Release 1.0

Changelog: Release 1.0

Added:

• Private Multimodal RAG: Introduced the ability to process and interact with both text documents and visual media (PNG/JPG) fully on-device.

• Dual-Pass Vision Engine:

  • Semantic Pass: Integrated moondream to interpret image layouts, UI structures, and diagrams.

  • Syntax Pass: Integrated Tesseract OCR for high-fidelity extraction of code blocks and technical text from images.

• Config-Driven Architecture:

  • config/parameters.json: Externalized control for LLM selection, VRAM-optimized chunking, and inference settings.

  • config/prompts.json: Customizable system personas and RAG response templates.

• Unified Deployment Script: Created run.sh to automate system diagnostics, Ollama model pulls, and container orchestration.

• Local Vector Storage: Implemented persistent storage using ChromaDB for fast semantic retrieval.

• User Management: Integrated MongoDB for secure session handling and user authentication.

Optimized:

• Hardware Balancing: Tuned the engine for 4GB VRAM hardware (GTX 1050 Ti), utilizing llama3.2:1b for efficient local inference.

• Project Structure: Modularized code into src/, utils/, and config/ directories for better maintainability.

Fixed:

• Ollama Network Bridge: Resolved connectivity issues between Docker containers and the host Ollama service on Linux systems.

• Context Integrity: Optimized chunking logic to ensure visual descriptions and extracted text remain linked in the vector database.

Pre-release Version 0.1

Pre-release Version 0.1

Features:

• On device document intelligence capabilities for .txt and .pdf files.
• User Login and Chat History support.
• On device VectorDB storage which is used for RAG context.