Setting Up Knowledge Sources
Setting up knowledge sources, KSCs, and content to prepare the ept AI chatbot for production.
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-v2.1Support-FAQs-Q4-2024HR-Policies-Employee-HandbookTechnical-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