name'] ?? ''));
         $journalName = trim((string)($journal['title'] ?? ''));
 
-        if ($paperTitle === '' || $journalName === '') {
+        $overlapList  = $this->cleanList($overlapFields);
-            return ['status' => 3, 'text' => $this->fallback];
+        $journalList  = $this->cleanList($journalFields);
+        $expertList   = $this->cleanList($expertFields);
+
+        $hasDescInput    = ($paperTitle !== '' && $journalName !== '');
+        $hasAdvisedInput = (!empty($overlapList) || (!empty($journalList) && !empty($expertList)));
+
+        // 两段都缺输入时直接走双兜底
+        if (!$hasDescInput && !$hasAdvisedInput) {
+            return $this->allFallback(3, 3);
         }
 
+        // LLM 未配置
         if ($this->url === '' || $this->model === '') {
-            return ['status' => 2, 'text' => $this->fallback];
+            return $this->allFallback(
+                $hasDescInput ? 2 : 3,
+                $hasAdvisedInput ? 2 : 3
+            );
         }
 
         $expertField = trim((string)($expert['fields'] ?? ($expert['field'] ?? '')));
@@ -66,27 +98,48 @@ class PromotionLlmService
         $journalDbs  = trim((string)($journal['databases'] ?? ''));
 
         $system = 'You are an academic editorial assistant. '
-            . 'Write a short, warm, professional English paragraph (2-3 sentences, <=50 words) '
+            . 'You will receive context about an author, their recent paper, and a target journal, '
-            . 'that: (1) briefly appreciates the author\'s recent paper, '
+            . 'and you must produce TWO English paragraphs for an invitation email. '
-            . '(2) explains why it fits the journal\'s scope, '
+            . 'Output STRICT MINIFIED JSON ONLY with exactly these keys:'
-            . '(3) gently invites a future submission. '
+            . '{"description":"...","advised_topics":"..."} '
-            . 'Do NOT use placeholders, do NOT add greetings, do NOT add signatures, '
+            . 'Rules for "description": 2-3 sentences, <=50 words, warm and professional; '
-            . 'output plain text only (no markdown).';
+            . '(a) briefly appreciate the author\'s recent paper, '
+            . '(b) explain why it fits the journal\'s scope, '
+            . '(c) gently invite a future submission. '
+            . 'Rules for "advised_topics": 1-2 sentences, <=40 words; '
+            . 'emphasize that the journal is particularly interested in the research directions '
+            . 'where the journal\'s focus and the author\'s work overlap; '
+            . 'mention the overlapping topics explicitly (use the provided overlap list when non-empty, '
+            . 'otherwise choose the best semantic overlap between journal focus and author fields); '
+            . 'end by inviting contributions leaning toward those directions. '
+            . 'No greetings, no signatures, no placeholders, no markdown, no code fences. '
+            . 'If a section genuinely cannot be produced, return an empty string for that key.';
 
         $userLines = [];
         $userLines[] = 'Author name: ' . ($expertName !== '' ? $expertName : '(unknown)');
         if ($expertField !== '') {
-            $userLines[] = 'Author research field: ' . $expertField;
+            $userLines[] = 'Author research field (raw): ' . $expertField;
+        }
+        if (!empty($expertList)) {
+            $userLines[] = 'Author research fields (list): ' . implode(', ', $expertList);
+        }
+        $userLines[] = 'Recent paper title: ' . ($paperTitle !== '' ? $paperTitle : '(none)');
+        $userLines[] = 'Target journal: ' . ($journalName !== '' ? $journalName : '(unknown)');
+        if (!empty($journalList)) {
+            $userLines[] = 'Journal focus fields: ' . implode(', ', $journalList);
+        }
+        if (!empty($overlapList)) {
+            $userLines[] = 'Overlap topics (exact match): ' . implode(', ', $overlapList);
+        } else {
+            $userLines[] = 'Overlap topics (exact match): (none, infer semantically from the two field lists above)';
         }
-        $userLines[] = 'Recent paper title: ' . $paperTitle;
-        $userLines[] = 'Target journal: ' . $journalName;
         if ($journalAims !== '') {
             $userLines[] = 'Journal aims & scope: ' . mb_substr($journalAims, 0, 500);
         }
         if ($journalDbs !== '') {
             $userLines[] = 'Journal indexing: ' . mb_substr($journalDbs, 0, 200);
         }
-        $userLines[] = 'Return only the paragraph, nothing else.';
+        $userLines[] = 'Return only minified JSON {"description":"...","advised_topics":"..."}.';
         $user = implode("\n", $userLines);
 
