Local Engineering Journal RAG

A private, local-first RAG (Retrieval-Augmented Generation) tool to query engineering journals. It uses Ollama and LlamaIndex to perform Root Cause Analysis queries on your notes, linking specific issues to their dates.

⚡️ Prerequisites

1. uv (Python package manager): Install uv
2. Ollama: Install Ollama
3. Models: Pull the recommended models:

   ollama pull gemma3:12b    # Chat model
   # Optional: ollama pull deepseek-r1:14b

🛠️ Setup

1. Initialize the project dependencies:

   uv sync

🚀 Usage

1. Add Data

Export your Google Doc Journal:

• File > Download > Markdown (.md)
• Save the file as journal.md in this project folder.

2. Run Query

Ask questions about dates, issues, or fixes:

uv run main.py "When did the network latency issue happen and what was the fix?"