9244899f9b
- Added tone instruction retrieval to SupportReplyService. - Improved user feedback when no relevant article is found. - Included article URL and tone instruction in LLM prompt. - Updated response format to include source information. - Enhanced article management UI with search functionality and editing capabilities. - Introduced a new API endpoint for nearest articles based on vector search. - Added confidence badge component to display article confidence levels. - Implemented tests for article searching, editing, and nearest article API. - Removed obsolete .htaccess file.
82 lines
3.1 KiB
PHP
82 lines
3.1 KiB
PHP
<?php
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namespace App\Http\Controllers\Api;
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use App\Exceptions\OllamaUnavailableException;
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use App\Http\Controllers\Controller;
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use App\Repositories\Contracts\ArticleRepositoryInterface;
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use App\Services\EmbeddingService;
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use Illuminate\Http\JsonResponse;
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use Illuminate\Http\Request;
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class NearestArticleController extends Controller
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{
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public function __invoke(
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Request $request,
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EmbeddingService $embeddingService,
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ArticleRepositoryInterface $articleRepository
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): JsonResponse {
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$validated = $request->validate([
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'query' => ['required', 'string', 'min:2', 'max:1000'],
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'limit' => ['sometimes', 'integer', 'min:1', 'max:20'],
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'min_similarity' => ['sometimes', 'numeric', 'min:0', 'max:1'],
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'include_content' => ['sometimes', 'boolean'],
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]);
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$query = trim($validated['query']);
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$limit = (int) ($validated['limit'] ?? 5);
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$minSimilarity = (float) ($validated['min_similarity'] ?? 0);
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$includeContent = $request->boolean('include_content', false);
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try {
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$embedding = $embeddingService->embed($query);
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} catch (OllamaUnavailableException $exception) {
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return response()->json([
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'message' => 'Embedding provider is unavailable.',
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'error' => $exception->getMessage(),
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], 503);
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}
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$embeddingContext = $embeddingService->context();
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$candidates = $articleRepository->findSimilarByEmbedding(
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embedding: $embedding,
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limit: $limit,
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embeddingContext: $embeddingContext,
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filters: ['published_only' => true]
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);
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$results = collect($candidates)
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->map(function ($candidate) use ($includeContent) {
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$similarity = max(0, min(1, 1 - $candidate->distance));
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$content = trim($candidate->content);
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return [
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'article_id' => $candidate->articleId,
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'title' => $candidate->title,
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'similarity' => round($similarity, 4),
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'distance' => round($candidate->distance, 4),
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'snippet' => str($content)->limit(220)->toString(),
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'content' => $includeContent ? $content : null,
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'source_url' => $candidate->sourceUrl,
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'source_article_id' => $candidate->sourceArticleId,
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'note' => $candidate->note,
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'allowed_actions' => $candidate->allowedActions,
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];
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})
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->filter(fn (array $result) => $result['similarity'] >= $minSimilarity)
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->values();
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return response()->json([
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'data' => $results,
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'meta' => [
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'query' => $query,
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'limit' => $limit,
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'min_similarity' => $minSimilarity,
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'published_only' => true,
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'embedding_provider_instance_id' => $embeddingContext['provider_instance_id'] ?? null,
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'embedding_model' => $embeddingContext['embedding_model'] ?? null,
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],
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]);
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}
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}
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