Muhammad Adnan Hanif

<p>Fast RAGbot is an intelligent chatbot that uses Retrieval-Augmented Generation (RAG) with support for multiple AI providers to provide accurate answers based exclusively on your website content.</p>
<p><strong>Key Features:</strong></p>
<ul>
<li><strong>Multi-LLM Support</strong>: Choose between Gemini, OpenAI (ChatGPT), or Claude</li>
<li><strong>Multi-Domain Indexing</strong>: Index up to 3 different domains</li>
<li><strong>Document Upload</strong>: Bulk upload PDF, DOCX, PPTX, XLSX, TXT, XML, CSV</li>
<li><strong>Conversation Memory</strong>: Maintains last 5 Q&A turns per session</li>
<li><strong>Smart Follow-ups</strong>: Suggests questions when answer not found</li>
<li><strong>Widget Customization</strong>: Custom colors, logo, position, theme CSS</li>
<li><strong>Pre-chat Form</strong>: Optional name/email collection</li>
<li><strong>Chat Logs</strong>: Full conversation logging with CSV export</li>
<li><strong>Shortcode Support</strong>: Embed chat anywhere with <code>[ragbot_chat]</code></li>
<li><strong>Grounded Responses</strong>: Answers only from your content – no hallucinations</li>
<li><strong>Source Citations</strong>: Provides URLs of source pages for transparency</li>
<li><strong>Mobile Responsive</strong>: Works perfectly on all devices</li>
<li><strong>Security First</strong>: Rate limiting, nonces, and proper sanitization</li>
</ul>
<p><strong>How It Works:</strong></p>
<ol>
<li>Crawls and indexes your website content</li>
<li>Creates semantic embeddings using Google Gemini</li>
<li>Retrieves relevant content based on user questions</li>
<li>Generates contextual answers with source citations</li>
<li>Displays responses in a floating chat widget</li>
</ol>
<p><strong>Perfect For:</strong></p>
<ul>
<li>Customer support automation</li>
<li>FAQ assistance</li>
<li>Product information queries</li>
<li>Company information lookup</li>
<li>Documentation assistance</li>
</ul>
<h3>External Services & Data Usage</h3>
<p>This plugin connects to external AI services to provide chatbot functionality. Below is a detailed explanation of what data is transmitted and how it is used.</p>
<h4>External Services Used</h4>
<p><strong>Google Gemini API</strong> (https://ai.google.dev/)<br />
* Used for: Text embeddings and AI text generation<br />
* Data sent: User questions, website content chunks, conversation history<br />
* Privacy Policy: https://policies.google.com/privacy<br />
* Terms of Service: https://policies.google.com/terms</p>
<p><strong>OpenAI API</strong> (https://openai.com/) – Optional<br />
* Used for: Text embeddings and AI text generation (when selected as active model)<br />
* Data sent: User questions, website content chunks, conversation history<br />
* Privacy Policy: https://openai.com/privacy/<br />
* Terms of Service: https://openai.com/terms/</p>
<p><strong>Claude API by Anthropic</strong> (https://anthropic.com/) – Optional<br />
* Used for: Text embeddings and AI text generation (when selected as active model)<br />
* Data sent: User questions, website content chunks, conversation history<br />
* Privacy Policy: https://www.anthropic.com/privacy<br />
* Terms of Service: https://www.anthropic.com/legal/terms</p>
<h4>What Data Is Transmitted</h4>
<ol>
<li><strong>User’s Question</strong>: The text message submitted by the website visitor</li>
<li><strong>Retrieved Document Chunks</strong>: Relevant excerpts from your indexed website content (typically 5-8 chunks of ~1000 characters each)</li>
<li><strong>Conversation History</strong>: Last 5 question-answer pairs from the current session</li>
