Files
dobetternorge-tools/api/corpus-search.php
T
daveadmin 5a0ef89dca feat(mcp): expose corpus_search, korrespond_refine, extract_text tools
Restores the 3 tools (manifest + invoke arms + invokeExtract helper),
the citation-atom RAG lever in LegalTools/corpus-search, and the catalog
icons. These were live on prod via rsync but uncommitted, so a git-pull
deploy reverted the manifest from 22 to 19 tools.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-01 16:45:41 +02:00

305 lines
14 KiB
PHP

<?php
declare(strict_types=1);
require_once __DIR__ . '/../includes/LegalTools.php';
dbnToolsRequireMethod('POST');
dbnToolsRequireAuth();
$input = dbnToolsJsonInput(4000);
$query = trim(dbnToolsString($input, 'query', 1000));
$rawMode = $input['mode'] ?? 'hybrid';
$mode = in_array($rawMode, ['hybrid', 'bm25', 'vector', 'azure'], true) ? $rawMode : 'hybrid';
$language = dbnToolsNormalizeLanguage($input['language'] ?? 'en');
$limit = max(1, min(20, (int)($input['limit'] ?? 8)));
$category = isset($input['category']) && $input['category'] !== '' ? trim((string)$input['category']) : null;
const EXCLUDED_DOMAIN = 'dobetternorge.no';
if (mb_strlen($query, 'UTF-8') < 3) {
dbnToolsError('Query must be at least 3 characters.', 422, 'query_too_short');
}
try {
// ── HYBRID: delegate to the existing RAG pipeline ──────────────────────
if ($mode === 'hybrid') {
$result = (new DbnLegalToolsService())->search($query, $language, $limit, 'disabled', null);
$hits = array_map(fn($h) => [
'title' => $h['title'] ?? '',
'category' => $h['category'] ?? '',
'section' => $h['section'] ?? null,
'excerpt' => $h['excerpt'] ?? ($h['chunk_text'] ?? ''),
'full_text' => $h['full_text'] ?? $h['chunk_text'] ?? $h['excerpt'] ?? '',
'score' => $h['score'] ?? null,
'document_id' => $h['document_id'] ?? null,
'chunk_id' => $h['chunk_id'] ?? null,
'source_url' => $h['source_url'] ?? null,
'language' => null,
], $result['hits'] ?? []);
$hits = array_values(array_filter($hits, fn($h) => !str_contains($h['source_url'] ?? '', EXCLUDED_DOMAIN)));
dbnToolsRespond(['ok' => true, 'hits' => $hits, 'mode' => 'hybrid', 'query' => $query]);
}
$ragDb = dbnToolsRagDb();
// ── BM25: FULLTEXT with LIKE fallback ───────────────────────────────────
if ($mode === 'bm25') {
$catClause = $category !== null ? ' AND d.category = ?' : '';
$excludeLike = '%' . EXCLUDED_DOMAIN . '%';
// Exact-identifier routing: the FULLTEXT tokenizer drops "§ 4-12" / "Art. 8"
// to stopword fragments, so a citation query never matches. Route those to a
// verbatim LIKE lookup and pin the hits ahead of the fuzzy BM25 results.
$exactHits = [];
$exactChunkIds = [];
$citationAtoms = DbnLegalToolsService::citationAtoms($query);
if (!empty($citationAtoms)) {
$atomClauses = [];
$atomParams = [1];
foreach ($citationAtoms as $atom) {
$like = '%' . str_replace(['%', '_'], ['\\%', '\\_'], $atom) . '%';
$atomClauses[] = '(c.content LIKE ? OR c.section_title LIKE ?)';
$atomParams[] = $like;
$atomParams[] = $like;
}
$atomParams[] = $excludeLike;
$exactSql = "SELECT d.id AS document_id, d.title, d.category,
d.source_url, c.id AS chunk_id, c.content AS excerpt,
c.section_title AS section, d.language, 1.0 AS score
FROM chunks c
JOIN documents d ON c.document_id = d.id
WHERE d.corpus_id = ? AND d.status = 'ready'
AND (" . implode(' OR ', $atomClauses) . ")
AND d.source_url NOT LIKE ?
$catClause
LIMIT $limit";
$exactParams = $atomParams;
if ($category !== null) $exactParams[] = $category;
try {
$stmt = $ragDb->prepare($exactSql);
$stmt->execute($exactParams);
foreach ($stmt->fetchAll(PDO::FETCH_ASSOC) as $r) {
$exactHits[] = $r;
if (isset($r['chunk_id'])) $exactChunkIds[(int)$r['chunk_id']] = true;
}
} catch (Throwable $e) {
// Non-fatal — fall through to fuzzy BM25.
