Geweb

Live demo: https://aisearch.mygeweb.com/
Geweb AI Search transforms your WordPress search into an intelligent assistant powered by Google Gemini AI. Instead of returning a plain list of matching posts, it understands the user’s question and provides a direct, contextual answer — along with links to the source pages.
The plugin intercepts the standard WordPress search form and opens a modal with two modes: instant autocomplete suggestions (via WP_Query) and a full AI chat powered by Google Gemini File Search.
<h4>Key Features</h4>
<ul>
<li>AI-Powered Answers — Uses Google Gemini File Search to find relevant content and generate natural-language answers</li>
<li>Conversation History — Users can ask follow-up questions; the context is maintained across the session</li>
<li>Source Attribution — Every AI answer includes links to the pages it was based on</li>
<li>Instant Autocomplete — Traditional keyword search with live suggestions while typing</li>
<li>Automatic Indexing — Posts are automatically uploaded to Gemini when published or updated</li>
<li>Bulk Library Generation — Index all existing content with one click and a live progress indicator</li>
<li>Multiple AI Models — Choose between Gemini 2.5 Flash, 2.5 Pro, and Gemini 3 models</li>
<li>Multiple Post Types — Index any public post type: posts, pages, or custom post types</li>
<li>Secure API Key Storage — API key is encrypted with libsodium before being stored in the database</li>
</ul>
<h4>How It Works</h4>
<ol>
<li>The plugin converts your WordPress posts to Markdown format (with URL and title in frontmatter)</li>
<li>Each document is uploaded to a Google Gemini File Search Store</li>
<li>When a user submits a search query, Gemini searches the indexed documents and generates an answer</li>
<li>The answer is displayed in a chat modal along with source links</li>
</ol>
<h4>Third-Party Services</h4>
This plugin connects to the Google Gemini API to index your content and answer user queries.
<ul>
<li>API endpoint: https://generativelanguage.googleapis.com/</li>
<li>Terms of Service: https://ai.google.dev/gemini-api/terms</li>
<li>Privacy Policy: https://policies.google.com/privacy</li>
</ul>
Data sent to Google:
<ul>
<li>Your post content (title and body), converted to Markdown, is uploaded to Gemini for indexing</li>
<li>User search queries are sent to Gemini to generate answers</li>
</ul>
By using this plugin you agree to Google’s Terms of Service and Privacy Policy. You are responsible for the content you index.
<h4>Requirements</h4>
<ul>
<li>PHP 7.2 or higher (libsodium is bundled with PHP 7.2+)</li>
<li>WordPress 6.0 or higher</li>
<li>Google Gemini API key (free tier available at https://aistudio.google.com/app/apikey)</li>
</ul>
<h3>Customization</h3>
<h4>How do I customize the AI behavior?</h4>
You can modify the AI system instruction and available models:
<pre><code>// Customize AI system instruction
add_filter('geweb_aisearch_gemini_system_instruction', function($instruction) {
 return $instruction . "\nAlways respond in a friendly, conversational tone.";
});

// Limit available models in settings
add_filter('geweb_aisearch_gemini_models', function($models) {
 return ['gemini-2.5-flash', 'gemini-2.5-pro'];
});
</code></pre>
Available filters: 
* <code>geweb_aisearch_gemini_system_instruction</code> – Modify AI prompt/behavior 
* <code>geweb_aisearch_gemini_models</code> – Customize available model list in settings
<h4>How do I translate the interface texts?</h4>
You can customize all search interface labels using filters in your theme’s functions.php:
<pre><code>// Customize search placeholder
add_filter('geweb_aisearch_search_placeholder', function($text) {
 return 'What would you like to know?';
});

// Customize "Ask AI" button text
add_filter('geweb_aisearch_ask_ai_button_text', function($text) {
 return 'Ask Pythia';
});

// Customize AI modal title
add_filter('geweb_aisearch_ai_modal_title', function($text) {
 return 'Oracle Pythia';
});

// Customize AI textarea placeholder
add_filter('geweb_aisearch_ai_textarea_placeholder', function($text) {
 return 'Write your detailed question to Pythia';
});
</code></pre>
Available filters: 
* <code>geweb_aisearch_search_placeholder</code> – Main search input placeholder 
* <code>geweb_aisearch_ask_ai_button_text</code> – “Ask AI” button label 
* <code>geweb_aisearch_ai_modal_title</code> – AI chat modal header 
* <code>geweb_aisearch_ai_textarea_placeholder</code> – AI question textarea placeholder
<h3>Third-Party Libraries</h3>
This plugin bundles the following open-source library:
league/html-to-markdown 
* Version: 5.x 
* Author: The League of Extraordinary Packages 
* License: MIT License 
* Repository: https://github.com/thephpleague/html-to-markdown 
* Purpose: Converts WordPress post HTML content to Markdown for AI indexing
<h3>Support</h3>
<ul>
<li>GitHub: https://github.com/mygeweb/geweb-ai-search</li>
</ul>

Geweb AI Search

AI-powered search for WordPress using Google Gemini. Smart answers, source links, and instant autocomplete — all in one modal.

