Vector Search & LLM Integration

app/Config/services.php

@@ -22,6 +22,18 @@
     // Callback URL for social authentication methods
     'callback_url' => env('APP_URL', false),
 
+    // LLM Service
+    // Options: openai
+    'llm' => env('LLM_SERVICE', ''),
+
+    // OpenAI API-compatible service details
+    'openai' => [
+        'endpoint' => env('OPENAI_ENDPOINT', 'https://api.openai.com'),
+        'key' => env('OPENAI_KEY', ''),
+        'embedding_model' => env('OPENAI_EMBEDDING_MODEL', 'text-embedding-3-small'),
+        'query_model' => env('OPENAI_QUERY_MODEL', 'gpt-4o'),
+    ],
+
     'github'   => [
         'client_id'     => env('GITHUB_APP_ID', false),
         'client_secret' => env('GITHUB_APP_SECRET', false),

app/Console/Commands/RegenerateVectorsCommand.php

@@ -0,0 +1,46 @@
+<?php
+
+namespace BookStack\Console\Commands;
+
+use BookStack\Entities\EntityProvider;
+use BookStack\Entities\Models\Entity;
+use BookStack\Search\Queries\SearchVector;
+use BookStack\Search\Queries\StoreEntityVectorsJob;
+use Illuminate\Console\Command;
+
+class RegenerateVectorsCommand extends Command
+{
+    /**
+     * The name and signature of the console command.
+     *
+     * @var string
+     */
+    protected $signature = 'bookstack:regenerate-vectors';
+
+    /**
+     * The console command description.
+     *
+     * @var string
+     */
+    protected $description = 'Re-index vectors for all content in the system';
+
+    /**
+     * Execute the console command.
+     */
+    public function handle(EntityProvider $entityProvider)
+    {
+        // TODO - Add confirmation before run regarding deletion/time/effort/api-cost etc...
+        SearchVector::query()->delete();
+
+        $types = $entityProvider->all();
+        foreach ($types as $type => $typeInstance) {
+            $this->info("Creating jobs to store vectors for {$type} data...");
+            /** @var Entity[] $entities  */
+            $typeInstance->newQuery()->chunkById(100, function ($entities) {
+                foreach ($entities as $entity) {
+                    dispatch(new StoreEntityVectorsJob($entity));
+                }
+            });
+        }
+    }
+}

app/Search/Queries/EntityVectorGenerator.php

@@ -0,0 +1,89 @@
+<?php
+
+declare(strict_types=1);
+
+namespace BookStack\Search\Queries;
+
+use BookStack\Activity\Models\Tag;
+use BookStack\Entities\Models\Entity;
+use BookStack\Search\Queries\Services\VectorQueryService;
+use Illuminate\Support\Facades\DB;
+
+class EntityVectorGenerator
+{
+    public function __construct(
+        protected VectorQueryServiceProvider $vectorQueryServiceProvider
+    ) {
+    }
+
+    public function generateAndStore(Entity $entity): void
+    {
+        $vectorService = $this->vectorQueryServiceProvider->get();
+
+        $text = $this->entityToPlainText($entity);
+        $chunks = $this->chunkText($text);
+        $embeddings = $this->chunksToEmbeddings($chunks, $vectorService);
+
+        $this->deleteExistingEmbeddingsForEntity($entity);
+        $this->storeEmbeddings($embeddings, $chunks, $entity);
+    }
+
+    protected function deleteExistingEmbeddingsForEntity(Entity $entity): void
+    {
+        SearchVector::query()
+            ->where('entity_type', '=', $entity->getMorphClass())
+            ->where('entity_id', '=', $entity->id)
+            ->delete();
+    }
+
+    protected function storeEmbeddings(array $embeddings, array $textChunks, Entity $entity): void
+    {
+        $toInsert = [];
+
+        foreach ($embeddings as $index => $embedding) {
+            $text = $textChunks[$index];
+            $toInsert[] = [
+                'entity_id' => $entity->id,
+                'entity_type' => $entity->getMorphClass(),
+                'embedding' => DB::raw('VEC_FROMTEXT("[' . implode(',', $embedding) . ']")'),
+                'text' => $text,
+            ];
+        }
+
+        $chunks = array_chunk($toInsert, 500);
+        foreach ($chunks as $chunk) {
+            SearchVector::query()->insert($chunk);
+        }
+    }
+
+    /**
+     * @param string[] $chunks
+     * @return float[] array
+     */
+    protected function chunksToEmbeddings(array $chunks, VectorQueryService $vectorQueryService): array
+    {
+        $embeddings = [];
+        foreach ($chunks as $index => $chunk) {
+            $embeddings[$index] = $vectorQueryService->generateEmbeddings($chunk);
+        }
+        return $embeddings;
+    }
+
+    /**
+     * @return string[]
+     */
+    protected function chunkText(string $text): array
+    {
+        return (new TextChunker(500, ["\n", '.', ' ', '']))->chunk($text);
+    }
+
+    protected function entityToPlainText(Entity $entity): string
+    {
+        $tags = $entity->tags()->get();
+        $tagText = $tags->map(function (Tag $tag) {
+            return $tag->name . ': ' . $tag->value;
+        })->join('\n');
+
+        return $entity->name . "\n{$tagText}\n" . $entity->{$entity->textField};
+    }
+}