}
}
// Try FULLTEXT index first
try {
$sql = "SELECT d.id AS document_id, d.title, d.category,
d.source_url, c.id AS chunk_id, c.content AS excerpt,
c.section_title AS section, d.language,
MATCH(c.content) AGAINST (? IN BOOLEAN MODE) AS score
FROM chunks c
JOIN documents d ON c.document_id = d.id
WHERE d.corpus_id = ? AND d.status = 'ready'
AND MATCH(c.content) AGAINST (? IN BOOLEAN MODE) > 0
AND d.source_url NOT LIKE ?
$catClause
ORDER BY score DESC
LIMIT $limit";
$params = [$query, 1, $query, $excludeLike];
if ($category !== null) $params[] = $category;
$stmt = $ragDb->prepare($sql);
$stmt->execute($params);
$rows = $stmt->fetchAll(PDO::FETCH_ASSOC);
} catch (Throwable $e) {
// FULLTEXT index absent — use LIKE
$like = '%' . str_replace(['%', '_'], ['\\%', '\\_'], $query) . '%';
$sql = "SELECT d.id AS document_id, d.title, d.category,
d.source_url, c.id AS chunk_id, c.content AS excerpt,
c.section_title AS section, d.language,
0.25 AS score
FROM chunks c
JOIN documents d ON c.document_id = d.id
WHERE d.corpus_id = ? AND d.status = 'ready'
AND (c.content LIKE ? OR d.title LIKE ?)
AND d.source_url NOT LIKE ?
$catClause
ORDER BY (d.title LIKE ?) DESC
LIMIT $limit";
$params = [1, $like, $like, $excludeLike];
if ($category !== null) $params[] = $category;
$params[] = $like;
$stmt = $ragDb->prepare($sql);
$stmt->execute($params);
$rows = $stmt->fetchAll(PDO::FETCH_ASSOC);
}
// Exact identifier hits lead; drop fuzzy rows that duplicate them.
if (!empty($exactChunkIds)) {
$rows = array_values(array_filter($rows, fn($r) => empty($exactChunkIds[(int)($r['chunk_id'] ?? 0)])));
}
$rows = array_slice(array_merge($exactHits, $rows), 0, $limit);
$hits = array_map(fn($r) => [
'title' => $r['title'] ?? '',
'category' => $r['category'] ?? '',
'section' => $r['section'] ?? null,
'excerpt' => mb_substr((string)($r['excerpt'] ?? ''), 0, 600, 'UTF-8'),
'full_text' => (string)($r['excerpt'] ?? ''),
'score' => isset($r['score']) ? round((float)$r['score'], 4) : null,
'document_id' => (int)$r['document_id'],
'chunk_id' => isset($r['chunk_id']) ? (int)$r['chunk_id'] : null,
'source_url' => $r['source_url'] ?? null,
'language' => $r['language'] ?? null,
'exact_match' => !empty($exactChunkIds[(int)($r['chunk_id'] ?? 0)]),
], $rows);
dbnToolsRespond(['ok' => true, 'hits' => $hits, 'mode' => 'bm25', 'query' => $query]);
}
// ── VECTOR: embed → Qdrant ─────────────────────────────────────────────
if ($mode === 'vector') {
$embeddings = dbnToolsLiteLLMEmbedBatch([$query]);
if (empty($embeddings) || !is_array($embeddings[0])) {
dbnToolsError('Embedding failed — vector search unavailable.', 502, 'embed_error');
}
$filter = ['must' => [['key' => 'corpus_id', 'match' => ['value' => 1]]]];
if ($category !== null) {
$filter['must'][] = ['key' => 'category', 'match' => ['value' => $category]];
}
$qdrantPayload = json_encode([
'vector' => $embeddings[0],
'limit' => $limit,
'with_payload' => true,
'filter' => $filter,
]);
$ch = curl_init('http://10.0.2.10:6333/collections/bnl_chunks/points/search');
curl_setopt_array($ch, [
CURLOPT_RETURNTRANSFER => true,
CURLOPT_POST => true,
CURLOPT_POSTFIELDS => $qdrantPayload,
CURLOPT_HTTPHEADER => ['Content-Type: application/json'],
CURLOPT_TIMEOUT => 15,
]);
$resp = curl_exec($ch);
$curlErr = curl_error($ch);
curl_close($ch);
if ($resp === false) {
dbnToolsError('Qdrant unreachable: ' . $curlErr, 502, 'qdrant_error');
}
$qdrantResult = json_decode($resp, true);
$points = $qdrantResult['result'] ?? [];
$hits = [];
foreach ($points as $pt) {
$p = $pt['payload'] ?? [];
$hits[] = [
'title' => $p['title'] ?? $p['document_title'] ?? '',
'category' => $p['category'] ?? '',
'section' => $p['section_title'] ?? null,
'excerpt' => mb_substr((string)($p['content'] ?? ''), 0, 600, 'UTF-8'),
'full_text' => (string)($p['content'] ?? ''),
'score' => round((float)($pt['score'] ?? 0), 4),