Alessandro Lioce

Creator Assistant Hub is the core infrastructure plugin of the Creator Assistant ecosystem. It connects your WordPress site to OpenAI and Qdrant to automatically generate and store vector embeddings for your content, enabling semantic search and AI-powered features.
How it works
The Hub is the shared infrastructure layer for the Creator Assistant ecosystem. When a compatible add-on is active and activates a vectorizer, the plugin generates vector embeddings via the OpenAI API and stores them in your Qdrant vector database cluster whenever a post is published or updated. This makes your content available for semantic search and retrieval by Creator Assistant add-ons. Without an active add-on, the Hub runs in standby mode — no content is sent to external services.
Key features
<ul>
<li>Automatic post vectorization — when an add-on activates a vectorizer, embeddings are generated and stored whenever a post is published or updated. Without an active add-on, no vectorization takes place.</li>
<li>Chunk-based vectorization — splits post content into word-level segments and stores each chunk as a separate Qdrant point, enabling fine-grained retrieval (activated by add-ons via filter).</li>
<li>Summary-based vectorization — generates a short AI summary of each post via OpenAI Chat Completions, then embeds and stores a single point per post for high-level semantic search (activated by add-ons via filter).</li>
<li>Background batch vectorization — an hourly cron job automatically picks up any existing posts that have not yet been vectorized, so your entire content library is indexed without manual intervention.</li>
<li>OpenAI integration — uses the <code>text-embedding-3-small</code> model (1536 dimensions) via the OpenAI Embeddings API for all vectorizers; the Summary vectorizer additionally calls the OpenAI Chat Completions API (<code>gpt-4.1-nano</code>) to generate post summaries.</li>
<li>Qdrant integration — stores and retrieves vector embeddings from your Qdrant Cloud cluster. Two collections are used: <code>post_chunk</code> for chunk-level points and <code>post_summary</code> for post-level summary points.</li>
<li>Block editor panel — shows the vectorization status of each post directly in the block editor sidebar (document settings panel).</li>
<li>Post list column — adds a “Vector Status” column to the posts and pages admin list, showing the vectorization status of each entry at a glance.</li>
<li>Settings page — configure OpenAI API key, Qdrant endpoint and API key, and cache expiration from a dedicated admin page.</li>
<li>API response caching — configurable cache duration to reduce API usage and latency.</li>
<li>Site Health check — reports the Hub service status in the WordPress Site Health screen.</li>
<li>Qdrant keep-alive — sends a daily lightweight ping to prevent free-tier Qdrant Cloud clusters from being suspended.</li>
<li>WPML compatible — detects the post language via WPML hooks (when WPML is active) and includes it in the Qdrant payload for multilingual filtering.</li>
<li>Extensible — exposes actions and filters so add-ons can register additional post types, override vectorizer behaviour, customise Qdrant payloads, and add settings tabs.</li>
</ul>
Requirements
<ul>
<li>An <a href="https://platform.openai.com/" rel="nofollow ugc">OpenAI</a> account with a valid API key.</li>
<li>A <a href="https://cloud.qdrant.io/" rel="nofollow ugc">Qdrant Cloud</a> account with an active cluster (free tier is supported).</li>
<li>WordPress 6.6 or higher.</li>
<li>PHP 7.4 or higher.</li>
</ul>
External services
This plugin connects to two third-party services. By using this plugin you agree to their respective terms and privacy policies.
<ul>
<li>
OpenAI — used to generate vector embeddings from your post content via the Embeddings API. When the Summary vectorizer is active (enabled by an add-on), post content is also sent to the Chat Completions API to generate a short AI summary before embedding.
<ul>
<li>Service: <a href="https://platform.openai.com/" rel="nofollow ugc">https://platform.openai.com/</a></li>
<li>Privacy Policy: <a href="https://openai.com/policies/privacy-policy" rel="nofollow ugc">https://openai.com/policies/privacy-policy</a></li>
<li>Terms of Use: <a href="https://openai.com/policies/terms-of-use" rel="nofollow ugc">https://openai.com/policies/terms-of-use</a></li>
</ul>
</li>
<li>
Qdrant Cloud — used to store and query vector embeddings.
<ul>
<li>Service: <a href="https://cloud.qdrant.io/" rel="nofollow ugc">https://cloud.qdrant.io/</a></li>
<li>Privacy Policy: <a href="https://qdrant.tech/legal/privacy-policy/" rel="nofollow ugc">https://qdrant.tech/legal/privacy-policy/</a></li>
<li>Terms of Service: <a href="https://qdrant.tech/legal/terms_and_conditions/" rel="nofollow ugc">https://qdrant.tech/legal/terms_and_conditions/</a></li>
</ul>
</li>
</ul>
Data is only transmitted to these services after you explicitly accept the Creator Assistant Terms of Service in the plugin settings and provide your own API credentials. No data is transmitted automatically upon activation.

Creator Assistant Hub

The AI infrastructure for your WordPress content. Vectorize posts with OpenAI embeddings and store them in Qdrant for semantic search.

Geweb AI Search vs Creator Assistant Hub