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96
docs/Integrations/WordPress/WordPress Basics.md
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96
docs/Integrations/WordPress/WordPress Basics.md
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---
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id: wordpress-overview
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title: WordPress Integration
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description: Overview of Evie's WordPress integration capabilities
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sidebar_label: Overview
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sidebar_position: 1
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---
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# WordPress Integration
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Evie offers seamless integration with WordPress through two dedicated plugins that help you enhance your WordPress site with AI capabilities. These plugins allow you to both synchronize your content with Evie's knowledge base and provide intelligent chat functionality to your visitors.
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## Available Plugins
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### Content Synchronization (eveai_sync)
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The content synchronization plugin automatically keeps your Evie knowledge base up-to-date with your WordPress content:
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- Syncs posts and pages to Evie's Standard Catalog
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- Maintains versioning of your content
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- Ensures your AI interactions always use the latest content
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### Chat Integration (eveai_chat)
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Add intelligent chat capabilities to your WordPress site:
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- Easy-to-integrate chat widget
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- Powered by Evie's Q&A RAG Specialist
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- Supports multiple languages
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- Simple configuration and setup
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## Prerequisites
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Before you can use either plugin, you'll need:
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1. A WordPress website
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2. An Evie account with API access
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3. An API key from Ask Eve AI
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## Getting Started
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### Obtaining Your API Key
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To use the WordPress plugins, you'll need an API key from Ask Eve AI. You can ask your AskEveAI administrator to provide you
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with an API Key. After the request, you'll receive an email containing:
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- Your tenant information
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- A unique API key
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- Enabled services information
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Here's an example of the API key email you'll receive:
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:::important
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Store your API key securely. It cannot be retrieved once the email is gone.
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:::
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```mermaid
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flowchart LR
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A[Request API Access] -->|Receive Email| B[API Key]
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B --> C[Configure Plugins]
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C --> D[Start Using Integration]
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```
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### Installation
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Both plugins can be [downloaded here](https://www.dropbox.com/scl/fo/6pkrp8o1n6rjvawjyrstt/AGGNOGlVn4hAz_BZOngOj68?rlkey=nj9gyz1k0bcjz7sxr0jq5c59l&dl=0)
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Both plugins follow the standard WordPress plugin installation process:
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1. Download the plugin files
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2. Go to your WordPress admin panel
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3. Navigate to Plugins > Add New
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4. Click "Upload Plugin"
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5. Select the plugin file and click "Install Now"
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6. Activate the plugin
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### Next Steps
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After installation, each plugin requires specific configuration:
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- [Content Synchronization Setup](./sync-plugin) - Configure how your WordPress content syncs with Evie
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- [Chat Integration Setup](./chat-plugin) - Set up the AI chat widget for your website
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## Support and Customization
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:::important
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Aggressive caching in WordPress can cripple correct behaviour of the Chat Plugin
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:::
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When running into problems:
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- Enable debugging in WordPress. We have quite extensive logging in both components.
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- For the chatbot itself, you can check the browser console (at least, on Chrome). A lot of debugging information is available.
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Both plugins are provided as open-source software, allowing for:
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- Custom modifications to match your needs
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- Integration with existing WordPress themes
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- Extended functionality development
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For technical support or questions about customization, please contact our support team.
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8
docs/Integrations/WordPress/_category_.json
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8
docs/Integrations/WordPress/_category_.json
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{
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"label": "WordPress Integrations",
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"position": 1,
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"link": {
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"type": "generated-index",
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"description": "Learn about the WordPress integration possibilities of Evie"
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}
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}
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127
docs/Integrations/WordPress/eveai_chat_plugin.md
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127
docs/Integrations/WordPress/eveai_chat_plugin.md
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---
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id: chat-plugin
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title: Chat Integration Plugin
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description: Add AI chat capabilities to your WordPress site
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sidebar_label: Chat Integration
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sidebar_position: 3
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---
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# Chat Integration Plugin (eveai_chat)
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The eveai_chat plugin enables you to add Evie's intelligent chat capabilities to any page or post on your WordPress site, allowing visitors to interact with your content through natural language conversations.
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## Configuration
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After installing and activating the plugin, configure the connection settings:
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### Connection Settings
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| Setting | Description |
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|---------|-------------|
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| Tenant ID | Your unique tenant identifier (found in API key email) |
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| API Key | Your authentication key (found in API key email) |
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| Socket URL | Evie's WebSocket endpoint (`https://evie.askeveai.com/`) |
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| Auth URL | Authentication endpoint (`https://evie.askeveai.com/api`) |
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Click "Save Settings" to store your configuration.
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## Adding Chat Widgets
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Once configured, you can add chat widgets to your pages or posts using a simple shortcode:
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```
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[eveai_chat language="en" languages="en,nl,fr,de,es" specialist_id="1"]
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```
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### Shortcode Parameters
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| Parameter | Description | Example |
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|-----------|-------------|---------|
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| language | Default chat language | `language="en"` |
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| languages | Available languages (comma-separated) | `languages="en,nl,fr,de"` |
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| specialist_id | ID of the Q&A RAG Specialist to use | `specialist_id="1"` |
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Example implementation on a page:
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## Chat Widget Behavior
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### Language Support
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- Users can switch languages during conversations via a dropdown menu
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- Language changes take effect immediately for new messages
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- Previous messages remain in their original language
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- Available languages are determined by your Evie tenant configuration
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### Conversation Management
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- Each page refresh starts a new conversation
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- Conversations don't persist across page navigations
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- No usage limits are currently implemented
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### Widget Display
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- Widget appears where the shortcode is placed in your content
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- Default height is 75vh (75% of viewport height)
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- Supports multiple widgets per page
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- Each widget can have different language and specialist settings
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- All widgets use the same tenant configuration
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## Implementation Guidelines
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### Best Practices
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1. **Specialist Selection**:
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- Use Q&A RAG Specialists only
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- Ensure specialist doesn't require additional parameters
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- Verify specialist ID before implementation
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|
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2. **Widget Placement**:
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- Consider user experience when placing widgets
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- Test on different screen sizes
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- Avoid placing multiple widgets too close together
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3. **Language Configuration**:
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- Set appropriate default language for your audience
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- Only include languages supported by your tenant
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- Provide clear language selection options
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|
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### Customization
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The widget's appearance can be customized by modifying the plugin's CSS:
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1. Locate `eveai-chat-style.css` in the plugin directory
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2. Modify styles to match your website's design
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3. Test changes across different devices and screen sizes
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|
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:::note
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Detailed customization instructions are beyond the scope of this documentation. For advanced customization needs, please consult your development team.