'document_id' => isset($p['document_id']) ? (int)$p['document_id'] : null,
'chunk_id' => $pt['id'] ?? null,
'source_url' => $p['source_url'] ?? null,
'language' => $p['language'] ?? null,
];
}
$hits = array_values(array_filter($hits, fn($h) => !str_contains($h['source_url'] ?? '', EXCLUDED_DOMAIN)));
dbnToolsRespond(['ok' => true, 'hits' => $hits, 'mode' => 'vector', 'query' => $query]);
}
// ── AZURE AI SEARCH: semantic + vector via Azure AI Search ────────────────
if ($mode === 'azure') {
$searchEndpoint = rtrim((string)dbnToolsEnv('DBN_AZURE_SEARCH_ENDPOINT', ''), '/');
$searchKey = (string)dbnToolsEnv('DBN_AZURE_SEARCH_KEY', '');
$searchIndex = (string)dbnToolsEnv('DBN_AZURE_SEARCH_INDEX', 'bnl-legal-v2');
if (!$searchEndpoint || !$searchKey) {
dbnToolsError('Azure AI Search is not configured on this server.', 503, 'azure_search_not_configured');
}
// Try to embed the query for hybrid (semantic + vector) search
$vector = null;
$embeddings = dbnToolsLiteLLMEmbedBatch([$query]);
if (!empty($embeddings) && is_array($embeddings[0])) {
$vector = $embeddings[0];
}
// Expanded keep-list: original 11 + government-policy, health-law,
// social-services, labour-law, immigration (unblocked after contamination cleanup)
$keepCats = [
'child-welfare', 'echr-case-law', 'child-abduction', 'legislation',
'anti-discrimination', 'legal', 'children-rights', 'family-law',
'civil-litigation', 'patient-rights', 'parliamentary',
'government-policy', 'health-law', 'social-services', 'labour-law', 'immigration',
];
$catFilter = implode(' or ', array_map(fn($c) => "category eq '$c'", $keepCats));
if ($category !== null) {
$catFilter = "category eq '$category'";
}
$payload = [
'search' => $query,
'top' => $limit,
'select' => 'id,chunk_id,content,title,section_title,category,source_url',
'queryType' => 'semantic',
'semanticConfiguration' => 'bnl-semantic',
'filter' => $catFilter,
];
if ($vector) {
$payload['vectorQueries'] = [[
'kind' => 'vector',
'vector' => $vector,
'fields' => 'content_vector',
'k' => $limit,
]];
}
$url = "$searchEndpoint/indexes/" . rawurlencode($searchIndex) . '/docs/search?api-version=2024-05-01-preview';
$ch = curl_init($url);
curl_setopt_array($ch, [
CURLOPT_POST => true,
CURLOPT_RETURNTRANSFER => true,
CURLOPT_TIMEOUT => 15,
CURLOPT_HTTPHEADER => ['Content-Type: application/json', "api-key: $searchKey"],
CURLOPT_POSTFIELDS => json_encode($payload, JSON_UNESCAPED_SLASHES),
]);
$resp = curl_exec($ch);
$code = (int)curl_getinfo($ch, CURLINFO_RESPONSE_CODE);
$curlErr = curl_error($ch);
curl_close($ch);
if ($curlErr) dbnToolsError("Azure Search unreachable: $curlErr", 502, 'azure_search_error');
if ($code !== 200) {
$errBody = json_decode((string)$resp, true);
$errMsg = $errBody['error']['message'] ?? "HTTP $code";
dbnToolsError("Azure AI Search error: $errMsg", 502, 'azure_search_error');
}
$data = json_decode((string)$resp, true);
$hits = array_map(fn($d) => [
'title' => trim(implode(' — ', array_filter([$d['title'] ?? '', $d['section_title'] ?? '']))),
'category' => $d['category'] ?? '',
'section' => $d['section_title'] ?? null,
'excerpt' => mb_substr((string)($d['content'] ?? ''), 0, 600, 'UTF-8'),
'full_text' => (string)($d['content'] ?? ''),
'score' => round((float)($d['@search.rerankerScore'] ?? $d['@search.score'] ?? 0), 4),
'document_id' => null,
'chunk_id' => $d['chunk_id'] ?? $d['id'] ?? null,
'source_url' => $d['source_url'] ?? null,
'language' => null,
], $data['value'] ?? []);
$hits = array_values(array_filter($hits, fn($h) => !str_contains($h['source_url'] ?? '', EXCLUDED_DOMAIN)));
dbnToolsRespond(['ok' => true, 'hits' => $hits, 'mode' => 'azure', 'query' => $query]);
}
dbnToolsError('Unknown search mode.', 422, 'invalid_mode');
} catch (DbnToolsHttpException $e) {
throw $e;
} catch (Throwable $e) {
dbnToolsError('Corpus search failed: ' . $e->getMessage(), 500, 'search_error');
}