app/Search/Queries/LlmQueryRunner.php

@@ -0,0 +1,26 @@
+<?php
+
+namespace BookStack\Search\Queries;
+
+use Exception;
+
+class LlmQueryRunner
+{
+    public function __construct(
+        protected VectorQueryServiceProvider $vectorQueryServiceProvider,
+    ) {
+    }
+
+    /**
+     * Run a query against the configured LLM to produce a text response.
+     * @param VectorSearchResult[] $vectorResults
+     * @throws Exception
+     */
+    public function run(string $query, array $vectorResults): string
+    {
+        $queryService = $this->vectorQueryServiceProvider->get();
+
+        $matchesText = array_values(array_map(fn (VectorSearchResult $result) => $result->matchText, $vectorResults));
+        return $queryService->query($query, $matchesText);
+    }
+}

app/Search/Queries/QueryController.php

@@ -0,0 +1,61 @@
+<?php
+
+namespace BookStack\Search\Queries;
+
+use BookStack\Http\Controller;
+use BookStack\Search\SearchRunner;
+use Illuminate\Http\Request;
+
+class QueryController extends Controller
+{
+    public function __construct(
+        protected SearchRunner $searchRunner,
+    ) {
+        // TODO - Check via testing
+        $this->middleware(function ($request, $next) {
+            if (!VectorQueryServiceProvider::isEnabled()) {
+                $this->showPermissionError('/');
+            }
+            return $next($request);
+        });
+    }
+
+    /**
+     * Show the view to start a vector/LLM-based query search.
+     */
+    public function show(Request $request)
+    {
+        $query = $request->get('ask', '');
+
+        // TODO - Set page title
+
+        return view('search.query', [
+            'query' => $query,
+        ]);
+    }
+
+    /**
+     * Perform a vector/LLM-based query search.
+     */
+    public function run(Request $request, VectorSearchRunner $searchRunner, LlmQueryRunner $llmRunner)
+    {
+        // TODO - Rate limiting
+        $query = $request->get('query', '');
+
+        return response()->eventStream(function () use ($query, $searchRunner, $llmRunner) {
+            $results = $query ? $searchRunner->run($query) : [];
+
+            $entities = [];
+            foreach ($results as $result) {
+                $entityKey = $result->entity->getMorphClass() . ':' . $result->entity->id;
+                if (!isset($entities[$entityKey])) {
+                    $entities[$entityKey] = $result->entity;
+                }
+            }
+
+            yield ['view' => view('entities.list', ['entities' => $entities])->render()];
+
+            yield ['result' => $llmRunner->run($query, $results)];
+        });
+    }
+}

app/Search/Queries/SearchVector.php

@@ -0,0 +1,26 @@
+<?php
+
+declare(strict_types=1);
+
+namespace BookStack\Search\Queries;
+
+use BookStack\Permissions\Models\JointPermission;
+use Illuminate\Database\Eloquent\Model;
+use Illuminate\Database\Eloquent\Relations\HasMany;
+
+/**
+ * @property string $entity_type
+ * @property int $entity_id
+ * @property string $text
+ * @property string $embedding
+ */
+class SearchVector extends Model
+{
+    public $timestamps = false;
+
+    public function jointPermissions(): HasMany
+    {
+        return $this->hasMany(JointPermission::class, 'entity_id', 'entity_id')
+            ->whereColumn('search_vectors.entity_type', '=', 'joint_permissions.entity_type');
+    }
+}