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:::
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## Technical Considerations
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- Widgets are displayed at shortcode location
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- Multiple widgets can be used within one WordPress instance
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- All widgets must use the same tenant
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- Different specialists can be used for different widgets
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- Mobile responsiveness should be considered when placing widgets
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- Page refreshes will reset conversations
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|
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```mermaid
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flowchart TB
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A[Configure Plugin Settings] -->|Save| B[Add Shortcode to Page]
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B --> C[Configure Widget Parameters]
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C --> D[Test Implementation]
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D --> E[Customize Appearance]
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style B fill:#3ecc5f,stroke:#333,stroke-width:2px
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```
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## Troubleshooting
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|
||||
| Issue | Possible Solution |
|
||||
|-------|------------------|
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| Widget not appearing | Verify shortcode syntax |
|
||||
| Connection errors | Check API credentials |
|
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| Invalid specialist errors | Verify specialist_id exists and is a Q&A RAG Specialist |
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||||
| Language not available | Confirm language is enabled in tenant configuration |
|
||||
|
||||
For additional support or custom implementation needs, contact your Evie support representative.
|
||||
121
docs/Integrations/WordPress/eveai_sync_plugin.md
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121
docs/Integrations/WordPress/eveai_sync_plugin.md
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---
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||||
id: sync-plugin
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title: Content Synchronization Plugin
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||||
description: Automatically sync your WordPress content with Evie
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sidebar_label: Content Sync
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sidebar_position: 2
|
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---
|
||||
|
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# Content Synchronization Plugin (eveai_sync)
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|
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The eveai_sync plugin automatically synchronizes your WordPress content with Evie's knowledge base, ensuring that your AI interactions always have access to your latest content.
|
||||
|
||||
## Configuration
|
||||
|
||||
After installing and activating the plugin, you'll need to configure several settings to connect with Evie:
|
||||
|
||||
|
||||
|
||||
### Basic Settings
|
||||
|
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| Setting | Description |
|
||||
|---------|----------------------------------------------------------------------|
|
||||
| API URL | The base URL for Evie's API (`https://eveai.askeveai.com/api/`) |
|
||||
| Tenant ID | Your unique tenant identifier (found in your API key email) |
|
||||
| API Key | Your authentication key for the API (found in your API key email) |
|
||||
| Catalog ID | The ID of the Evie catalog where content will be stored |
|
||||
| Default Language | The primary language of your content |
|
||||
| Excluded Categories | Comma-separated list of WordPress categories to exclude from syncing |
|
||||
|
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Click "Save Settings" to store your configuration.
|
||||
|
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## Initial Content Sync
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||||
|
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When setting up the plugin for the first time, you'll need to perform an initial bulk sync of your existing content:
|
||||
|
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1. Configure all settings as described above
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2. Click the "Start Bulk Sync" button
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3. Wait for the sync to complete
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- A log will be displayed after the sync finishes
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- The process cannot be interrupted once started
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||||
- All published posts and pages (except excluded categories) will be uploaded to Evie
|
||||
|
||||
```mermaid
|
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flowchart TB
|
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A[Configure Settings] -->|Save| B[Start Bulk Sync]
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||||
B --> C[Upload Content]
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||||
C --> D[Process Content]
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||||
D --> E[Sync Complete]
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||||
style B fill:#3ecc5f,stroke:#333,stroke-width:2px
|
||||
```
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||||
|
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## Automatic Synchronization
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||||
|
||||
After the initial setup, the plugin automatically maintains synchronization between your WordPress site and Evie:
|
||||
|
||||
### What Gets Synced?
|
||||
|
||||
✅ **Synchronized**:
|
||||
- Published posts and pages
|
||||
- Content updates to existing posts/pages
|
||||
- HTML content and formatting
|
||||
|
||||
❌ **Not Synchronized**:
|
||||
- Draft content
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||||
- Private or password-protected content
|
||||
- Posts/pages in excluded categories
|
||||
|
||||
### Sync Behaviors
|
||||
|
||||
The plugin handles different content changes automatically:
|
||||
|
||||
| Action in WordPress | Result in Evie |
|
||||
|--------------------|----------------------------------------|
|
||||
| New post/page published | Creates new document in Evie |
|
||||
| Existing content updated | Creates a new document version in Evie |
|
||||
| Content deleted | Marks document as invalid in Evie* |
|
||||
|
||||
*Note: Documents are never deleted from Evie to preserve historical interaction context.
|
||||
|
||||
### Processing Status
|
||||
|
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While content synchronization happens automatically, the actual processing in Evie occurs asynchronously:
|
||||
- Content is immediately sent to Evie when changes occur
|
||||
- Processing status can be monitored in Evie's administrative interface
|
||||
- Final processing time depends on network conditions and content complexity
|
||||
|
||||
## Resetting the Integration
|
||||
|
||||
If you need to start fresh (for example, when switching to a different catalog), you can reset the integration:
|
||||
|
||||
1. Click the "Reinitialize Site" button
|
||||
2. All Evie metadata will be removed from your WordPress site
|
||||
3. Sync status for all content will be reset
|
||||
4. You can then reconfigure the plugin and perform a new bulk sync
|
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|
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:::caution
|
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Reinitializing the site only affects the WordPress-Evie connection metadata. It does not delete any content from either WordPress or Evie.
|
||||
:::
|
||||
|
||||
## Best Practices
|
||||
|
||||
To get the most out of the content synchronization:
|
||||
|
||||
1. **Initial Setup**:
|
||||
- Configure and test settings before starting bulk sync
|
||||
- Choose excluded categories carefully
|
||||
|
||||
2. **Content Management**:
|
||||
- Publish content only when it's ready for AI consumption
|
||||
- Maintain consistent content structure for better AI interactions
|
||||
|
||||
3. **Monitoring**:
|
||||
- Regularly check Evie's administrative interface for processing status
|
||||
- Review AI interactions to ensure content is being utilized effectively
|
||||
|
||||
## Technical Considerations
|
||||
|
||||
- The plugin handles HTML content, preserving your content's formatting
|
||||
- No special catalog configuration is required in Evie
|
||||
- There are no size limitations for WordPress sites
|
||||
- Network connectivity affects sync speed and reliability
|
||||
8
docs/Integrations/_category_.json
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8
docs/Integrations/_category_.json
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{
|
||||
"label": "Integrations",
|
||||
"position": 4,
|
||||
"link": {
|
||||
"type": "generated-index",
|
||||
"description": "Learn about the integration possibilities of Evie"
|
||||
}
|
||||
}
|
||||
8
docs/Library/_category_.json
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8
docs/Library/_category_.json
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|
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{
|
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"label": "Library",
|
||||
"position": 2,
|
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"link": {
|
||||
"type": "generated-index",
|
||||
"description": "Learn about the core components of Evie's Library system"
|
||||
}
|
||||
}
|
||||
177
docs/Library/library_basics.md
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177
docs/Library/library_basics.md
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|
||||
---
|
||||
id: library_basics
|
||||
title: Evie's Library Basics
|
||||
description: Understanding catalogs, documents, and document versions in Evie's Library
|
||||
sidebar_label: Library Basics
|
||||
sidebar_position: 1
|
||||
---
|
||||
|
||||
# Evie's Library Basics: Catalogs, Documents & DocumentVersions
|
||||
|
||||
## Overview
|
||||
Evie's Library is an intelligent information storage and retrieval system. It organizes your business information semantically, making it easily accessible and searchable. The library can handle various types of content including HTML pages, PDF documents, and other document formats, storing them in a way that preserves their meaning and context.
|
||||
|
||||
## Library Structure
|
||||
The library is organized into sections called Catalogs, which help group related information together. Each catalog contains Documents, which can have multiple versions to track changes over time.
