Page Content Extractor

Page Content Extractor is a WordPress plugin built to manage a set of service pages that follow slug conventions and include geographic variations. Instead of opening and editing each page by hand, the administrator enters a slug pattern and a text fragment or image name, and the plugin identifies the relevant pages and extracts the locality from the slug for the subsequent operations.

The text flow detects the editor used by each page — Elementor, Gutenberg, or the classic editor — and searches the content through a word-by-word normalization that removes differences in HTML, spacing, and capitalization. The algorithm also recognizes {{locality}}-style placeholders, and for Gutenberg it recursively walks the blocks. Matching pages are presented as cards in the admin, together with the editor type and the extracted locality.

For AI-assisted localization, the plugin sends the text to Gemini 2.0 Flash and asks for a rewrite that preserves meaning, introduces natural references to the locality, and limited HTML markup for emphasis. Suggestions can be generated individually or in batch; the interface processes batches of 10 pages and shows progress, and each suggestion can be applied separately or in bulk.

Applying content is editor-aware. For Elementor, the plugin reads _elementor_data, recursively traverses the elements, and saves the modified JSON to post meta, then clears the Elementor cache. For Gutenberg, it parses the blocks, modifies the blocks that contain the text, and serializes the structure back into post_content. For the classic editor it uses direct replacement in post_content. The snapshot does not implement transactions or explicit rollback, and the match-replacement logic can substitute the entire field/block in which the phrase was found, which is why destructive operations are preceded in the UI by confirmations.

The image flow searches for pages that use a given file and offers two strategies: traversing the editor structure or a direct database mode, introduced as a lower-memory-footprint variant. The DB mode searches post_content and _elementor_data, identifies the URL and attachment ID, then displays for each page the current image alongside a preview area for a new image.

Image generation uses Vertex AI Imagen 3. The plugin builds a JWT from the configured service account, obtains a Google OAuth access token, calls the Vertex AI endpoint, decodes the Base64 image, and saves it to the WordPress Media Library. PNG responses are converted to JPG via GD. The file name includes the locality and a timestamp, and the resulting image can be applied individually or in batch.

Replacing images updates both post_content and the Elementor data, including URLs and attachment IDs. The code includes several fallbacks for Gutenberg/media-text structures and a direct path via wpdb when the standard update doesn't produce the expected result. After changes, the plugin invalidates the post cache, the Elementor cache, and can clear caches for WP Super Cache, W3 Total Cache, WP Rocket, Autoptimize, and LiteSpeed.

The snapshot also keeps diagnostic tools for block structure, memory usage, and logs. There is also legacy or incomplete code: the shortcode file is not loaded by the bootstrap, a few old JavaScript handlers have no active PHP endpoints, and the Google Cloud library declared in Composer is unused because the autoloader is commented out. The repository does not contain automated tests, CI/CD workflows, or deploy configuration.

From a hardening perspective, the analyzed version would benefit from current_user_can checks on all destructive/AI AJAX endpoints, strict sanitization of the HTML returned by the model before preview and persistence, moving sensitive credentials out of wp_options into a secure secret store/config, and disabling debug being enabled by default. debug.log is included in the snapshot and contains information about the local environment, although no API keys, Bearer tokens, or private keys were identified in the analyzed file.