163 lines
1.8 KiB
Markdown
163 lines
1.8 KiB
Markdown
# Project Knowledge
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## Vision
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The project creates a complete pipeline that transforms spoken meetings into structured organizational knowledge.
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The transcript is the canonical source.
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AI-generated summaries are reproducible artefacts.
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---
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## Design Principles
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Offline-first where practical.
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Replaceable AI components.
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Vendor independence.
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Modular architecture.
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Small focused modules.
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Simple interfaces.
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---
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## Core Pipeline
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Recorder
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↓
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Transcription
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↓
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Speaker Identification
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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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Storage
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↓
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Export
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---
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## AI Components
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Recorder
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Responsible only for recording.
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No AI.
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Transcription
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Responsible only for speech-to-text.
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No summarization.
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Speaker Identification
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Responsible only for identifying speakers.
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Must not modify transcript text.
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---
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LLM Analysis
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Responsible for:
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- Summary
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- Decisions
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- Action Items
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- Risks
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- Questions
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- Knowledge extraction
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---
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Storage
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Stores:
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Audio
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Transcript
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Metadata
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AI Results
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Knowledge Objects
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---
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## Architectural Rule
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Every module has exactly one responsibility.
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---
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## Transcript Policy
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Never modify the original transcript.
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Corrections must create a new derived version.
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---
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## AI Output Policy
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Every AI output should be reproducible.
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Prompt version should be stored.
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Model should be stored.
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Timestamp should be stored.
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---
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## Long-Term Goal
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Every meeting becomes searchable organizational knowledge.
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No information should be lost after the meeting.
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---
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## Engineering Principles
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The project follows an architecture-first development approach.
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Before implementing a feature:
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- define the domain model
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- define module boundaries
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- document architectural decisions
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Implementation is intentionally delayed until the architecture is considered sufficiently stable. |