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Catalog {
|
||||
+name
|
||||
+description
|
||||
+type (Standard/Dossier)
|
||||
+min_chunk_size
|
||||
+max_chunk_size
|
||||
+user_metadata
|
||||
}
|
||||
class Document {
|
||||
+name
|
||||
+valid_from
|
||||
+valid_to
|
||||
}
|
||||
class DocumentVersion {
|
||||
+url
|
||||
+file_type
|
||||
+language
|
||||
+user_context
|
||||
+processing_status
|
||||
}
|
||||
|
||||
Catalog "1" -- "*" Document : contains
|
||||
Document "1" -- "*" DocumentVersion : has versions
|
||||
note for Catalog "Configurable based on type, e.g. Dossier has tagging fields"
|
||||
note for DocumentVersion "Processed asynchronously & Generates semantic chunks"
|
||||
```
|
||||
|
||||
### Catalogs
|
||||
A catalog is a container for related documents. You can create different catalogs to organize your information in ways that make sense for your business. Each catalog has the following key features:
|
||||
|
||||
- **Name and Description**: Helps identify the catalog's purpose
|
||||
- **Type**: Determines how information is organized within the catalog
|
||||
- **Chunk Size Settings**: Controls how documents are processed for optimal retrieval
|
||||
- **Custom Metadata**: Allows adding business-specific information
|
||||
|
||||
Catalog Types
|
||||
|
||||
Standard Catalog
|
||||
|
||||
Basic catalog type for general document storage
|
||||
All stored information is treated as a unified collection
|
||||
Suitable for most general knowledge bases
|
||||
|
||||
|
||||
Dossier Catalog
|
||||
|
||||
Advanced catalog type with tagging capabilities
|
||||
Allows organizing documents with custom tags
|
||||
Requires configuration of tagging fields during catalog creation
|
||||
Example tagging field configuration:
|
||||
|
||||
|
||||
|
||||
```
|
||||
{
|
||||
"tagging_fields": {
|
||||
"company": {
|
||||
"type": "string",
|
||||
"required": true,
|
||||
"description": "Company name"
|
||||
},
|
||||
"year": {
|
||||
"type": "integer",
|
||||
"required": false,
|
||||
"max_value": 2100,
|
||||
"min_value": 1900,
|
||||
"description": "Document year"
|
||||
},
|
||||
"document_type": {
|
||||
"type": "enum",
|
||||
"required": false,
|
||||
"description": "Type of document",
|
||||
"allowed_values": [
|
||||
"quarterly_report",
|
||||
"annual_report",
|
||||
"presentation",
|
||||
"press_release"
|
||||
]
|
||||
},
|
||||
"confidentiality": {
|
||||
"type": "enum",
|
||||
"required": false,
|
||||
"description": "Document confidentiality level",
|
||||
"allowed_values": [
|
||||
"public",
|
||||
"internal",
|
||||
"confidential"
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
This configuration defines:
|
||||
|
||||
- A required company name field as text
|
||||
- An optional year field (between 1900 and 2100)
|
||||
- An optional document type selection from predefined options
|
||||
- An optional confidentiality level selection
|
||||
|
||||
### Documents and Versioning
|
||||
Documents in Evie's Library are managed with version control to ensure information stays current:
|
||||
|
||||
- **Basic Document Properties**:
|
||||
- Name
|
||||
- Validity period (optional)
|
||||
- Associated metadata
|
||||
|
||||
- **Document Versions**:
|
||||
- Track changes in document content
|
||||
- Store the actual content and its processing state
|
||||
- Support multiple file formats
|
||||
- Can be automatically updated for URL-based sources
|
||||
- Include language information
|
||||
|
||||
### Multilingual Support
|
||||
Evie's Library has built-in multilingual capabilities:
|
||||
- Documents in different languages can coexist in the same catalog
|
||||
- Information can be retrieved regardless of the language it was stored in
|
||||
- Questions can be asked in any supported language
|
||||
- No need to store multiple translations of the same document
|
||||
|
||||
### Document Processing
|
||||
When documents are added to the library:
|
||||
|
||||
1. They are automatically processed to understand their content
|
||||
2. Processing happens in the background without interrupting your work
|
||||
3. Documents are split into semantic chunks for optimal understanding
|
||||
4. The latest version becomes available once processing is complete
|
||||
|
||||
### Using the Library
|
||||
To make the most of Evie's Library:
|
||||
|
||||
1. **Organize Your Information**:
|
||||
- Create catalogs based on your business needs
|
||||
- Choose between Standard and Dossier catalogs based on whether you need tagging
|
||||
- Add relevant metadata to help organize information
|
||||
|
||||
2. **Add Documents**:
|
||||
- Provide URLs for documents whenever possible (recommended method)
|
||||
- URLs allow automatic document refreshing
|
||||
- Ensures your library stays up-to-date with source changes
|
||||
- Maintains version history automatically
|
||||
- File uploads are supported as an alternative
|
||||
- Use when URL access isn't available
|
||||
- Note: Updates will require manual re-upload
|
||||
|
||||
3. **Maintain Your Library**:
|
||||
- URL-based documents can be automatically refreshed to stay current
|
||||
- Monitor processing status for new additions
|
||||
- Manage document validity periods if needed
|
||||
- For uploaded files, consider periodically checking if updates are needed
|
||||
|
||||
## Best Practices
|
||||
- Group related documents in the same catalog
|
||||
- Use meaningful names and descriptions for catalogs and documents
|
||||
- Add relevant metadata to make information more discoverable
|
||||
- For Dossier catalogs, establish consistent tagging conventions
|
||||
- Prefer URL-based documents over file uploads to enable automatic updates
|
||||
230
docs/Library/processors.md
Normal file
230
docs/Library/processors.md
Normal file
@@ -0,0 +1,230 @@
|
||||
---
|
||||
id: processors
|
||||
title: Understanding Processors
|
||||
description: Learn how processors handle different types of files in Evie's Library
|
||||
sidebar_label: Processors
|
||||
sidebar_position: 2
|
||||
---
|
||||
|
||||
# Understanding Processors
|
||||
|
||||
## Overview
|
||||
|
||||
Processors are essential components in Evie's Library that determine how different types of files (HTML, PDF, audio)
|
||||
are processed and stored. Each processor is specifically configured for a catalog and handles one or more file types,
|
||||
ensuring that content is properly extracted, chunked, and stored according to your business needs.
