# Document Transcription System Overview (Version 4)

This project is a personal-scale application for transcribing, organizing, and preserving historical documents, images, and related people records.

## Start Here

Read [architecture_v4.md](architecture_v4.md) first for the technical overview and system design.

## Core Capabilities

- Folder and multi-image ingestion into sequential `Source` pages under a single `Document`.
- Parallel asynchronous AI vision transcription using Python `asyncio` bounded by rate limits.
- Portable relational storage using SQLModel and SQLAlchemy across SQLite and PostgreSQL.
- Complete prompt and response provenance for every transcription job and page execution.
- File-integrity tracking through SHA-256 hashing and stored file sizes.
- Historical `Person` management with many-to-many document links and extensible relationship roles.
- Registry-driven `DocumentType` classification with stable codes and controlled selection.
- Inline human revision of transcribed pages while preserving immutable machine output.
- Partial-failure recovery for multi-page jobs.
- Cross-platform operational workflows driven by Python-based tooling.

## Technical Stack

- Application Web Framework: FastAPI + NiceGUI
- Persistence Engine: SQLModel / SQLAlchemy
- Data Validation and Schemas: Pydantic V2
- Concurrency and Workers: Python `asyncio`
- Vision Providers: OpenAI, Anthropic, and OpenRouter adapters

## Core Documentation Index

- [System Architecture](architecture_v4.md)
- [System Requirements](requirements_v4.md)
- [Data Model](schema_v4.md)
- [Error Handling Policy](error_handling_v4.md)

## Transition Documents

- [Scope Boundary](scope_boundary_v4.md)
- [Implementation Plan](implementation_plan_v4.md)