<li><strong>Model Parameters</strong>: Temperature (0.1), max tokens (1000), and other generation settings</li>
</ol>
<h4>Data Usage & Storage</h4>
<ul>
<li>Data is transmitted <strong>only</strong> for generating responses to user questions</li>
<li><strong>No data is stored or used for training</strong> by external AI providers (per their API terms)</li>
<li>Data transmission occurs in real-time and is not cached by the plugin on external servers</li>
<li>All API communications use HTTPS encryption</li>
</ul>
<h4>Local WordPress Storage</h4>
<p>The plugin stores the following data in your WordPress database:</p>
<p><strong>Options (wp_options table)</strong>:<br />
* <code>ragbot_settings</code> – Plugin configuration including API keys, widget settings, and preferences</p>
<p><strong>Custom Tables</strong>:<br />
* <code>wp_rag_docs</code> – Indexed website pages and uploaded documents<br />
* <code>wp_rag_chunks</code> – Text chunks created from indexed content<br />
* <code>wp_rag_embeddings</code> – Vector embeddings for semantic search<br />
* <code>wp_rag_sources</code> – Content source configurations (domains, settings)<br />
* <code>wp_rag_logs</code> – Chat conversation logs (optional, includes user name/email if pre-chat form enabled)<br />
* <code>wp_rag_url_queue</code> – Queue of URLs pending indexing</p>
<p><strong>Session Data</strong>:<br />
* PHP sessions store temporary conversation history (cleared when session ends)<br />
* Browser sessionStorage stores chat UI state (cleared when tab closes)</p>
<h4>Data Control & Privacy</h4>
<p><strong>User Control</strong>:<br />
* Delete API keys anytime from Settings > Fast RAGbot > Models tab<br />
* Clear all indexed content using “Clear Index” button<br />
* Reset plugin settings to defaults<br />
* Export or delete chat logs from Settings > Fast RAGbot > Chat Logs tab</p>
<p><strong>Data Deletion</strong>:<br />
* Deactivating the plugin preserves your data<br />
* Uninstalling the plugin removes all database tables and options<br />
* Use “Clear Index” to remove indexed content without uninstalling</p>
<p><strong>Privacy Compliance</strong>:<br />
* No data is shared with third parties except your chosen AI provider<br />
* Chat logs are optional and stored locally in your database<br />
* Pre-chat form (name/email collection) is optional and disabled by default<br />
* All user inputs are sanitized and validated<br />
* Rate limiting prevents abuse (10 requests per 60 seconds per IP)</p>
<h4>Developer Privacy Policy</h4>
<p>For questions about data handling, please review:<br />
* Your chosen AI provider’s privacy policy (links above)<br />
* Your own website’s privacy policy (you are the data controller)<br />
* WordPress.org privacy guidelines: https://wordpress.org/about/privacy/</p>
<h3>Privacy Policy</h3>
<p>This plugin acts as a data processor, sending user questions to your chosen AI provider. You (the site owner) are the data controller and responsible for:<br />
* Disclosing AI service usage in your privacy policy<br />
* Obtaining user consent where required by law (GDPR, CCPA, etc.)<br />
* Ensuring compliance with local privacy regulations</p>
<p>The plugin stores chat logs locally in your database. If you enable the pre-chat form, user names and emails are stored and should be disclosed in your privacy policy.</p>
<h3>Support</h3>
<p>For support, please visit the plugin’s support forum or contact the developer.</p>
<h3>Credits</h3>
<ul>
<li>Supports embeddings and text generation using Google Gemini, OpenAI, or Claude.</li>
<li>Built with WordPress coding standards</li>
<li>Follows accessibility best practices</li>
</ul>