|
||||
|
||||
We will use the term *Chunks* or *Chunking* throughout the remainder of this chapter. Chunking is the process of
|
||||
splitting large files into smaller pieces for storage. This enables Evie to more precisely capture the semantics of each
|
||||
piece, and it enables Evie to return smaller and more specific pieces of content related to a question that is asked.
|
||||
|
||||
Evie has some proprietary algorithms to intelligently process and chunk files, to optimize the knowledge in her Library.
|
||||
|
||||
The relationship between Catalogs and Processors is shown in this diagram:
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Catalog {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+type: String
|
||||
+min_chunk_size: Integer
|
||||
+max_chunk_size: Integer
|
||||
+user_metadata: JSON
|
||||
+system_metadata: JSON
|
||||
+configuration: JSON
|
||||
}
|
||||
class Processor {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+type: String
|
||||
+sub_file_type: String
|
||||
+tuning: Boolean
|
||||
+user_metadata: JSON
|
||||
+system_metadata: JSON
|
||||
+configuration: JSON
|
||||
}
|
||||
|
||||
Catalog "1" -- "*" Processor : has
|
||||
note for Processor "Unique per catalog\nConfigured for specific file types"
|
||||
```
|
||||
|
||||
## Key Concepts
|
||||
|
||||
### Processor Basics
|
||||
|
||||
- **Catalog-Specific**: Each processor is uniquely defined for a specific catalog and cannot be shared across catalogs
|
||||
- **File Type Support**: Currently supports HTML, PDF, Markdown, Docx and audio files
|
||||
- **Optional Usage**: If no processor is specified for a file type, files of that type will not be processed
|
||||
- **File Size Limits**: Maximum file size of 50MB for all file types
|
||||
|
||||
### Sub-File Types
|
||||
|
||||
Sub-file types allow you to process different document types within the same catalog using different rules. For example:
|
||||
- Quarterly reports might have a different structure than project definitions
|
||||
- News articles might need different processing than product documentation
|
||||
- Internal memos might require different handling than public announcements
|
||||
|
||||
### General Configuration Options
|
||||
General configuration options, along with processor-specific configuration options, are used to allow you, the end-user,
|
||||
to specialise the way documents are processed and chunked. This enables us to use your knowledge about document
|
||||
structure with ours, to enable optimal storage of knowledge in Evie's Library.
|
||||
|
||||
These general configuration options are available in the configuration of most processors, and introduce some additional
|
||||
rules for chunking to take place.
|
||||
|
||||
1. **Chunking Heading Level**
|
||||
- Defines the number of headings that should be used to split a file into meaningful chunks
|
||||
- Default value: 2
|
||||
- You can specify a value between 1 and 6
|
||||
2. **Chunking Patterns**
|
||||
- Defines 'business sections' as regular expressions, allowing you force splitting the file if a section heading matches a given regular expression
|
||||
- A practical example: '\bProfile\b' checks if the word 'Profile' is present in the title, and could be used if you have a lot of structured content describing your customers. There profile will be defined in a separate chunk.
|
||||
- You can specify any number of patterns (on a new line)
|
||||
|
||||
## Types of Processors
|
||||
|
||||
### HTML Processor
|
||||
The HTML processor provides detailed control over how HTML content is processed through various configuration options.
|
||||
These options define the HTML processing, and they follow a strict process:
|
||||
|
||||
1. **Included Elements** (`html_included_elements`)
|
||||
- Defines the main sections of the document to process
|
||||
- Only content within these elements will be considered
|
||||
- Example: `article, main`
|
||||
|
||||
2. **Excluded Elements** (`html_excluded_elements`)
|
||||
- Elements to remove from included sections
|
||||
- Useful for navigation, headers, footers, etc.
|
||||
- Example: `header, footer, nav, script`
|
||||
|
||||
3. **HTML Tags** (`html_tags`)
|
||||
- Specific content tags to process
|
||||
- Determines what content is actually stored
|
||||
- Example: `p, h1, h2, h3, table`
|
||||
|
||||
4. **Excluded Classes** (`html_excluded_classes`)
|
||||
- Classes of elements to exclude
|
||||
- Useful for removing specific sections like sidebars
|
||||
- Example: `sidebar, advertisement`
|
||||
|
||||
This is graphically shown in this process flow:
|
||||
|
||||
```mermaid
|
||||
flowchart TD
|
||||
A[HTML Document] --> B[Check Included Elements]
|
||||
B --> C[Remove Excluded Elements]
|
||||
C --> D[Process HTML Tags]
|
||||
D --> E[Remove Excluded Classes]
|
||||
|
||||
style A fill:#9c2d66,stroke:#333,stroke-width:2px
|
||||
style B fill:#423372,stroke:#333,stroke-width:2px
|
||||
style C fill:#423372,stroke:#333,stroke-width:2px
|
||||
style D fill:#423372,stroke:#333,stroke-width:2px
|
||||
style E fill:#423372,stroke:#333,stroke-width:2px
|
||||
|
||||
note1[Only process content within<br>included elements]
|
||||
note2[Remove specified elements<br>from included content]
|
||||
note3[Include only specified<br>HTML tags]
|
||||
note4[Remove content with<br>excluded classes]
|
||||
|
||||
B --- note1
|
||||
C --- note2
|
||||
D --- note3
|
||||
E --- note4
|
||||
```
|
||||
|
||||
Additional HTML processing settings:
|
||||
- **End Tags** (`html_end_tags`): Defines where chunks can logically end
|
||||
- **Chunk Sizing**: Respects catalog's min/max chunk sizes while maintaining content coherence
|
||||
|
||||
### PDF Processor
|
||||
- Handles PDF document processing
|
||||
- No additional configuration required
|
||||
- Automatically extracts text and maintains document structure
|
||||
|
||||
### Markdown Processor
|
||||
- Handles Markdown document processing
|
||||
- No additional configuration required
|
||||
- Automatically extracts text and maintains document structure
|
||||
|
||||
### Docx Processor
|
||||
The Docx processor provides detailed control on how to handle Microsoft Office documents through various configuration
|
||||
options:
|
||||
|
||||
1. **Extract Comments**
|
||||
- Whether to include document comments in the markdown
|
||||
- Default: False
|
||||
2. **Extract Headers/Footers**
|
||||
- Whether to include headers and footers in the markdown
|
||||
- Default: False
|
||||
3. **Preserve Formatting**
|
||||
- Whether to preserve bold, italic, and other text formatting
|
||||
- Default: True
|
||||
4. **List Style**
|
||||
- How to format lists
|
||||
- One of ["dash", "asterisk", "plus"]
|
||||
- Default value: "dash"
|
||||
5. **Image Handling**
|
||||
- How to handle embedded images
|
||||
- One of ["skip", "extract", "placeholder"]
|
||||
- Default value: "skip"
|
||||
6. **Table Alignment**
|
||||
- How to align table contents
|
||||
- One of ["left", "center", "preserve"]
|
||||
- Default value: "left"
|
||||
|
||||
### Audio Processor
|
||||
- Supports mp3, mp4, and ogg formats
|
||||
- Automatically transcribes audio content
|
||||
- No additional configuration required
|
||||
|
||||
## Managing Processors
|
||||
|
||||
### Creating Processors
|
||||
|
||||
When creating a processor, consider:
|
||||
1. Which catalog it will serve
|
||||
2. What file type it needs to handle
|
||||
3. Whether you need a sub-file type
|
||||
4. Any specific configuration needed (especially for HTML)
|
||||
|
||||
### Modifying Processors
|
||||
|
||||
- Processors can be modified after creation
|
||||
- Changes don't automatically apply to already processed documents
|
||||
- Documents must be manually reprocessed to apply new processor settings
|
||||
|
||||
### Processor Tuning
|
||||
|
||||
The tuning feature is available for implementation teams to:
|
||||
- Generate additional processing logs
|
||||
- Gain insights into exact processing behavior
|
||||
- Fine-tune processor behavior for specific contexts
|
||||
|
||||
Note: Tuning logs are only accessible to implementation teams, not end users.
