Sprint Goal: Build and implement the foundation for a code search system that accepts Git repositories, processes their content, and creates searchable indexes. The requirements that are addressed are shown below.
Key Deliverables:
- Repository URL input interface with validation
- Git repository fetching and processing service
- Code indexing system with vector DB integration
- Basic layered architectural foundation (Scala)
Task Board
Link to the main product backlog: Product Backlog
SBI ID | Task Description | User Story | PBI ID | Est. Points | Status |
---|---|---|---|---|---|
ARCHITECTURE & SETUP | |||||
S1.A1 | Set up basic layered project structure (Scala) | (Foundation) | F1 | 10 | ✓ |
S1.A2 | Define core interfaces between initial layers | (Foundation) | F1 | 5 | ✓ |
S1.A3 | Implement design patterns discussed during the course | (Foundation) | F1 | 10 | ✓ |
REPOSITORY INPUT (15 Points) | |||||
S1.1.1 | Create UI component for repository URL input | Repository Input | F2 | 5 | ✓ |
S1.1.2 | Implement URL validation with clear feedback | Repository Input | F2 | 3 | ✓ |
S1.1.3 | Create Git wrapper for repository fetching | Repository Input | F2 | 7 | ✓ |
CODE PROCESSING (20 Points) | |||||
S1.2.1 | Implement file traversal & content extraction | Code Processing | F2 | 8 | ✓ |
S1.2.2 | Add language detection & basic file filtering | Code Processing | F2 | 4 | ✓ |
S1.2.3 | Create code chunking strategy for indexing | Code Processing | F3 | 8 | ✓ |
SEARCH INDEXING (15 Points) | |||||
S1.3.1 | Implement code embedding generation (Langchain4J) | Search Indexing | F3 | 8 | ✓ |
S1.3.2 | Create vector database integration (Qdrant) using Langchain4j | Search Indexing | F3 | 7 | ✓ |