Setting Up Knowledge Sources
This guide covers how to set up and configure knowledge sources for your ept AI chatbot. Knowledge sources are the foundation of your AI's intelligence - they contain the information your chatbot will use to provide accurate, helpful responses to users.
Overview
Setting up knowledge sources involves:
- Content Preparation: Organizing and preparing your content for AI consumption
- Knowledge Source Creation: Adding your content to the ept AI system
- Knowledge Source Configuration (KSC): Grouping sources for different use cases
- Testing and Validation: Ensuring your AI can access and use the content effectively
Prerequisites
Before setting up knowledge sources, ensure you have:
- Administrator Access: You need admin privileges to configure knowledge sources
- Content Ready: Prepare your documentation, FAQs, product information, and other content
- Use Case Defined: Understand what your chatbot should help users accomplish
- Content Strategy: Plan how to organize content for different audiences and purposes
Step 1: Prepare Your Content
Content Organization Strategy
Organize your content into logical categories based on your chatbot's purpose:
For Customer Support Chatbots:
- Product Documentation: User guides, technical specifications, feature descriptions
- Troubleshooting Guides: Common issues, error messages, and solutions
- FAQs: Frequently asked questions and their answers
- How-to Guides: Step-by-step instructions for common tasks
- Contact Information: Support channels, escalation procedures
For Sales Chatbots:
- Product Information: Features, benefits, specifications
- Pricing Information: Plans, packages, pricing tiers
- Case Studies: Customer success stories and testimonials
- Competitive Information: Comparison with alternatives
- Sales Process: Qualification criteria, next steps
For Internal Knowledge Bots:
- Company Policies: HR policies, procedures, guidelines
- Process Documentation: Workflows, standard operating procedures
- Training Materials: Onboarding guides, best practices
- Resource Information: Tools, systems, and access procedures
Content Format Requirements
ept AI supports multiple content formats:
Document Files:
- PDF: User manuals, technical documentation, reports
- DOC/DOCX: Word documents, policies, procedures
- TXT: Plain text files, simple documentation
- CSV: Structured data, lists, tables
Web Content:
- URLs: Links to documentation, knowledge bases, websites
- Web Pages: Direct content from your website or intranet
- API Endpoints: Dynamic content from databases or systems
Images and Media:
- Images: Screenshots, diagrams, charts (with OCR processing)
- Scanned Documents: PDFs of printed materials
Content Quality Guidelines
Accuracy and Currency:
- Ensure all information is current and factually correct
- Update content regularly to reflect changes in products, policies, or procedures
- Remove outdated information that could mislead users
Clarity and Readability:
- Use clear, concise language appropriate for your target audience
- Avoid jargon unless your audience is technical
- Structure content with headings, lists, and clear sections
- Use consistent terminology throughout your content
Completeness and Relevance:
- Provide comprehensive information for each topic
- Include context and background information where helpful
- Focus on content that addresses common user questions and needs
- Ensure content is relevant to your chatbot's purpose
Step 2: Create Knowledge Sources
Adding Knowledge Sources
- Navigate to Configuration: Go to Configuration > Knowledge Sources in your ept AI dashboard
- Create New Source: Click "Create Knowledge Source"
- Configure Basic Information:
{
"basic_info": {
"name": "Product User Guide",
"description": "Complete user guide for our flagship product",
"source_type": "PDF",
"confidentiality": "public",
"tags": ["product", "user-guide", "documentation"]
}
}
Source Type Configuration
For File Uploads:
- Upload File: Select and upload your document
- File Validation: Ensure the file is readable and properly formatted
- Content Extraction: The system will extract text content automatically
- Processing Status: Monitor the processing status in the dashboard
For URL Sources:
{
"url_config": {
"url": "https://your-domain.com/documentation",
"authentication": "none", // or "basic", "oauth"
"credentials": {
"username": "optional_username",
"password": "optional_password"
},
"crawl_depth": 2, // How deep to crawl linked pages
"include_patterns": ["*.html", "*.pdf"],
"exclude_patterns": ["*/admin/*", "*/private/*"]
}
}
For Database Connections:
{
"database_config": {
"connection_string": "your_connection_string",
"query": "SELECT * FROM knowledge_base WHERE status = 'active'",
"refresh_schedule": "daily",
"authentication": "connection_string" // or "environment_variables"
}
}
Organizing Knowledge Sources
Create Logical Groups:
- Public Content: Marketing materials, general product information
- Internal Documentation: Company policies, internal procedures
- Technical Documentation: API docs, technical specifications
- Support Resources: Troubleshooting guides, FAQs
Use Descriptive Names:
Product-User-Guide-v2.1
Support-FAQs-Q4-2024
HR-Policies-Employee-Handbook
Technical-API-Documentation
Add Metadata:
- Tags: Use consistent tags for easy filtering and organization
- Categories: Group sources by content type or audience
- Version Information: Track content versions and update dates
- Access Control: Mark sources as public, internal, or confidential
Step 3: Create Knowledge Source Configurations (KSCs)
Understanding KSCs
Knowledge Source Configurations (KSCs) are groups of knowledge sources that define what information your chatbot can access for specific use cases. They provide:
- Content Organization: Logical grouping of related knowledge sources
- Access Control: Different KSCs for different user types or channels