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Plan Your Structure**
|
||||
- Define clear sub-file types based on document characteristics
|
||||
- Consider document structure when configuring HTML processors
|
||||
|
||||
2. **HTML Processing**
|
||||
- Start with broader included elements and narrow down
|
||||
- Test configuration with representative documents
|
||||
- Use excluded classes for fine-grained control
|
||||
|
||||
3. **General Tips**
|
||||
- Keep file sizes under the 50MB limit
|
||||
- Document your processor configurations
|
||||
- Plan for periodic review of processor settings
|
||||
|
||||
## Future Extensions
|
||||
|
||||
The processor framework is designed for extensibility:
|
||||
- Additional processor types planned
|
||||
- Metadata fields ready for future features
|
||||
- Configuration options may be expanded
|
||||
185
docs/Library/retrievers.md
Normal file
185
docs/Library/retrievers.md
Normal file
@@ -0,0 +1,185 @@
|
||||
---
|
||||
id: retrievers
|
||||
title: Understanding Retrievers
|
||||
description: Learn how retrievers find and extract relevant information from your documents
|
||||
sidebar_label: Retrievers
|
||||
sidebar_position: 3
|
||||
---
|
||||
|
||||
# Understanding Retrievers
|
||||
|
||||
## Overview
|
||||
|
||||
Retrievers are essential components in Evie's Library that help find and extract relevant information from your documents.
|
||||
Think of retrievers as intelligent search engines that understand the meaning behind your questions and find the most
|
||||
relevant content from your stored documents.
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Catalog {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+type: String
|
||||
+min_chunk_size: Integer
|
||||
+max_chunk_size: Integer
|
||||
+user_metadata: JSON
|
||||
}
|
||||
|
||||
class Retriever {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+catalog_id: Integer
|
||||
+type: String
|
||||
+tuning: Boolean
|
||||
+configuration: JSON
|
||||
+arguments: JSON
|
||||
}
|
||||
|
||||
class StandardRAGRetriever {
|
||||
+configuration
|
||||
es_k: Integer
|
||||
es_similarity_threshold: Float
|
||||
+arguments
|
||||
query: String
|
||||
}
|
||||
|
||||
class DossierRetriever {
|
||||
+configuration
|
||||
es_k: Integer
|
||||
es_similarity_threshold: Float
|
||||
tag_conditions: JSON
|
||||
+arguments
|
||||
query: String
|
||||
}
|
||||
|
||||
Catalog "1" -- "*" Retriever : has
|
||||
Retriever <|-- StandardRAGRetriever
|
||||
Retriever <|-- DossierRetriever
|
||||
|
||||
note for StandardRAGRetriever "Default similarity threshold: 0.3<br>Default es_k: 8"
|
||||
note for DossierRetriever "Coming soon<br>Specialized for Dossier catalogs"
|
||||
```
|
||||
## Key Concepts
|
||||
|
||||
### What is a Retriever?
|
||||
|
||||
A retriever is responsible for:
|
||||
- Understanding the meaning of your questions
|
||||
- Searching through document chunks in your catalog
|
||||
- Finding the most relevant information based on semantic similarity
|
||||
- Providing context for Evie's responses
|
||||
|
||||
```mermaid
|
||||
flowchart LR
|
||||
A[User Question] --> B[Retriever]
|
||||
B --> C[Document Chunks]
|
||||
C --> D[Most Relevant Information]
|
||||
D --> E[Evie's Response]
|
||||
|
||||
style A fill:#9c2d66,stroke:#333,stroke-width:2px
|
||||
style B fill:#423372,stroke:#333,stroke-width:2px
|
||||
style C fill:#423372,stroke:#333,stroke-width:2px
|
||||
style D fill:#423372,stroke:#333,stroke-width:2px
|
||||
style E fill:#9c2d66,stroke:#333,stroke-width:2px
|
||||
```
|
||||
|
||||
### How Retrievers Work
|
||||
|
||||
When you ask Evie a question, the retriever:
|
||||
1. Analyzes your question to understand its meaning
|
||||
2. Compares it with stored document chunks
|
||||
3. Assigns similarity scores to each chunk
|
||||
4. Returns the most relevant chunks based on configuration settings
|
||||
|
||||
## Types of Retrievers
|
||||
|
||||
### Standard RAG Retriever
|
||||
|
||||
The Standard RAG (Retrieval-Augmented Generation) Retriever is the default option suitable for most use cases. It
|
||||
searches through all documents in a catalog to find relevant information.