         $payload = [
@@ -100,15 +153,55 @@ class PromotionLlmService
 
         $content = $this->postChat($payload);
         if ($content === null) {
-            return ['status' => 2, 'text' => $this->fallback];
+            return $this->allFallback(
+                $hasDescInput ? 2 : 3,
+                $hasAdvisedInput ? 2 : 3
+            );
         }
 
-        $content = $this->cleanContent($content);
+        $parsed = $this->parseJson($content);
-        if ($content === '') {
+        if ($parsed === null) {
-            return ['status' => 2, 'text' => $this->fallback];
+            return $this->allFallback(
+                $hasDescInput ? 2 : 3,
+                $hasAdvisedInput ? 2 : 3
+            );
         }
 
-        return ['status' => 1, 'text' => $content];
+        $desc    = $this->cleanContent((string)($parsed['description'] ?? ''));
+        $advised = $this->cleanContent((string)($parsed['advised_topics'] ?? ''));
+
+        $descStatus = 1;
+        if ($desc === '') {
+            $desc = $this->fallback;
+            $descStatus = $hasDescInput ? 2 : 3;
+        }
+
+        $advisedStatus = 1;
+        if ($advised === '') {
+            $advised = $this->advisedFallback;
+            $advisedStatus = $hasAdvisedInput ? 2 : 3;
+        }
+
+        return [
+            'description'           => $desc,
+            'description_status'    => $descStatus,
+            'advised_topics'        => $advised,
+            'advised_topics_status' => $advisedStatus,
+        ];
+    }
+
+    /**
+     * 兼容旧接口：单段 description 生成（仍走 generateEmailContent，取第一段）
+     *
+     * @return array ['status' => 1|2|3, 'text' => string]
+     */
+    public function generateDescription(array $expert, array $journal): array
+    {
+        $r = $this->generateEmailContent($expert, $journal);
+        return [
+            'status' => intval($r['description_status']),
+            'text'   => (string)$r['description'],
+        ];
     }
 
     /**
@@ -153,6 +246,28 @@ class PromotionLlmService
         return null;
     }
 
+    /**
+     * 从模型原始输出里提取 JSON 对象；失败返回 null。
+     */
+    private function parseJson(string $raw)
+    {
+        $raw = trim($raw);
+        if ($raw === '') return null;
+        $raw = preg_replace('/^```[a-zA-Z]*\s*|```$/m', '', $raw);
+        $raw = trim($raw);
+
+        // 直接 decode
+        $obj = json_decode($raw, true);
+        if (is_array($obj)) return $obj;
+
+        // 抓出第一个 {...} 块再 decode
+        if (preg_match('/\{.*\}/s', $raw, $m)) {
+            $obj = json_decode($m[0], true);
+            if (is_array($obj)) return $obj;
+        }
+        return null;
+    }
+
     /**
      * 清洗 LLM 输出：去除 markdown 包裹、多余空白、首尾引号、过长截断。
      */
@@ -169,8 +284,41 @@ class PromotionLlmService
         return trim($text);
     }
 
+    /**
+     * 对领域列表做 trim / 去空 / 去重，保留首次出现顺序。
+     */
+    private function cleanList(array $list): array
+    {
+        $out = [];
+        $seen = [];
+        foreach ($list as $item) {
+            $v = trim((string)$item);
+            if ($v === '') continue;
+            $key = strtolower($v);
+            if (isset($seen[$key])) continue;
+            $seen[$key] = true;
+            $out[] = $v;
+        }
+        return $out;
+    }
+
+    private function allFallback(int $descStatus, int $advisedStatus): array
+    {
+        return [
+            'description'           => $this->fallback,
+            'description_status'    => $descStatus,
+            'advised_topics'        => $this->advisedFallback,
+            'advised_topics_status' => $advisedStatus,
+        ];
+    }
+
     public function getFallback(): string
     {
         return $this->fallback;
     }
+
+    public function getAdvisedFallback(): string
+    {
+        return $this->advisedFallback;
+    }
 }

