My Observer RAG Chat Assistant For WooCommerce
| 开发者 | DarrisB |
|---|---|
| 更新时间 | 2026年7月29日 20:23 |
| PHP版本: | 8.2 及以上 |
| WordPress版本: | 7.0 |
| 版权: | GPLv2 or later |
| 版权网址: | 版权信息 |
详情介绍:
My Observer RAG Chat Assistant adds an AI-powered product assistant to your WooCommerce store using Retrieval-Augmented Generation (RAG).
The plugin builds a local product knowledge index from your catalog content and can also ingest supporting business documents through the Product Intelligence Engine. Linked document knowledge is searched alongside WooCommerce product data so shopper responses can use richer store context. You control provider settings, indexing, document uploads, and widget placement directly in WordPress.
This plugin is designed for merchants who want:
- Product-aware chat that can reference your catalog content
- Optional document-aware retrieval linked to WooCommerce products
- A simple setup flow inside wp-admin
- Local vector indexing for retrieval workflows
- Flexibility to use OpenAI or Claude-based configurations How it works at a high level:
- Product data is indexed from your WooCommerce catalog.
- Optional TXT, CSV, DOCX, and text-based PDF files can be uploaded into the Product Intelligence Engine.
- User questions are matched against relevant product and document context.
- Your configured LLM provider generates the final response using retrieved context. The storefront chat widget can be embedded with shortcode or auto-injected in the footer, and the admin experience includes a modern Angular-based settings UI for runtime configuration and document management.
安装:
- Upload the plugin folder to
/wp-content/plugins/. - Activate the plugin in WordPress.
- Confirm WooCommerce is installed and active.
- Go to
My Observer > Settings. - Configure provider credentials:
OpenAI API Key, orClaude API KeyplusClaude Embeddings URLfor Claude-compatible embeddings.- Save settings in the Angular admin UI.
- Optionally upload knowledge documents in the Product Intelligence Engine section.
- Add shortcode
[myobserver_rag_widget]to a page, or enable auto inject.
屏幕截图:
常见问题:
Does this plugin require WooCommerce?
Yes. WooCommerce must be installed and active.
Can I place the chat widget manually?
Yes. Use [myobserver_rag_widget] (or legacy [rag_bot_widget]) in any page, post, or block shortcode element.
Is product indexing automatic?
You can run indexing manually from My Observer > Settings using the "Index All Products" action.
Can I upload documents to improve retrieval?
Yes. The Product Intelligence Engine lets you upload TXT, CSV, DOCX, and text-based PDF files, review them in the admin queue, and link them to WooCommerce products.
Does this plugin include payment or subscription checkout by itself?
Core storefront assistant functionality is in this plugin. Optional advanced add-ons are provided separately. = Do I need to reindex after editing a product? Usually no for normal edits, because updates are queued automatically via cron. Use manual reindex if cron is disabled, delayed, or after large imports/migrations.
Does this plugin require an external vector database?
No. It uses a high-performance, file-based embedded vector database written in native PHP, separate from your MySQL database.
更新日志:
2.0.0
- Added the new Angular-powered admin settings experience for
My Observer > Settings. - Added the Product Intelligence Engine for document uploads, document-to-product linking, queue review, and document reindex actions.
- Extended retrieval so uploaded document knowledge can be searched alongside WooCommerce product context.
- Added PDF text extraction support for text-based PDFs during document ingest.
- Improved WordPress admin runtime loading and nonce/config bootstrapping for the new settings UI.
- Cleaned plugin packaging and install structure for WordPress upload/activation compatibility.
- Added built-in diagnostics views for index health, retrieval testing, and live product/document vector reporting.
- Improved the document library UI with queue-style browsing, document totals, inline status messaging, and modal-based linked product review.
- Added document delete actions with automatic vector-store compaction so document counts and storage feedback update more reliably after cleanup.
- Improved full product reindex behavior to rebuild cleanly, compact the local vector store, and report more accurate live index counts.
- Added page-aware storefront chat context so retrieval can prefer the current product, listing, search, cart, or checkout context when relevant.
- Improved local widget and settings UX with better overflow handling, right-aligned save actions, overlay diagnostics results, and immediate readiness updates after saving API credentials.
- Hardened API key handling so saved keys are not returned to the enhanced UI or printed into fallback settings fields.
- Changed the shipped extension manifest to an empty tabs list so production installs do not expose premium placeholder tabs by default.
- Initial public release.