|
||||
|
||||
Configuration options include:
|
||||
- **Maximum Results (es_k)**: Controls how many document chunks to retrieve (default: 8)
|
||||
- **Similarity Threshold**: Determines how closely chunks must match your question (default: 0.3)
|
||||
- Lower threshold = stricter matching
|
||||
- Higher threshold = more permissive matching
|
||||
|
||||
### Dossier Retriever (Coming Soon)
|
||||
|
||||
A specialized retriever for Dossier catalogs that will allow:
|
||||
- Filtering by document tags
|
||||
- Creating specific "viewpoints" based on tag combinations
|
||||
- Combining semantic search with tag-based filtering
|
||||
|
||||
## Setting Up Retrievers
|
||||
|
||||
### Creating a New Retriever
|
||||
|
||||
To create a retriever:
|
||||
1. Enter standard values such as name and description
|
||||
2. Select the target catalog
|
||||
3. Choose the retriever type
|
||||
4. After saving, you will have the ability to set the specific configuration (based on the type)
|
||||
|
||||
### Configuration Best Practices
|
||||
|
||||
1. **Similarity Threshold Tuning**:
|
||||
- Start with the default 0.3 threshold
|
||||
- If receiving too much information: Lower the threshold
|
||||
- If receiving too little information: Raise the threshold
|
||||
|
||||
2. **Multiple Retrievers**:
|
||||
You can create multiple retrievers for the same catalog to serve different purposes. For example:
|
||||
- A broad retriever with higher threshold for general questions
|
||||
- A strict retriever with lower threshold for specific queries
|
||||
- Different retrievers for different document subsets (in Dossier catalogs)
|
||||
|
||||
## Practical Examples
|
||||
|
||||
### Standard RAG Retriever Example
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "General Knowledge Retriever",
|
||||
"type": "STANDARD_RAG",
|
||||
"configuration": {
|
||||
"es_k": 8,
|
||||
"es_similarity_threshold": 0.3
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Future Dossier Retriever Example
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "Quarterly Reports 2024",
|
||||
"type": "DOSSIER_RAG",
|
||||
"configuration": {
|
||||
"es_k": 8,
|
||||
"es_similarity_threshold": 0.3,
|
||||
"tag_conditions": {
|
||||
"document_type": "quarterly_report",
|
||||
"year": 2024
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Tips for Optimal Retrieval
|
||||
|
||||
1. **Name Retrievers Clearly**:
|
||||
Use descriptive names that indicate their purpose and configuration
|
||||
|
||||
2. **Monitor Performance**:
|
||||
- If answers are missing important information, consider:
|
||||
- Increasing the similarity threshold
|
||||
- Increasing the maximum results (es_k)
|
||||
- If answers contain irrelevant information, consider:
|
||||
- Decreasing the similarity threshold
|
||||
- Decreasing the maximum results
|
||||
|
||||
3. **Use Multiple Retrievers**:
|
||||
Create specialized retrievers for different use cases within the same catalog
|
||||
8
docs/Specialists/_category_.json
Normal file
8
docs/Specialists/_category_.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"label": "Specialists",
|
||||
"position": 3,
|
||||
"link": {
|
||||
"type": "generated-index",
|
||||
"description": "Learn about the Specialists enabling intelligent interactions and task execution"
|
||||
}
|
||||
}
|
||||
156
docs/Specialists/q_a_rag_specialist.md
Normal file
156
docs/Specialists/q_a_rag_specialist.md
Normal file
@@ -0,0 +1,156 @@
|
||||
---
|
||||
id: qa-rag-specialist
|
||||
title: Q&A RAG Specialist
|
||||
description: Understand how to configure and use the Q&A RAG Specialist for intelligent conversations
|
||||
sidebar_label: Q&A RAG Specialist
|
||||
sidebar_position: 2
|
||||
---
|
||||
|
||||
# Q&A RAG Specialist
|
||||
|
||||
## Overview
|
||||
|
||||
The Q&A RAG Specialist enables intelligent question-answering interactions using your organization's specific information stored in Evie's Library. Whether supporting customers on your website or helping employees access internal knowledge, this specialist provides accurate, context-aware responses based on your documented information.
|
||||
|
||||
## Structure
|
||||
|
||||
The Q&A RAG Specialist extends the base Specialist with specific configuration, arguments, and results tailored for question-answering:
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Specialist {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+type: String
|
||||
+configuration: JSON
|
||||
+arguments: JSON
|
||||
+results: JSON
|
||||
}
|
||||
|
||||
class QARagSpecialist {
|
||||
+configuration
|
||||
specialist_context: String
|
||||
temperature: Float
|
||||
+arguments
|
||||
language: String
|
||||
query: String
|
||||
+results
|
||||
detailed_query: String
|
||||
answer: String
|
||||
citations: Array
|
||||
insufficient_info: Boolean
|
||||
}
|
||||
|
||||
Specialist <|-- QARagSpecialist
|
||||
```
|
||||
|
||||
## Configuration
|
||||
|
||||
### Specialist Context
|
||||
The context defines the specialist's identity and behavior. A well-structured context typically includes:
|
||||
|
||||
1. **Identity**
|
||||
- The specialist's name
|
||||
- Role or position (e.g., company spokesperson)
|
||||
|
||||
2. **Reference Handling**
|
||||
- How your company/product names might appear
|
||||
- Common variations or abbreviations
|
||||
- How to handle self-references
|
||||
|
||||
3. **Domain Clarity**
|
||||
- Clear description of the business domain
|
||||
- Disambiguation from similar companies/products
|
||||
|
||||
Example context:
|
||||
```json
|
||||
{
|
||||
"specialist_context": "You are Evie, the main spokesperson for 'Ask Eve AI'.
|
||||
'Ask Eve AI' can be spelled in different ways (e.g. askeveai), can be
|
||||
shortened to Evie, and can be referred to as 'you' (as you share the
|
||||
same name as the product, and actually are an impersonation of the
|
||||
product Evie). Ask Eve AI sells an advanced SAAS platform, also called
|
||||
Evie, that enables companies to easily implement business cases based
|
||||
on generative AI, mainly LLMs."
|
||||
}
|
||||
```
|
||||
|
||||
### Temperature
|
||||
Controls the balance between creativity and precision in responses:
|
||||
|
||||
- **Range**: 0 to 1
|
||||
- **Default**: 0.3
|
||||
- **Effect**:
|
||||
- Lower values (closer to 0): More conservative, strictly adhering to source content
|
||||
- Higher values (closer to 1): More creative, potentially introducing more variation
|
||||
- Adjust based on your needs:
|
||||
- Increase if responses feel too rigid
|
||||
- Decrease if responses take too many liberties with the source material
|
||||
- Note: Higher temperatures increase the risk of hallucinations
|
||||
|
||||
## Arguments
|
||||
|
||||
Arguments required for each interaction:
|
||||
|
||||
1. **language**
|
||||
- Specifies the desired response language
|
||||
- Evie intelligently handles multi-language content
|
||||
- Can find relevant information across language barriers
|
||||
- Note: While Evie translates answers, it is not a document translation service
|
||||
|
||||
2. **query**
|
||||
- The actual question from the end user
|
||||
- Will be processed considering session context
|
||||
|
||||
## Results
|
||||
|
||||
The specialist returns structured results for each interaction:
|
||||
|
||||
1. **detailed_query**
|
||||
- Enhanced version of the original query
|
||||
- Incorporates context from previous interactions
|
||||
- Helps maintain conversation coherence
|
||||
|
||||
2. **answer**
|
||||
- The specialist's response to the query
|
||||
- Based on retrieved information
|
||||
- Formulated according to configuration settings
|
||||
|
||||
3. **citations**
|
||||
- References to specific embeddings used
|
||||
- Traceable back to source document versions
|
||||
- Enables verification and source tracking
|
||||
|
||||
4. **insufficient_info**
|
||||
- Boolean flag indicating information adequacy
|
||||
- `true` when library content insufficient for proper response
|
||||
- Helps monitor answer quality and identify knowledge gaps
|
||||
|
||||
## Integration Notes
|
||||
|
||||
While the specialist provides structured arguments and results, these technical details are typically hidden from end users. Client interfaces (such as chat widgets) handle:
|
||||
|
||||
- Submitting properly formatted arguments
|
||||
- Receiving and processing results
|
||||
- Presenting information in a user-friendly format
|
||||
|
||||
This abstraction allows for:
|
||||
- Clean user experiences
|
||||
- Consistent interaction patterns
|
||||
- Technical flexibility for integrators
|
||||
|
||||
## Multi-language Capabilities
|
||||
|
||||
The Q&A RAG Specialist features advanced language handling:
|
||||
|
||||
- Finds relevant content across languages
|
||||
- Provides responses in requested language
|
||||
- Maintains context across language switches
|
||||
- Intelligently translates responses while preserving meaning
|
||||
|
||||
For example, English questions can receive relevant information from Dutch documents, with responses properly formulated in English.