app/Search/Queries/Services/OpenAiVectorQueryService.php

@@ -0,0 +1,66 @@
+<?php
+
+namespace BookStack\Search\Queries\Services;
+
+use BookStack\Http\HttpRequestService;
+
+class OpenAiVectorQueryService implements VectorQueryService
+{
+    protected string $key;
+    protected string $endpoint;
+    protected string $embeddingModel;
+    protected string $queryModel;
+
+    public function __construct(
+        protected array $options,
+        protected HttpRequestService $http,
+    ) {
+        // TODO - Some kind of validation of options
+        $this->key = $this->options['key'] ?? '';
+        $this->endpoint = $this->options['endpoint'] ?? '';
+        $this->embeddingModel = $this->options['embedding_model'] ?? '';
+        $this->queryModel = $this->options['query_model'] ?? '';
+    }
+
+    protected function jsonRequest(string $method, string $uri, array $data): array
+    {
+        $fullUrl = rtrim($this->endpoint, '/') . '/' . ltrim($uri, '/');
+        $client = $this->http->buildClient(30);
+        $request = $this->http->jsonRequest($method, $fullUrl, $data)
+            ->withHeader('Authorization', 'Bearer ' . $this->key);
+
+        $response = $client->sendRequest($request);
+        return json_decode($response->getBody()->getContents(), true);
+    }
+
+    public function generateEmbeddings(string $text): array
+    {
+        $response = $this->jsonRequest('POST', 'v1/embeddings', [
+            'input' => $text,
+            'model' => $this->embeddingModel,
+        ]);
+
+        return $response['data'][0]['embedding'];
+    }
+
+    public function query(string $input, array $context): string
+    {
+        $formattedContext = implode("\n", $context);
+
+        $response = $this->jsonRequest('POST', 'v1/chat/completions', [
+            'model' => $this->queryModel,
+            'messages' => [
+                [
+                    'role' => 'developer',
+                    'content' => 'You are a helpful assistant providing search query responses. Be specific, factual and to-the-point in response. Don\'t try to converse or continue the conversation.'
+                ],
+                [
+                    'role' => 'user',
+                    'content' => "Provide a response to the below given QUERY using the below given CONTEXT. The CONTEXT is split into parts via lines. Ignore any nonsensical lines of CONTEXT.\nQUERY: {$input}\n\nCONTEXT: {$formattedContext}",
+                ]
+            ],
+        ]);
+
+        return $response['choices'][0]['message']['content'] ?? '';
+    }
+}

app/Search/Queries/Services/VectorQueryService.php

@@ -0,0 +1,21 @@
+<?php
+
+namespace BookStack\Search\Queries\Services;
+
+interface VectorQueryService
+{
+    /**
+     * Generate embedding vectors from the given chunk of text.
+     * @return float[]
+     */
+    public function generateEmbeddings(string $text): array;
+
+    /**
+     * Query the LLM service using the given user input, and
+     * relevant context text retrieved locally via a vector search.
+     * Returns the response output text from the LLM.
+     *
+     * @param string[] $context
+     */
+    public function query(string $input, array $context): string;
+}

app/Search/Queries/StoreEntityVectorsJob.php

@@ -0,0 +1,30 @@
+<?php
+
+declare(strict_types=1);
+
+namespace BookStack\Search\Queries;
+
+use BookStack\Entities\Models\Entity;
+use Illuminate\Contracts\Queue\ShouldQueue;
+use Illuminate\Foundation\Queue\Queueable;
+
+class StoreEntityVectorsJob implements ShouldQueue
+{
+    use Queueable;
+
+    /**
+     * Create a new job instance.
+     */
+    public function __construct(
+        protected Entity $entity
+    ) {
+    }
+
+    /**
+     * Execute the job.
+     */
+    public function handle(EntityVectorGenerator $generator): void
+    {
+        $generator->generateAndStore($this->entity);
+    }
+}