Establish initial project architecture

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# 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
---
# High-Level Pipeline
Recording
↓
Transcription
↓
Speaker Diarization
↓
Working Transcript
↓
LLM Analysis
↓
Knowledge Extraction
↓
Export
---
# Domain Model
Meeting
│
├── Recording
├── Transcript
│ ├── Canonical
│ └── Working
├── Speakers
├── Participants
├── AI Artifacts
├── Knowledge Objects
├── Attachments
└── Exports
---
# Module Responsibilities
## Recorder
Responsible only for capturing audio.
Input:
None
Output:
Recording
---
## 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
Recording
↓
Canonical Transcript
↓
Working Transcript
↓
AI Artifacts
↓
Knowledge Objects
↓
Exports
---
# 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