|
||||
|
||||
---
|
||||
|
||||
The next sections cover best practices, common use cases, and integration examples.
|
||||
155
docs/Specialists/specialists_introduction.md
Normal file
155
docs/Specialists/specialists_introduction.md
Normal file
@@ -0,0 +1,155 @@
|
||||
---
|
||||
id: specialists
|
||||
title: Understanding Specialists - Introduction
|
||||
description: Learn how specialists use Evie's Library to execute specific tasks
|
||||
sidebar_label: Specialists Intro
|
||||
sidebar_position: 1
|
||||
---
|
||||
|
||||
# Understanding Specialists - Introduction
|
||||
|
||||
## Overview
|
||||
|
||||
Specialists are powerful components in Evie's ecosystem that perform specific activities using information from Evie's Library. Think of specialists as expert assistants, each trained for particular tasks - from answering questions to filling templates or providing specialized support.
|
||||
|
||||
## How Specialists Work
|
||||
|
||||
Every specialist follows a structured approach:
|
||||
|
||||
1. **Information Gathering**: Using one or more retrievers, specialists search Evie's Library for relevant information
|
||||
2. **Information Processing**: Retrieved information is processed according to the specialist's specific algorithm
|
||||
3. **Task Execution**: The specialist performs its designated task using:
|
||||
- Retrieved information
|
||||
- Its configuration settings
|
||||
- Provided arguments
|
||||
|
||||
```mermaid
|
||||
flowchart TD
|
||||
A[User Request] --> B[Specialist]
|
||||
B --> C{Process Arguments}
|
||||
C --> D[Evaluate Specialist Arguments]
|
||||
D --> E[Push Arguments to Retrievers]
|
||||
E --> F[Search Library using Retrievers]
|
||||
F --> G[Combine Retrieved Information]
|
||||
G --> H[Execute Specialist Algorithm]
|
||||
H --> I[Return Results]
|
||||
|
||||
style A fill:#9c2d66,stroke:#333,stroke-width:2px
|
||||
style B fill:#423372,stroke:#333,stroke-width:2px
|
||||
style I fill:#9c2d66,stroke:#333,stroke-width:2px
|
||||
```
|
||||
|
||||
### Key Components
|
||||
|
||||
The relationship between specialists and other components is shown in this diagram:
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Specialist {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+description: Text
|
||||
+type: String
|
||||
+configuration: JSON
|
||||
+arguments: JSON
|
||||
+results: JSON
|
||||
}
|
||||
|
||||
class Retriever {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+catalog_id: Integer
|
||||
+type: String
|
||||
+configuration: JSON
|
||||
}
|
||||
|
||||
Specialist "*" -- "*" Retriever : uses
|
||||
note for Specialist "Each specialist can use multiple retrievers"
|
||||
note for Retriever "Each retriever can be used by multiple specialists"
|
||||
```
|
||||
|
||||
### Sessions and Interactions
|
||||
|
||||
Each specialist operates within sessions, managing interactions as shown here:
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class ChatSession {
|
||||
+id: Integer
|
||||
+session_id: String
|
||||
+session_start: DateTime
|
||||
+session_end: DateTime
|
||||
}
|
||||
|
||||
class Interaction {
|
||||
+id: Integer
|
||||
+chat_session_id: Integer
|
||||
+specialist_id: Integer
|
||||
+specialist_arguments: JSON
|
||||
+specialist_results: JSON
|
||||
+question_at: DateTime
|
||||
+answer_at: DateTime
|
||||
}
|
||||
|
||||
class Specialist {
|
||||
+id: Integer
|
||||
+name: String
|
||||
+type: String
|
||||
}
|
||||
|
||||
ChatSession "1" -- "*" Interaction
|
||||
Specialist "1" -- "*" Interaction
|
||||
```
|
||||
|
||||
## Working with Specialists
|
||||
|
||||
### Configuration & Arguments
|
||||
|
||||
Specialists use three key data structures:
|
||||
|
||||
1. **Configuration**
|
||||
- Fixed parameters that remain constant during all interactions
|
||||
- Defines core behavior settings (e.g., inference parameters)
|
||||
- Set during specialist creation
|
||||
|
||||
2. **Arguments**
|
||||
- Variable parameters passed during each interaction
|
||||
- Can change between interactions within a session
|
||||
- Example: questions or specific task parameters
|
||||
|
||||
3. **Results**
|
||||
- Output structure returned after each interaction
|
||||
- Contains the specialist's response or task output
|
||||
- Format depends on specialist type
|
||||
|
||||
### Sessions
|
||||
|
||||
- Each session is dedicated to one specialist
|
||||
- Sessions maintain context across multiple interactions
|
||||
- Session boundaries are specialist-specific
|
||||
- For Q&A specialists: typically aligned with client communication sessions
|
||||
- For task-based specialists: may be bound by task completion
|
||||
|
||||
### Argument Inheritance
|
||||
|
||||
Specialists implement an intelligent argument inheritance mechanism:
|
||||
|
||||
1. Arguments can be defined at both specialist and retriever levels
|
||||
2. When argument names match:
|
||||
- Specialist arguments take precedence
|
||||
- Retriever-specific values can override this if explicitly set
|
||||
3. This allows for:
|
||||
- Consistent argument handling across retrievers
|
||||
- Flexibility when needed for specific retrievers
|
||||
|
||||
## Current Specialist Types
|
||||
|
||||
Currently, the main specialist type is the RAG (Retrieval-Augmented Generation) Specialist, focused on question-answering using library content. Additional specialist types are being developed for:
|
||||
|
||||
- Sales support
|
||||
- Template filling
|
||||
- Specialized customer support
|
||||
- Document analysis
|
||||
- And more...
