Enhanced GitHub Data Ingestion and SQLite Management

📅 2025-08-18 — Session: Enhanced GitHub Data Ingestion and SQLite Management

🕒 03:00–03:50
🏷️ Labels: Github, Sqlite, Python, Data Management, Debugging
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance data ingestion from GitHub repositories and manage SQLite databases effectively, focusing on recursive file loading, code parsing, error handling, data cleanup, and performance debugging.

Key Activities

• Recursive File Loading: Implemented strategies for full recursive coverage of files using the GitHub Trees API and GithubRepositoryReader.
• Code Parsing: Utilized LlamaIndex’s CodeSplitter for efficient Python code parsing and docstring extraction.
• Error Handling: Addressed Tree-sitter ImportError in LlamaIndex’s CodeSplitter by exploring installation of language packs and alternative parsers.
• Data Cleanup: Developed a workflow for clean removal of repository records from Chroma embeddings, SQLite metadata, and vector caches.
• SQLite Management: Debugged SQLite tables related to Chroma, including table inspection and record deletion.
• Database Performance: Investigated performance issues in SQLite and Chroma, identifying potential script stalls and debugging strategies.

Achievements

• Successfully implemented recursive file loading and efficient code parsing techniques.
• Resolved ImportError issues with Tree-sitter in LlamaIndex.
• Established a comprehensive procedure for data cleanup across multiple layers.
• Improved SQLite table management and performance debugging methods.

Pending Tasks

• Further testing of the recursive file loading and data cleanup procedures to ensure robustness.
• Explore additional performance optimization techniques for SQLite and Chroma integration.