Fast RAGbot

AI-powered chatbot with multi-LLM support (Gemini/OpenAI/Claude), multi-domain indexing, document upload, and conversation memory.

mobalabkashima

<p>RAG Chat for Amazon Bedrock is a WordPress plugin that seamlessly integrates your WordPress content with Amazon Bedrock Knowledge Bases to create an intelligent RAG (Retrieval-Augmented Generation) chatbot system.</p>
<p><strong>Key Features:</strong></p>
<ul>
<li><strong>Direct Amazon Bedrock Integration</strong>: Connects directly to Amazon Bedrock Knowledge Bases without external servers</li>
<li><strong>Automatic Content Synchronization</strong>: Automatically syncs WordPress posts and pages to Amazon Bedrock when content is created, updated, or deleted</li>
<li><strong>Real-time Chat Interface</strong>: Provides a chat widget for visitors to interact with your content using AI</li>
<li><strong>Comprehensive Admin Interface</strong>: Four dedicated admin pages for configuration and content management</li>
<li><strong>AWS Security</strong>: Uses AWS Signature Version 4 authentication for secure API communication</li>
<li><strong>Content Management</strong>: Track sync status and manage which content is synchronized to Amazon Bedrock</li>
</ul>
<p><strong>How It Works:</strong></p>
<ol>
<li>Configure your AWS credentials and Amazon Bedrock Knowledge Base in the plugin settings</li>
<li>New WordPress posts and pages are automatically synchronized to Amazon Bedrock when saved or deleted</li>
<li>Existing content can be synchronized using the export function in the Content Management page</li>
<li>Visitors can use the chat interface to ask questions about your content</li>
<li>Amazon Bedrock retrieves relevant content and generates intelligent responses using your WordPress data</li>
</ol>
<p><strong>Requirements:</strong></p>
<ul>
<li>AWS account with Amazon Bedrock access</li>
<li>Amazon Bedrock Knowledge Base configured</li>
<li>Valid AWS credentials (Access Key ID and Secret Access Key)</li>
</ul>
<p><strong>Demo:</strong></p>
<p>See the plugin in action: <a href="https://wp-rag-demo.mobalab.net/ask-rag-chat-for-amazon-bedrock/" rel="nofollow ugc">Live Demo</a></p>
<h3>Troubleshooting</h3>
<p><strong>Plugin Installation & Setup Issues</strong></p>
<h4>Plugin activation fails</h4>
<ol>
<li>Ensure your WordPress version meets the minimum requirement (6.6+)</li>
<li>Check that your PHP version is 7.4 or higher</li>
<li>Verify there are no plugin conflicts by temporarily deactivating other plugins</li>
</ol>
<h4>The chat interface doesn’t appear on my page</h4>
<ol>
<li>Make sure you’ve inserted the shortcode <code>[rag_chat_ab_chat]</code> in the correct location</li>
<li>Check that the plugin is activated</li>
<li>Verify your AWS credentials are correctly configured in the plugin settings</li>
</ol>
<p><strong>Content Synchronization Issues</strong></p>
<h4>Content sync is failing</h4>
<ol>
<li>Verify your AWS credentials have the correct permissions</li>
<li>Check that your Knowledge Base ID and Data Source ID are correct</li>
<li>Ensure your Knowledge Base has a “Custom” type data source</li>
<li>For existing content, use the “Export Posts and Pages to Amazon Bedrock” feature on the Content Management page</li>
</ol>
<h4>Export operation times out</h4>
<p>If you have many posts and pages, “Export Posts and Pages to Amazon Bedrock” may take a long time and cause timeout errors depending on your PHP settings. To reduce the risk of timeout:</p>
<ol>
<li>Export content in smaller batches by selecting specific date ranges</li>
<li>Consider increasing your PHP execution time limit if you have server access</li>
<li>Contact your hosting provider if timeout issues persist</li>
<li>For large-scale exports, we offer a dedicated bulk export PHP script that runs independently on your server and can handle large volumes of content without web browser timeout limitations. Contact us at <a href="https://tally.so/r/3jjoga" rel="nofollow ugc">https://tally.so/r/3jjoga</a> for more information about our bulk export solution</li>
</ol>
<p><strong>AWS Authentication & Permissions</strong></p>
<h4>AWS permission errors</h4>
<ol>
<li>Double-check all required IAM permissions are granted to your user</li>
