180 lines
2.0 KiB
Markdown
180 lines
2.0 KiB
Markdown
# Architecture
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## Purpose
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The Meeting Knowledge Assistant transforms recorded meetings into structured organizational knowledge through a modular processing pipeline.
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---
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# Design Principles
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- Architecture first
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- Offline first where practical
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- Immutable source data
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- Replaceable AI components
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- Small, focused modules
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- Explicit interfaces
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- Reproducible AI outputs
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---
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# High-Level Pipeline
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Recording
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↓
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Transcription
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↓
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Speaker Diarization
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↓
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Working Transcript
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↓
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LLM Analysis
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↓
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Knowledge Extraction
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↓
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Export
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---
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# Domain Model
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Meeting
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│
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├── Recording
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├── Transcript
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│ ├── Canonical
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│ └── Working
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├── Speakers
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├── Participants
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├── AI Artifacts
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├── Knowledge Objects
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├── Attachments
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└── Exports
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---
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# Module Responsibilities
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## Recorder
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Responsible only for capturing audio.
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Input:
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None
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Output:
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Recording
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---
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## Transcription
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Responsible only for speech-to-text conversion.
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Input:
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Recording
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Output:
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Canonical Transcript
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---
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## Diarization
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Responsible only for speaker identification.
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Input:
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Recording + Canonical Transcript
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Output:
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Working Transcript
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---
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## LLM
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Responsible for semantic analysis.
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Input:
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Transcript
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Output:
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AI Artifacts
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---
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## Knowledge Extraction
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Responsible for creating structured knowledge.
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Input:
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AI Artifacts
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Output:
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Knowledge Objects
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---
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## Export
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Responsible for creating user-facing documents.
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Input:
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Knowledge Objects
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Output:
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Markdown
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PDF
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DOCX
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---
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# Artifact Lifecycle
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Recording
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↓
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Canonical Transcript
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↓
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Working Transcript
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↓
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AI Artifacts
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↓
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Knowledge Objects
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↓
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Exports
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---
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# Storage Strategy
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The domain model is independent of the storage backend.
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Possible implementations:
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- File System
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- SQLite
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- PostgreSQL
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- Cloud Storage
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---
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# Future Extensions
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- Live transcription
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- Video processing
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- OCR
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- Semantic search
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- Knowledge graph
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- Company glossary
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- Multi-language meetings
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- Local LLM support |