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wangjinlei
331
application/common/CitationRelevanceService.php
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331
application/common/CitationRelevanceService.php
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<?php
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namespace app\common;
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/**
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* 引用相关性检测服务（PubMed + embedding）
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*
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* 依赖：
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* - PubmedService：用 DOI 抓取 title/abstract/mesh/publication_types
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* - CrossrefService：撤稿/更正识别（补充）
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*
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* embedding：
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* - 使用你们内部大模型的 embedding 接口（无需 token 付费，但速度慢）
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* - 通过构造参数传入 embedding_url / headers / timeout
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* - 内置文件缓存，减少重复 embedding 成本
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*/
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class CitationRelevanceService
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{
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private $pubmed;
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private $crossref;
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private $embeddingUrl = '';
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private $embeddingHeaders = [];
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private $timeout = 120;
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private $chatUrl = '';
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private $chatModel = '';
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private $embeddingDim = 256;
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private $chatMaxTokens = 1200;
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public function __construct(PubmedService $pubmed = null, CrossrefService $crossref = null, array $config = [])
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{
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$this->pubmed = $pubmed ?: new PubmedService();
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$this->crossref = $crossref ?: new CrossrefService();
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if (isset($config['embedding_url'])) $this->embeddingUrl = (string)$config['embedding_url'];
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if (isset($config['embedding_headers']) && is_array($config['embedding_headers'])) $this->embeddingHeaders = $config['embedding_headers'];
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if (isset($config['timeout'])) $this->timeout = max(10, intval($config['timeout']));
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if (isset($config['chat_url'])) $this->chatUrl = (string)$config['chat_url'];
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if (isset($config['chat_model'])) $this->chatModel = (string)$config['chat_model'];
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if (isset($config['embedding_dim'])) $this->embeddingDim = max(32, intval($config['embedding_dim']));
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if (isset($config['chat_max_tokens'])) $this->chatMaxTokens = max(256, intval($config['chat_max_tokens']));
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}
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/**
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* 单条引用相关性检测
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*
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* @param string $contextText 引用处上下文（英文）
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* @param array $referRow production_article_refer 行（至少含 refer_doi/doilink/title/author/joura/dateno）
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* @param array $options
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* - sentence_is_background(bool) 若外部已判断为背景堆引用，可直接降级
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* - sim_related(float) related 阈值，默认 0.75
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* - sim_unsure(float) unsure 阈值，默认 0.60
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* - check_retraction(bool) 是否检查撤稿/更正，默认 true
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*/
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public function checkOne(string $contextText, array $referRow, array $options = []): array
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{
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$contextText = trim($contextText);
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$simRelated = isset($options['sim_related']) ? (float)$options['sim_related'] : 0.75;
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$simUnsure = isset($options['sim_unsure']) ? (float)$options['sim_unsure'] : 0.60;
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$checkRetraction = isset($options['check_retraction']) ? (bool)$options['check_retraction'] : true;
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$isBackground = !empty($options['sentence_is_background']);
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// 1) 问题条目（退稿/更正）：先 Crossref（有 DOI 才能判断）
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$problemFlag = 'unknown';
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$problemReason = '';
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if ($checkRetraction) {
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$qc = $this->crossref->qcCitation($contextText, $referRow, ['check_retraction' => true]);
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$problemFlag = $qc['problem_flag'] ?? 'unknown';
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$problemReason = $qc['problem_reason'] ?? '';
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}
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// 2) PubMed 抓取 abstract/mesh（提升语义）
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$doi = $this->extractDoiFromRefer($referRow);
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$pub = $doi ? $this->pubmed->fetchByDoi($doi) : null;
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$pubText = '';
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$pubTypes = [];
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if ($pub) {
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$pubTypes = $pub['publication_types'] ?? [];
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$mesh = $pub['mesh_terms'] ?? [];
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$pubText = trim(
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($pub['title'] ?? '') . "\n" .
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($pub['abstract'] ?? '') . "\n" .