|
||||
|
||||
Detailed documentation for each specialist type is available in their respective sections.
|
||||
102
docs/introduction.md
Normal file
102
docs/introduction.md
Normal file
@@ -0,0 +1,102 @@
|
||||
---
|
||||
id: introduction
|
||||
title: Introduction to Ask Eve AI
|
||||
description: Learn about Evie, a cutting-edge AI solution for transforming how businesses interact with information
|
||||
sidebar_label: Introduction
|
||||
sidebar_position: 1
|
||||
slug: /
|
||||
keywords:
|
||||
- introduction
|
||||
- AI assistant
|
||||
- knowledge base
|
||||
- Evie
|
||||
---
|
||||
|
||||
# Introduction to Ask Eve AI
|
||||
|
||||
Welcome to the world of Ask Eve AI, affectionately known as **Evie**—a cutting-edge AI solution
|
||||
designed to revolutionise how businesses interact with information. Whether enhancing customer
|
||||
experiences, boosting internal efficiency, or empowering specialised teams, Evie is here to unlock
|
||||
the full potential of your organisation’s knowledge and to assist you and your teams in everyday
|
||||
tasks.
|
||||
|
||||
## What is Evie?
|
||||
|
||||
Evie is an Agentic AI assistant tailored to your unique business needs. By leveraging advanced AI
|
||||
techniques, she transforms complex information into natural, engaging dialogues. Unlike generic
|
||||
chatbots, Evie is deeply integrated into your specific knowledge base, offering precise,
|
||||
traceable, and contextual responses.
|
||||
Using agentic AI techniques, Evie can automate repetitive tasks, improve internal productivity,
|
||||
and empower your teams with expertise.
|
||||
|
||||
Here’s how Evie stands out:
|
||||
- **Custom Knowledge Integration**: Evie learns from your documents, intranet, website, and other sources, providing responses grounded in your organisation’s information.
|
||||
- **Conversational AI**: Interact with Evie just like you would with a colleague. She understands context, remembers past interactions, and responds naturally.
|
||||
- **Agentic Behaviour**: Evie goes beyond just conversations. She can perform smart actions based on your information or based on the conversation. We are gradually extending Evie's possibilities by transforming the knowledge of our partners into intelligent specialists (Agentic AI).
|
||||
- **Multilingual Capabilities**: Evie breaks language barriers, understanding and responding in multiple languages based on your business requirements.
|
||||
|
||||
## Key Features and Benefits
|
||||
|
||||
### Enhanced Customer Experience
|
||||
The tables have turned, and a new human-computer interaction paradigm is taking the world by storm. In the recent past
|
||||
end users (internal or external) were left to interact with information — abundantly available in digital format — having
|
||||
to learn to talk to computers. Now, we can interact with information systems by using human language. Evie fully embraces
|
||||
this new paradigm and transforms the way people interact with your business. Moreover, Evie is available 24/7, 365 days a year,
|
||||
and can be accessed from anywhere.
|
||||
|
||||
### Boosted Internal Productivity
|
||||
Internally, Evie acts as a conversational hub for your organisation. Employees can quickly find policies, data, and other
|
||||
resources using simple language, reducing time spent searching for information and improving productivity. Evie also exposes
|
||||
an API, enabling you to integrate Evie into your internal tools.
|
||||
|
||||
### Expertise On Demand
|
||||
Evie serves as an always-on expert assistant, making specialised knowledge instantly accessible across your organisation.
|
||||
This democratises access to expertise and allows your human experts to focus on high-value tasks.
|
||||
|
||||
### Automated Tasks
|
||||
Throughout their history, computers have enabled automation of tasks. LLMs and AI Agents allow for deeper automation,
|
||||
especially in cases where human-like interactions are essential. This is where Evie steps in. It doesn't aim to replace
|
||||
existing technology. It enables to automate tasks that are very dependent on human language, integrating with already
|
||||
existing technology, improving internal productivity and reducing human error.
|
||||
|
||||
## Why Choose Evie?
|
||||
|
||||
Evie is more than a chatbot; she’s an intelligent information assistant designed to adapt to your needs:
|
||||
- **Transparency**: Evie provides citations for her answers, enabling users to verify information at its source.
|
||||
- **Customization**: From integration with specific platforms to tailoring conversational styles, Evie is built to align with your unique environment.
|
||||
- **Continuous Improvement**: Evie evolves with your business, adapting to new information and changing requirements effortlessly.
|
||||
|
||||
## How Does Evie Work?
|
||||
|
||||
At the heart of Evie, we use state of the art technology to automate beyond classic systems.
|
||||
|
||||
### Retrieval-Augmented Generation (RAG)
|
||||
Retrieval-Augmented Generation (RAG) is a powerful technique that enables us to ensure Evie's interactions are embedded
|
||||
in your organisation's information (when required). It prevents the system from ***hallucinating***.
|
||||
Think of Evie as a hyper-intelligent librarian, organising your knowledge in a way that makes it easy to find relevant information.
|
||||
As a librarian, Evie has some essential talents:
|
||||
|
||||
1. **Efficient Knowledge Storage**: Evie stores the information you offer her (html, pdfs, audio, ...) intelligently in the library. She stores the information semantically, i.e. Evie understands the content you offer her, and indexes your information as such.
|
||||
2. **Efficient Knowledge Retrieval**: Once stored, Evie has the ability to semantically retrieve relevant information from the library for a given question, task, ...
|
||||
3. **Real-Time Updates**: As you add new information, Evie incorporates it seamlessly into her responses.
|
||||
4.
|
||||
|
||||
### Agentic AI
|
||||
|
||||
Agentic AI is a powerful technique that enables us to automate beyond classic systems. It allows Evie to perform smart
|
||||
actions based on your information or based on the conversation. Evie is a platform that allows our partners to transform
|
||||
their business ideas into intelligent specialists. As such, the Evie's functionality is continuously evolving.
|
||||
Some examples of its capabilities are:
|
||||
|
||||
1. **Knowledge Retrieval**: When asked a question or given a task, Evie searches your knowledge base for the most relevant information and provides the end user contextual responses.
|
||||
2. **
|
||||
|
||||
## Ready to Transform Information Access?
|
||||
|
||||
Whether you aim to:
|
||||
- Turn your website into an interactive knowledge hub,
|
||||
- Optimize your intranet for streamlined internal processes,
|
||||
- Empower your teams with instant access to expertise, or
|
||||
- Have tasks you want to automate
|
||||
|
||||
Evie is the intelligent, adaptable solution you’ve been looking for.
|
||||
Reference in New Issue
Block a user