<li>Verify your AWS Access Key ID and Secret Access Key are correct</li>
<li>Ensure your AWS account has access to Amazon Bedrock in the selected region</li>
<li>Check the AWS CloudTrail logs for detailed error information</li>
</ol>
<h4>AWS Marketplace subscription error</h4>
<p>If you encounter “Model access is denied” with “aws-marketplace:ViewSubscriptions” permission errors:</p>
<ol>
<li>Your IAM user needs the <code>aws-marketplace:ViewSubscriptions</code> permission</li>
<li>Add this permission to your IAM user’s policy</li>
<li>Wait 15 minutes after fixing the permissions before trying again</li>
<li>This is required for AWS Marketplace subscription completion</li>
</ol>
<p><strong>Model Access & Configuration</strong></p>
<h4>Model use case details required</h4>
<p>If you encounter an error like “Model use case details have not been submitted for this account. Fill out the Anthropic use case details form before using the model”:</p>
<ol>
<li>Anthropic requires use case details before using their models</li>
<li>Fill out the Anthropic use case details form in your AWS console</li>
<li>Wait 15 minutes after submitting before trying again</li>
<li>See the AWS documentation: https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html</li>
</ol>
<h4>Inference profile required error</h4>
<p>If you get an error like “Invocation of model ID anthropic.claude-haiku-4-5-20251001-v1:0 with on-demand throughput isn’t supported. Retry your request with the ID or ARN of an inference profile”:</p>
<ol>
<li>Some models require using inference profiles instead of direct model invocation</li>
<li>Use the ID or ARN of an inference profile that contains the model</li>
<li>Configure inference profiles in your Amazon Bedrock settings</li>
<li>See the AWS documentation: https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference.html</li>
</ol>
<h4>Chat responses are not working</h4>
<ol>
<li>Verify that your AWS region is correct in the plugin settings</li>
<li>Check that your Knowledge Base contains synchronized content</li>
<li>Ensure your IAM user has <code>bedrock:RetrieveAndGenerate</code> permissions</li>
<li>Try asking questions related to your synchronized content</li>
</ol>
<h3>External services</h3>
<p>This plugin uses the following Amazon Bedrock API endpoints provided by Amazon Web Services, Inc.:</p>
<ul>
<li>PUT https://bedrock-agent.{$region}.amazonaws.com/knowledgebases/{$knowledge_base_id}/datasources/{$data_source_id}
<ul>
<li>Called when a post or page is created or updated.</li>
<li>Used to add / update content on Amazon Bedrock.</li>
<li>The whole content (post or page) is sent.</li>
</ul>
</li>
<li>POST https://bedrock-agent.{$region}.amazonaws.com/knowledgebases/{$knowledge_base_id}/datasources/{$data_source_id}/documents/deleteDocuments
<ul>
<li>Called when a post is deleted or moved to trash.</li>
<li>Used to delete content from Amazon Bedrock.</li>
<li>Only the post / page ID is sent.</li>
</ul>
</li>
<li>POST https://bedrock-agent-runtime.{$region}.amazonaws.com/retrieveAndGenerate
<ul>
<li>Called when a visitor asks a question.</li>
<li>Used to generate responses using Amazon Bedrock’s AI.</li>
<li>The query that the user enters is sent.</li>
<li>The response contains a session ID, and it will be send to this endpoint in the subsequent requests along with the query.</li>
</ul>
</li>
</ul>
<p>Please see the following links for more information about Amazon Web Services:</p>
<ul>
<li><a href="https://aws.amazon.com/service-terms/" rel="nofollow ugc">AWS Service Terms</a></li>
<li><a href="https://aws.amazon.com/privacy/" rel="nofollow ugc">AWS Privacy</a></li>
</ul>
<h3>Related Projects</h3>
<p>This plugin is based on <strong>WP RAG</strong> (https://github.com/mobalab/wp-rag), which provides RAG functionality using external servers and OpenAI’s APIs. RAG Chat for Amazon Bedrock offers a different approach by integrating directly with Amazon Bedrock Knowledge Bases for users who prefer AWS-native solutions.</p>


RAG Chat for Amazon Bedrock

Integrate WordPress content with Amazon Bedrock Knowledge Bases to create an intelligent RAG (Retrieval-Augmented Generation) chatbot system.

Fast RAGbot vs RAG Chat for Amazon Bedrock