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(!empty($mesh) ? ('MeSH: ' . implode('; ', $mesh)) : '')
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);
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}
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// 3) embedding 相似度（context vs pubmed_text），无 pubmed_text 则退化为 crossref 的证据法
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if ($pubText !== '') {
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$v1 = $this->embedCached($contextText);
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$v2 = $this->embedCached($pubText);
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$sim = ($v1 && $v2) ? $this->cosine($v1, $v2) : 0.0;
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$relevanceFlag = 'unsure';
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if ($sim >= $simRelated) {
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$relevanceFlag = 'related';
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} elseif ($sim >= $simUnsure) {
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$relevanceFlag = 'unsure';
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} else {
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$relevanceFlag = $isBackground ? 'unsure_background' : 'suspicious_unrelated';
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}
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// PubMed 自身也能提示撤稿/更正（作为补充）
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if ($checkRetraction && $problemFlag !== 'retracted_or_corrected' && !empty($pubTypes)) {
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$ptLower = strtolower(implode(' | ', $pubTypes));
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if (strpos($ptLower, 'retracted publication') !== false
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|| strpos($ptLower, 'retraction of publication') !== false
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|| strpos($ptLower, 'published erratum') !== false
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) {
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$problemFlag = 'retracted_or_corrected';
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$problemReason = 'PubMed publication type indicates retraction/correction';
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}
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}
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return [
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'problem_flag' => $problemFlag,
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'problem_reason' => $problemReason,
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'relevance_flag' => $relevanceFlag,
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'relevance_score' => round($sim, 4),
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'reason' => $pubText !== '' ? 'embedding(context,pubmed_text)' : 'embedding_unavailable',
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'pubmed' => [
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'pmid' => $pub['pmid'] ?? '',
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'year' => $pub['year'] ?? '',
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'journal' => $pub['journal'] ?? '',
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'publication_types' => $pubTypes,
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],
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];
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}
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// 退化：没有 PubMed 信息时，用 CrossrefService 证据法（会偏保守）
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$fallback = $this->crossref->qcCitation($contextText, $referRow, ['check_retraction' => false]);
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$fallback['problem_flag'] = $problemFlag;
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$fallback['problem_reason'] = $problemReason;
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$fallback['reason'] = 'fallback_crossref_evidence; ' . ($fallback['reason'] ?? '');
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return $fallback;
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}
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// ---------------- embedding ----------------
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private function embedCached(string $text): ?array
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{
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$text = trim($text);
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if ($text === '') return null;
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$key = 'emb_' . sha1($text);
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$cached = $this->cacheGet($key, 90 * 86400);
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if (is_array($cached) && !empty($cached)) return $cached;
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$vec = $this->embed($text);
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if (is_array($vec) && !empty($vec)) {
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$this->cacheSet($key, $vec);
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return $vec;
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}
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return null;
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}
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/**
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* 调用内部 embedding 接口
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* 兼容返回格式：
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* - OpenAI embeddings: {data:[{embedding:[...] }]}
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* - {embedding:[...]}
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* - 直接返回数组 [...]
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*/
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private function embed(string $text): ?array
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{
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// 1) 优先使用独立 embeddings 接口
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if ($this->embeddingUrl !== '') {
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$payload = json_encode(['text' => $text], JSON_UNESCAPED_UNICODE);
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$ch = curl_init();
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curl_setopt($ch, CURLOPT_URL, $this->embeddingUrl);
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curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
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curl_setopt($ch, CURLOPT_TIMEOUT, $this->timeout);
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curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false);
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curl_setopt($ch, CURLOPT_POST, true);
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curl_setopt($ch, CURLOPT_POSTFIELDS, $payload);
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$headers = array_merge(['Content-Type: application/json'], $this->embeddingHeaders);
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curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
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$res = curl_exec($ch);
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curl_close($ch);
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if (!is_string($res) || trim($res) === '') return null;
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$decoded = json_decode($res, true);
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if (is_array($decoded)) {
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if (isset($decoded['data'][0]['embedding']) && is_array($decoded['data'][0]['embedding'])) {
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return $this->normalizeVector($decoded['data'][0]['embedding']);
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}
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if (isset($decoded['embedding']) && is_array($decoded['embedding'])) {
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return $this->normalizeVector($decoded['embedding']);
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}
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$isVec = isset($decoded[0]) && (is_float($decoded[0]) || is_int($decoded[0]));
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if ($isVec) return $this->normalizeVector($decoded);
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}
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return null;
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}
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// 2) 没有 embeddings 接口时，使用 chat/completions 生成固定维度向量
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if ($this->chatUrl === '' || $this->chatModel === '') {
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return null;
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}
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$sys = "You are an embedding generator. Output ONLY valid JSON in this exact shape: {\"embedding\":[...]}.\n"