application/common/PromotionService.php

@@ -123,6 +123,17 @@ class PromotionService
             }
             $expert['fields'] = implode(',', $fieldSet);
             $expert['representative_work_title'] = $matchedTitle !== '' ? $matchedTitle : $fallbackTitle;
+
+            // 现场发送路径：没有提前准备 LLM，退回 .env 兜底文案
+            try {
+                $llmSvc = new PromotionLlmService();
+                $expert['llm_description']   = $llmSvc->getFallback();
+                $expert['ai_advised_topics'] = $llmSvc->getAdvisedFallback();
+            } catch (\Exception $e) {
+                $expert['llm_description']   = '';
+                $expert['ai_advised_topics'] = '';
+            }
+
             $expertVars  = $this->buildExpertVars($expert);
             $journalVars = $this->buildJournalVars($journal);
             $vars        = array_merge($journalVars, $expertVars);
@@ -312,21 +323,60 @@ class PromotionService
         $expert['fields'] = implode(',', $fieldSet);
         $expert['representative_work_title'] = $matchedTitle !== '' ? $matchedTitle : $fallbackTitle;
 
+        // 领域交集（大小写不敏感，保留 expert 原字面值用于展示）
+        $overlapFields = [];
+        if (!empty($taskFieldLower)) {
+            foreach ($fieldSet as $fn) {
+                if (isset($taskFieldLower[strtolower($fn)])) {
+                    $overlapFields[] = $fn;
+                }
+            }
+        }
+
         $journal = Db::name('journal')->where('journal_id', $task['journal_id'])->find();
 
-        // 调用 LLM 生成个性化描述（失败/缺条件时回退到兜底文案）
+        // 一次 LLM 调用生成两段内容（description + advised_topics）
-        $llmResult = ['status' => 0, 'text' => ''];
+        $llmResult = [
+            'description'           => '',
+            'description_status'    => 0,
+            'advised_topics'        => '',
+            'advised_topics_status' => 0,
+        ];
         try {
             $llm = new PromotionLlmService();
-            $llmResult = $llm->generateDescription($expert, $journal ?: []);
+            $llmResult = $llm->generateEmailContent(
+                $expert,
+                $journal ?: [],
+                $overlapFields,
+                $taskFields,
+                $fieldSet
+            );
         } catch (\Exception $e) {
-            $llmResult = ['status' => 2, 'text' => ''];
+            // 兜底双占位（$llm 实例可能未成功构建，单独拿一个尝试）
+            $fbDesc = '';
+            $fbAdvised = '';
+            try {
+                $fbSvc = isset($llm) ? $llm : new PromotionLlmService();
+                $fbDesc = $fbSvc->getFallback();
+                $fbAdvised = $fbSvc->getAdvisedFallback();
+            } catch (\Exception $ignore) {
+                // 忽略，使用空串
+            }
+            $llmResult = [
+                'description'           => $fbDesc,
+                'description_status'    => 2,
+                'advised_topics'        => $fbAdvised,
+                'advised_topics_status' => 2,
+            ];
             $this->log("prepareSingleEmail log_id={$logId} llm_exception=" . $e->getMessage());
         }
-        $llmText   = (string)$llmResult['text'];
+        $llmText          = (string)$llmResult['description'];
-        $llmStatus = intval($llmResult['status']);
+        $llmStatus        = intval($llmResult['description_status']);
+        $advisedText      = (string)$llmResult['advised_topics'];
+        $advisedStatus    = intval($llmResult['advised_topics_status']);
 
-        $expert['llm_description'] = $llmText;
+        $expert['llm_description']    = $llmText;
+        $expert['ai_advised_topics']  = $advisedText;
 
