# Knowledge Base Example
This example shows how to build a searchable documentation system with rich metadata for organization and filtering.
## Use Case
You're building a company knowledge base with:
- Documentation from multiple teams
- Articles with different topics and difficulty levels
- Content that needs to be searchable and filterable
## What You'll Learn
- Organizing documents with metadata
- Using metadata for categorization
- Filtering searches by metadata fields
- Building a scalable knowledge base structure
## Setup
### 1. Create the Collection
```
Create a collection named "company-kb"
```
### 2. Add Structured Documents
```
Add these documents to company-kb:
- id: "eng-001", text: "Our API uses REST principles with JSON payloads. Authentication is handled via JWT tokens in the Authorization header.", metadata: {"team": "engineering", "topic": "api", "difficulty": "intermediate", "category": "technical"}
- id: "eng-002", text: "To deploy to production, merge your PR to main. The CI/CD pipeline automatically runs tests and deploys if all checks pass.", metadata: {"team": "engineering", "topic": "deployment", "difficulty": "beginner", "category": "process"}
- id: "hr-001", text: "New employees receive benefits information during onboarding. Health insurance enrollment must be completed within 30 days.", metadata: {"team": "hr", "topic": "benefits", "difficulty": "beginner", "category": "policy"}
- id: "hr-002", text: "Performance reviews occur quarterly. Managers should prepare feedback and schedule 1-on-1 meetings two weeks in advance.", metadata: {"team": "hr", "topic": "performance", "difficulty": "beginner", "category": "process"}
- id: "sales-001", text: "Our enterprise pricing model includes volume discounts for contracts over $100k annually. Custom SLAs are available.", metadata: {"team": "sales", "topic": "pricing", "difficulty": "advanced", "category": "business"}
- id: "sales-002", text: "The sales pipeline has four stages: Lead, Qualified, Proposal, and Closed. Update Salesforce after each customer interaction.", metadata: {"team": "sales", "topic": "pipeline", "difficulty": "beginner", "category": "process"}
```
## Search Examples
### Basic Search (No Filters)
```
Search company-kb for "how do I deploy code"
```
Expected: Returns deployment-related docs (eng-002 likely ranks highest)
### Filter by Team
```
Search company-kb for "process documentation" with filter {"must": [{"key": "team", "match": {"value": "engineering"}}]}
```
Returns only engineering team documents.
### Filter by Difficulty
```
Search company-kb for "getting started" with filter {"must": [{"key": "difficulty", "match": {"value": "beginner"}}]}
```
Returns beginner-friendly documentation.
### Multiple Filters (AND)
```
Search company-kb for "company procedures" with filter {"must": [{"key": "category", "match": {"value": "process"}}, {"key": "difficulty", "match": {"value": "beginner"}}]}
```
Returns beginner process documents only.
### Filter by Topic
```
Search company-kb for "pricing information" with filter {"must": [{"key": "team", "match": {"value": "sales"}}]}
```
Restricts search to sales team content.
## Metadata Design Best Practices
### 1. Consistent Schema
Use the same metadata fields across all documents:
```json
{
"team": "string",
"topic": "string",
"difficulty": "beginner|intermediate|advanced",
"category": "technical|process|policy|business"
}
```
### 2. Hierarchical Organization
Consider nesting metadata for complex taxonomies:
```json
{
"team": "engineering",
"subteam": "backend",
"topic": "api",
"subtopic": "authentication"
}
```
### 3. Multiple Tags
Use arrays for multi-category documents:
```json
{
"tags": ["api", "security", "authentication"],
"relevant_teams": ["engineering", "security"]
}
```
### 4. Timestamps and Versioning
Track freshness and versions:
```json
{
"created_at": "2024-01-15",
"updated_at": "2024-03-20",
"version": "2.1",
"status": "published"
}
```
## Scaling Your Knowledge Base
### Add More Content Types
- Code examples with language tags
- Video transcripts with duration metadata
- Meeting notes with attendees and dates
- Product specs with version numbers
### Implement Access Control
Use metadata for permissions:
```json
{
"visibility": "public|internal|confidential",
"authorized_teams": ["engineering", "leadership"]
}
```
Then filter searches based on user permissions.
### Track Usage
Add metadata for analytics:
```json
{
"views": 0,
"last_accessed": null,
"author": "user@company.com"
}
```
## Maintenance
### Update Documents
To update content, delete and re-add:
```
Delete documents ["eng-001"] from company-kb
Add these documents to company-kb:
- id: "eng-001", text: "Updated API documentation...", metadata: {...}
```
### Archive Old Content
Use status metadata to hide outdated docs:
```json
{
"status": "archived",
"archived_date": "2024-12-01"
}
```
Then filter searches to exclude archived content:
```
Search company-kb for "deployment" with filter {"must_not": [{"key": "status", "match": {"value": "archived"}}]}
```
## Clean Up
```
Delete collection "company-kb"
```
## Next Steps
- [Advanced Filtering Examples](../filters/) - Learn complex filter patterns
- See the main README for information on batch document operations
