# Architecture

## Purpose

The Meeting Knowledge Assistant transforms recorded meetings into structured organizational knowledge through a modular processing pipeline.

---

# Design Principles

- Architecture first
- Offline first where practical
- Immutable source data
- Replaceable AI components
- Small, focused modules
- Explicit interfaces
- Reproducible AI outputs
- External recording and internal processing are separate responsibilities.
- The processing pipeline must not depend on OBS-specific metadata or behavior.
- Imported recordings must be treated like recordings from any other supported source.

---

## High-Level Pipeline

External Recorder
    ↓
Audio Import
    ↓
Recording Validation
    ↓
Meeting Storage
    ↓
Transcription
    ↓
Speaker Diarization
    ↓
Working Transcript
    ↓
LLM Analysis
    ↓
Knowledge Extraction
    ↓
Export

---

## Core Pipeline

External Recording

↓

Audio Import and Validation

↓

Transcription

↓

Speaker Diarization

↓

Working Transcript

↓

LLM Analysis

↓

Knowledge Extraction

↓

Storage and Export

# Domain Model

Meeting
│
├── Recording
├── Transcript
│     ├── Canonical
│     └── Working
├── Speakers
├── Participants
├── AI Artifacts
├── Knowledge Objects
├── Attachments
└── Exports

---

# Module Responsibilities

## Input and Ingest

Responsible for importing existing recordings into the application.

Initial reference source:

- OBS Studio

Initial supported formats:

- WAV

- FLAC

Responsibilities:

- validate the input file

- collect technical metadata

- calculate checksums

- copy or move the recording into the meeting directory

- create the initial Recording domain object

The ingest component must not perform transcription or modify the audio content.

## Recorder

The recorder module is reserved for a future integrated recording implementation.

It is not required for the MVP.

The initial application workflow uses externally created recordings, with OBS
Studio as the recommended reference recorder.

---

## Transcription

Responsible only for speech-to-text conversion.

Input:
Recording

Output:
Canonical Transcript

---

## Diarization

Responsible only for speaker identification.

Input:
Recording + Canonical Transcript

Output:
Working Transcript

---

## LLM

Responsible for semantic analysis.

Input:
Transcript

Output:
AI Artifacts

---

## Knowledge Extraction

Responsible for creating structured knowledge.

Input:
AI Artifacts

Output:
Knowledge Objects

---

## Export

Responsible for creating user-facing documents.

Input:
Knowledge Objects

Output:
Markdown
PDF
DOCX

---

## Artifact Lifecycle

```text
Imported Recording
    ↓
Validated Source Recording
    ↓
Canonical Transcript
    ↓
Working Transcript
    ↓
AI Artifacts
    ↓
Knowledge Objects
    ↓
Exports

---

## Initial Recording Strategy

The MVP does not implement platform-specific audio capture.

OBS Studio is the recommended reference recorder for online meetings.

The application initially processes existing WAV or FLAC recordings. Integrated

recording remains a future extension and must not be required by transcription,

diarization or analysis modules.

---

# Storage Strategy

The domain model is independent of the storage backend.

Possible implementations:

- File System
- SQLite
- PostgreSQL
- Cloud Storage

---

# Future Extensions

- Live transcription
- Video processing
- OCR
- Semantic search
- Knowledge graph
- Company glossary
- Multi-language meetings
- Local LLM support