

Overview
Semantic Search provides an intelligent search experience that goes beyond simple file name matching. Search for errors, ask questions about models, or find files by context - all processed in real-time with no pre-built indexes.How It Works
The search bar understands natural language queries and semantic context:- Error Search: Type error messages to quickly locate the problematic files
- Contextual Queries: Ask questions about models and their functionality
- File Name Search: Traditional file name searches work seamlessly
- Macro Discovery: Find macros by describing what they do
Performance
Medium Projects
Medium Projects
Under 500ms - Fast results for typical dbt projects
Large Projects
Large Projects
Under 5 seconds - Even projects with 1000s of files return results quickly
Real-Time Processing
No indexes stored - Everything is computed in memory to ensure the most up-to-date results. Changes to your project are immediately searchable without rebuilding indexes.
Search Examples
Error Detection
- Type error messages from your dbt runs
- The search will identify which specific files contain the errors
- Get direct navigation to problematic code
Model Questions
- “Find the model that calculates customer lifetime value”
- “Show me models that use the orders table”
- “Which model handles revenue calculations”
Macro Discovery
- “Find macro that formats dates”
- “Show me the macro for data quality checks”
- “Macro that handles null values”
File Search
- Standard file name searches work alongside semantic queries
- Partial names and patterns are supported
- Case-insensitive matching
Key Features
- Context-Aware: Understands the purpose and functionality of your models
- Error-Focused: Quickly pinpoint files causing build failures
- No Maintenance: No indexes to rebuild or maintain
- Always Current: Searches reflect your latest code changes immediately
- Natural Language: Ask questions in plain English
Try combining different search approaches - you can search for errors, then follow up with contextual questions about the affected models.