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. "Rules:\n"
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. "- embedding must be an array of exactly {$this->embeddingDim} floats\n"
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. "- each float must be between -1 and 1\n"
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. "- do not include any other keys or any extra text\n";
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$payload = json_encode([
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'model' => $this->chatModel,
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'temperature' => 0,
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'max_tokens' => $this->chatMaxTokens,
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'messages' => [
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['role' => 'system', 'content' => $sys],
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['role' => 'user', 'content' => $text],
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],
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], JSON_UNESCAPED_UNICODE);
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$ch = curl_init();
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curl_setopt($ch, CURLOPT_URL, $this->chatUrl);
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curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
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curl_setopt($ch, CURLOPT_TIMEOUT, $this->timeout);
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curl_setopt($ch, CURLOPT_SSL_VERIFYPEER, false);
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curl_setopt($ch, CURLOPT_POST, true);
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curl_setopt($ch, CURLOPT_POSTFIELDS, $payload);
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$headers = array_merge(['Content-Type: application/json'], $this->embeddingHeaders);
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curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
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$res = curl_exec($ch);
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curl_close($ch);
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if (!is_string($res) || trim($res) === '') return null;
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$decoded = json_decode($res, true);
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$content = '';
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if (is_array($decoded) && isset($decoded['choices'][0]['message']['content'])) {
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$content = (string)$decoded['choices'][0]['message']['content'];
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}
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$content = trim($content);
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if ($content === '') return null;
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// content 可能被包裹在 ```json ... ```
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if (preg_match('/```(?:json)?\\s*([\\s\\S]*?)\\s*```/i', $content, $m)) {
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$content = trim($m[1]);
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}
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$j = json_decode($content, true);
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if (!is_array($j) || !isset($j['embedding']) || !is_array($j['embedding'])) {
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return null;
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}
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$vec = $j['embedding'];
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if (count($vec) !== $this->embeddingDim) {
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return null;
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}
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return $this->normalizeVector($vec);
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}
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private function cosine(array $a, array $b): float
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{
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$n = min(count($a), count($b));
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if ($n <= 0) return 0.0;
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$dot = 0.0; $na = 0.0; $nb = 0.0;
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for ($i = 0; $i < $n; $i++) {
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$x = (float)$a[$i];
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$y = (float)$b[$i];
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$dot += $x * $y;
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$na += $x * $x;
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$nb += $y * $y;
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}
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if ($na <= 0.0 || $nb <= 0.0) return 0.0;
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return $dot / (sqrt($na) * sqrt($nb));
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}
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private function normalizeVector(array $v): array
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{
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$sum = 0.0;
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$out = [];
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foreach ($v as $x) {
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$fx = (float)$x;
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$out[] = $fx;
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$sum += $fx * $fx;
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}
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if ($sum <= 0.0) return $out;
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$norm = sqrt($sum);
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for ($i = 0; $i < count($out); $i++) {
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$out[$i] = $out[$i] / $norm;
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}
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return $out;
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}
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private function extractDoiFromRefer(array $referRow): string
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{
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// 复用 CrossrefService 内部逻辑（通过 qcCitation 的抽取函数不可直接访问，所以这里简单实现）
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$doi = trim((string)($referRow['refer_doi'] ?? ''));
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if ($doi !== '') return $doi;
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$doilink = trim((string)($referRow['doilink'] ?? ''));
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if ($doilink === '') return '';
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if (preg_match('#doi\\.org/([^?#]+)#i', $doilink, $m)) {
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return trim((string)$m[1]);
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}
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return $doilink;
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}
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// ---------------- cache ----------------
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private function cacheDir(): string
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{
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return rtrim(ROOT_PATH, '/') . '/runtime/embed_cache';
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}
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private function cacheGet(string $key, int $ttlSeconds)
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{
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$file = $this->cacheDir() . '/' . $key . '.json';
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if (!is_file($file)) return null;
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$mtime = filemtime($file);
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if (!$mtime || (time() - $mtime) > $ttlSeconds) return null;
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$raw = @file_get_contents($file);
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$decoded = json_decode((string)$raw, true);
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return $decoded;
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}
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private function cacheSet(string $key, $value): void
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{
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$dir = $this->cacheDir();
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if (!is_dir($dir)) @mkdir($dir, 0777, true);
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$file = $dir . '/' . $key . '.json';
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@file_put_contents($file, json_encode($value, JSON_UNESCAPED_UNICODE));
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}
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}
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