         $expertVars  = $this->buildExpertVars($expert);
         $journalVars = $this->buildJournalVars($journal);
@@ -341,27 +391,41 @@ class PromotionService
         $now = time();
         if ($rendered['code'] !== 0) {
             Db::name('promotion_email_log')->where('log_id', $logId)->update([
-                'state'           => 2,
+                'state'                     => 2,
-                'error_msg'       => 'Prepare failed: ' . $rendered['msg'],
+                'error_msg'                 => 'Prepare failed: ' . $rendered['msg'],
-                'llm_description' => mb_substr($llmText, 0, 2000),
+                'llm_description'           => mb_substr($llmText, 0, 2000),
-                'llm_status'      => $llmStatus,
+                'llm_status'                => $llmStatus,
-                'send_time'       => $now,
+                'llm_advised_topics'        => mb_substr($advisedText, 0, 2000),
+                'llm_advised_topics_status' => $advisedStatus,
+                'send_time'                 => $now,
             ]);
             $this->tryFinalizeTask($task['task_id']);
-            return ['code' => 1, 'msg' => $rendered['msg'], 'llm_status' => $llmStatus];
+            return [
+                'code' => 1,
+                'msg'  => $rendered['msg'],
+                'llm_status' => $llmStatus,
+                'llm_advised_topics_status' => $advisedStatus,
+            ];
         }
 
         Db::name('promotion_email_log')->where('log_id', $logId)->update([
-            'subject_prepared' => mb_substr($rendered['data']['subject'], 0, 512),
+            'subject_prepared'          => mb_substr($rendered['data']['subject'], 0, 512),
-            'body_prepared'    => $rendered['data']['body'],
+            'body_prepared'             => $rendered['data']['body'],
-            'llm_description'  => mb_substr($llmText, 0, 2000),
+            'llm_description'           => mb_substr($llmText, 0, 2000),
-            'llm_status'       => $llmStatus,
+            'llm_status'                => $llmStatus,
-            'prepared_at'      => $now,
+            'llm_advised_topics'        => mb_substr($advisedText, 0, 2000),
+            'llm_advised_topics_status' => $advisedStatus,
+            'prepared_at'               => $now,
         ]);
 
         $this->tryFinalizeTask($task['task_id']);
 
-        return ['code' => 0, 'msg' => 'ok', 'llm_status' => $llmStatus];
+        return [
+            'code' => 0,
+            'msg'  => 'ok',
+            'llm_status' => $llmStatus,
+            'llm_advised_topics_status' => $advisedStatus,
+        ];
     }
 
     /**
@@ -725,16 +789,19 @@ class PromotionService
 
     public function buildExpertVars($expert)
     {
-        $llm = $expert['llm_description'] ?? '';
+        $llm     = $expert['llm_description']    ?? '';
+        $advised = $expert['ai_advised_topics']  ?? '';
         return [
-            'expert_title'       => "Ph.D",
+            'expert_title'              => "Ph.D",
-            'expert_name'        => $expert['name'] ?? '',
+            'expert_name'               => $expert['name']        ?? '',
-            'expert_email'       => $expert['email'] ?? '',
+            'expert_email'              => $expert['email']       ?? '',
-            'expert_affiliation' => $expert['affiliation'] ?? '',
+            'expert_affiliation'        => $expert['affiliation'] ?? '',
-            'expert_field'       => $expert['fields'] ?? ($expert['field'] ?? ''),
+            'expert_field'              => $expert['fields']      ?? ($expert['field'] ?? ''),
             'representative_work_title' => $expert['representative_work_title'] ?? '',
-            'llm_description'    => $llm,
+            'llm_description'           => $llm,
-            'ai_content_analysis' => $llm,
+            'ai_content_analysis'       => $llm,
+            'ai_advised_topics'         => $advised,
+            'llm_advised_topics'        => $advised,
         ];
     }
 

sql/add_llm_advised_topics_to_promotion_email_log.sql

@@ -0,0 +1,7 @@
+-- 为 t_promotion_email_log 增加第二段 AI 生成字段（推荐投稿方向）
+-- llm_advised_topics:         大模型生成的"我们特别关注 X/Y/Z 领域"段落，对应模板变量 {{ai_advised_topics}}
+-- llm_advised_topics_status:  0未处理 1成功 2失败兜底 3跳过(无可用领域)
+
+ALTER TABLE `t_promotion_email_log`
+  ADD COLUMN `llm_advised_topics` TEXT NULL COMMENT '大模型生成的推荐投稿方向文案' AFTER `llm_description`,
+  ADD COLUMN `llm_advised_topics_status` TINYINT NOT NULL DEFAULT 0 COMMENT 'AI 推荐方向状态: 0未处理 1成功 2失败兜底 3跳过' AFTER `llm_advised_topics`;