- Performance Optimization: Efficient content retrieval and processing
- Confidentiality Management: Control over sensitive information access
Creating KSCs
- Navigate to KSC Configuration: Go to Configuration > Knowledge Source Configurations
- Create New KSC: Click "Create Knowledge Source Configuration"
- Configure the KSC:
{
"ksc_config": {
"name": "Customer Support KSC",
"description": "Knowledge sources for customer support and troubleshooting",
"confidentiality": "public",
"knowledge_sources": [
"Product-User-Guide-v2.1",
"Support-FAQs-Q4-2024",
"Troubleshooting-Guide",
"Contact-Information"
],
"source_priority": {
"Product-User-Guide-v2.1": 1,
"Support-FAQs-Q4-2024": 2,
"Troubleshooting-Guide": 3,
"Contact-Information": 4
}
}
}
Common KSC Types
Customer Support KSC:
{
"customer_support_ksc": {
"purpose": "Handle customer support inquiries and troubleshooting",
"sources": [
"product-documentation",
"troubleshooting-guides",
"faqs",
"contact-information"
],
"confidentiality": "public",
"response_style": "helpful_and_supportive"
}
}
Sales Team KSC:
{
"sales_ksc": {
"purpose": "Support sales conversations and lead qualification",
"sources": [
"product-specifications",
"pricing-information",
"case-studies",
"competitive-analysis"
],
"confidentiality": "internal",
"response_style": "informative_and_persuasive"
}
}
Internal Knowledge KSC:
{
"internal_ksc": {
"purpose": "Help employees with internal processes and policies",
"sources": [
"hr-policies",
"process-documentation",
"training-materials",
"resource-information"
],
"confidentiality": "internal",
"response_style": "professional_and_efficient"
}
}
KSC Best Practices
Purpose-Driven Design:
- Create KSCs for specific use cases and audiences
- Include only sources relevant to the KSC's purpose
- Consider the user's context and needs when selecting sources
Content Prioritization:
- Order sources by importance (most relevant first)
- Consider source freshness and accuracy
- Balance comprehensive coverage with performance
Confidentiality Management:
- Ensure KSC confidentiality matches content sensitivity
- Separate public and internal content clearly
- Review access permissions regularly
Performance Optimization:
- Limit KSC size for faster response times
- Use specific sources rather than broad categories
- Monitor and adjust based on usage patterns
Step 4: Test Your Knowledge Sources
Initial Testing
Basic Functionality Test:
- Create Test Questions: Develop questions that should be answerable from your knowledge sources
- Test Knowledge Access: Verify the AI can find and use information from your sources
- Check Response Quality: Review accuracy, relevance, and helpfulness of responses
- Validate Content Coverage: Ensure the AI can handle questions across all knowledge areas
Sample Test Questions:
- "How do I reset my password?"
- "What are your business hours?"
- "How much does the premium plan cost?"
- "What's your return policy?"
Quality Assurance Checklist
Content Accuracy:
- All information is current and correct
- No outdated or conflicting information
- Technical details are accurate
- Contact information is up to date
Response Quality:
- Responses are factually correct
- Responses address the actual question
- Information is complete and helpful
- Responses are consistent for similar questions
Content Coverage:
- AI can handle common user questions
- All major topics are covered
- No significant knowledge gaps
- Content is appropriate for the target audience
Troubleshooting Common Issues
AI Can't Find Information:
- Check if the knowledge source was processed successfully
- Verify the source contains the expected content
- Ensure the source is included in the appropriate KSC
- Check source formatting and readability
Incorrect or Outdated Responses:
- Update the knowledge source with current information
- Remove or archive outdated content
- Verify source processing captured all content
- Check for conflicting information across sources
Poor Response Quality:
- Review and improve source content quality
- Ensure content is well-structured and clear
- Add more comprehensive information to sources
- Consider adding more specific sources for detailed topics
Step 5: Optimize and Maintain
Content Maintenance
Regular Updates:
- Schedule regular content reviews and updates
- Update information when products, policies, or procedures change
- Remove outdated content that could mislead users
- Add new content based on user questions and feedback
Quality Monitoring:
- Track which knowledge sources are most used
- Monitor response quality and user satisfaction
- Identify knowledge gaps based on user questions
- Gather feedback from users and support teams
Performance Optimization:
- Monitor KSC performance and response times
- Adjust source priorities based on usage patterns
- Optimize content structure for better AI understanding
- Consider splitting large sources into smaller, more focused ones
Advanced Configuration
Source Prioritization:
{
"source_priority_config": {
"high_priority": ["current-product-guide", "active-faqs"],
"medium_priority": ["general-information", "contact-details"],
"low_priority": ["archived-content", "legacy-documentation"]
}
}
Content Filtering:
{
"content_filtering": {
"include_patterns": ["*.html", "*.pdf", "*.docx"],
"exclude_patterns": ["*/draft/*", "*/archive/*"],
"content_types": ["documentation", "faqs", "guides"],
"date_range": {
"start_date": "2023-01-01",
"end_date": "current"
}
}
}
Next Steps
Once your knowledge sources are set up and tested:
- Integrate the Chatbot - Add the chatbot to your applications
- Configure the Design - Customize the visual appearance and user experience
- Set up Continuous Improvement - Monitor and optimize performance
Related Documentation
- Knowledge Sources - Detailed knowledge source configuration
- Knowledge Source Configurations - Advanced KSC management
- Configuration Overview - All configuration options