feat: replace Mistral web_search with Tavily for specs research

- Add WebSearchInterface + TavilyWebSearch (POST /search, max 5 results)
- SpecsResearchAgent now fetches search results first, injects them as
  {{searchResults}} context into the prompt, then calls plain generate()
  — no dependency on model-specific web_search tool support
- Update specs_research prompt template (PHP default + DB migration) to
  use the new {{searchResults}} variable
- Wire TAVILY_API_KEY env var; register TavilyWebSearch in services.yaml

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.env

@@ -16,6 +16,8 @@ OLLAMA_BASE_URL=http://172.18.0.1:11434
 OLLAMA_VISION_MODEL=llava
 OLLAMA_TEXT_MODEL=llama3.2
 
+TAVILY_API_KEY=
+
 MISTRAL_BASE_URL=https://api.mistral.ai
 MISTRAL_API_KEY=
 # Vision requires a Pixtral model, e.g. pixtral-12b-2409

config/services.yaml

@@ -82,6 +82,13 @@ services:
         arguments:
             $model: '%env(AI_TEXT_MODEL)%'
 
+    App\Infrastructure\Search\WebSearchInterface:
+        alias: App\Infrastructure\Search\TavilyWebSearch
+
+    App\Infrastructure\Search\TavilyWebSearch:
+        arguments:
+            $apiKey: '%env(TAVILY_API_KEY)%'
+
     App\Infrastructure\AI\Agent\JsonCodingAgent:
         arguments:
             $model: '%env(AI_TEXT_MODEL)%'

migrations/Version20260520020000.php

@@ -0,0 +1,51 @@
+<?php
+
+declare(strict_types=1);
+
+namespace DoctrineMigrations;
+
+use Doctrine\DBAL\Schema\Schema;
+use Doctrine\Migrations\AbstractMigration;
+
+final class Version20260520020000 extends AbstractMigration
+{
+    public function getDescription(): string
+    {
+        return 'Update specs_research prompt to include {{searchResults}} from Tavily';
+    }
+
+    public function up(Schema $schema): void
+    {
+        $body = <<<'PROMPT'
+You are a hardware specifications expert. Extract the technical specifications for the {{articleType}}: "{{subject}}".
+
+Web search results:
+{{searchResults}}
+
+Based on the search results above, list all technical specifications including:
+processor, RAM, storage variants, display size and resolution, GPU, battery capacity,
+ports, connectivity, weight, dimensions, OS, and any other relevant specs.
+Be specific and accurate. If a spec is not found in the search results, omit it rather than guessing.
+PROMPT;
+
+        $this->addSql(
+            "UPDATE app.prompt_templates SET body = :body WHERE key = 'specs_research'",
+            ['body' => $body],
+        );
+    }
+
+    public function down(Schema $schema): void
+    {
+        $body = <<<'PROMPT'
+List all known technical specifications for the {{articleType}}: "{{subject}}".
+Include: processor, RAM, storage variants, display size and resolution, GPU, battery capacity,
+ports, connectivity, weight, dimensions, OS, and any other relevant specs.
+If you know this device, be specific and complete. If it is unknown, say so explicitly.
+PROMPT;
+
+        $this->addSql(
+            "UPDATE app.prompt_templates SET body = :body WHERE key = 'specs_research'",
+            ['body' => $body],
+        );
+    }
+}

src/Infrastructure/AI/Agent/SpecsResearchAgent.php

@@ -6,12 +6,14 @@ namespace App\Infrastructure\AI\Agent;
 
 use App\Infrastructure\AI\OllamaClientInterface;
 use App\Infrastructure\AI\PromptTemplateService;
+use App\Infrastructure\Search\WebSearchInterface;
 
 final class SpecsResearchAgent
 {
     public function __construct(
         private readonly OllamaClientInterface $client,
         private readonly PromptTemplateService $prompts,
+        private readonly WebSearchInterface $search,
         private readonly string $model,
     ) {
     }
@@ -20,12 +22,15 @@ final class SpecsResearchAgent
     {
         $subject = trim(($manufacturer !== '' ? $manufacturer.' ' : '').$modelName);
 
+        $searchResults = $this->search->search("{$subject} {$articleTypeName} specifications");
+
         $prompt = $this->prompts->render('specs_research', [
             'articleType' => $articleTypeName,
             'subject' => $subject,
+            'searchResults' => $searchResults !== '' ? $searchResults : 'No web results available.',
         ]);
 
-        $result = $this->client->generateWithWebSearch($this->model, $prompt);
+        $result = $this->client->generate($this->model, $prompt);
 
         if ('' === trim($result)) {
             throw new \RuntimeException("No specifications found for model: {$modelName}");

src/Infrastructure/AI/PromptTemplateService.php

@@ -11,10 +11,15 @@ final class PromptTemplateService
     /** @var array<string, string> */
     private const array DEFAULTS = [
         'specs_research' => <<<'PROMPT'
-List all known technical specifications for the {{articleType}}: "{{subject}}".
-Include: processor, RAM, storage variants, display size and resolution, GPU, battery capacity,
+You are a hardware specifications expert. Extract the technical specifications for the {{articleType}}: "{{subject}}".
+
+Web search results:
+{{searchResults}}
+
+Based on the search results above, list all technical specifications including:
+processor, RAM, storage variants, display size and resolution, GPU, battery capacity,
 ports, connectivity, weight, dimensions, OS, and any other relevant specs.
-If you know this device, be specific and complete. If it is unknown, say so explicitly.
+Be specific and accurate. If a spec is not found in the search results, omit it rather than guessing.
 PROMPT,
 
         'ebay_title' => <<<'PROMPT'
@@ -89,7 +94,7 @@ PROMPT,
     public static function knownKeys(): array
     {
         return [
-            'specs_research' => ['articleType', 'subject'],
+            'specs_research' => ['articleType', 'subject', 'searchResults'],
             'ebay_title' => ['typeName', 'deviceLabel', 'condition', 'specsSection'],
             'ebay_description' => ['typeName', 'deviceLabel', 'condition', 'conditionNotes', 'specsSection'],
             'vision_analyze' => [],

src/Infrastructure/Search/TavilyWebSearch.php

@@ -0,0 +1,45 @@
+<?php
+
+declare(strict_types=1);
+
+namespace App\Infrastructure\Search;
+
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+
+final class TavilyWebSearch implements WebSearchInterface
+{
+    private const string API_URL = 'https://api.tavily.com/search';
+
+    public function __construct(
+        private readonly HttpClientInterface $httpClient,
+        private readonly string $apiKey,
+    ) {
+    }
+
+    public function search(string $query): string
+    {
+        $response = $this->httpClient->request('POST', self::API_URL, [
+            'json' => [
+                'api_key' => $this->apiKey,
+                'query' => $query,
+                'max_results' => 5,
+                'include_raw_content' => false,
+            ],
+            'timeout' => 30,
+        ]);
+
+        /** @var array{results: list<array{title: string, url: string, content: string}>} $data */
+        $data = $response->toArray();
+
+        if (empty($data['results'])) {
+            return '';
+        }
+
+        $parts = [];
+        foreach ($data['results'] as $result) {
+            $parts[] = "### {$result['title']}\n{$result['content']}";
+        }
+
+        return implode("\n\n", $parts);
+    }
+}

src/Infrastructure/Search/WebSearchInterface.php

@@ -0,0 +1,13 @@
+<?php
+
+declare(strict_types=1);
+
+namespace App\Infrastructure\Search;
+
+interface WebSearchInterface
+{
+    /**
+     * Run a web search and return the results as plain text suitable for use as AI context.
+     */
+    public function search(string $query): string;
+}