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Architecture Overview

System Overview

Gemini Analyzer couples a Python FastAPI service with a Tkinter desktop client to deliver dual-mode project intelligence: cloud-powered analysis via Google Gemini 2.5 or fully local processing for sensitive codebases.

Application Modes

  • Desktop GUI — Tkinter interface that performs local scans and presents insights without leaving the workstation
  • REST API Service — FastAPI deployment with Docker packaging for CI/CD and enterprise integrations
  • Shared Core Library — Common analysis logic consumed by both the GUI and API layers

Key Components

  • Analysis Engine: Multi-language parsers, dependency mapping, and metrics collectors
  • AI Orchestrator: Routes requests to Gemini 2.5 or privacy-first local models
  • Storage Layer: Project metadata, cached insights, and optional SQL backend
  • Config & Validation: Pydantic settings plus strict schema validation

Integrations

  • Google Generative AI SDK for hosted intelligence when API keys are provided
  • Docker deployment for consistent production environments
  • CLI & Scripts to bootstrap analysis tasks and health checks

Security & Privacy

  • Local-only mode ensures sensitive repositories never leave the machine
  • Sanitised uploads for remote analysis with optional API key gating
  • Audit-ready logging across both GUI and API deployments
Summarised from the Gemini Analyzer project blueprint and README.