Contorium introduces a structured system for representing and querying software project intelligence.
Architecture is divided into:
- PIL (storage layer)
- CIL (cognitive layer)
- LLM provider layer (optional) ⸻
- System Design User ↓ CIL Query Layer ↓ Cognitive Kernel ↓ PIL (Event-based storage) ↓ .contora/ ⸻
- PIL — Deterministic Source of Truth PIL stores structured artifacts:
- Cognitive Events
- Decision Graph (ADR lifecycle)
- Snapshots (time-based state)
- Knowledge Graph
- Module History
- Health Signals Key Principle PIL is fully deterministic. No LLM involvement is required. ⸻
- CIL — Query & Reasoning Layer CIL provides structured access to PIL: Supported intents:
- history
- decision
- state
- entity
- time_travel
- story
- essence
- dna
- health
- next actions All requests are routed through: runCognitiveKernel() ⸻
- Kernel Architecture The kernel ensures:
- single routing entry
- deterministic aggregation
- structured output formatting
- traceable execution path ⸻
- LLM Provider Layer Contorium introduces an optional abstraction layer for LLM integration. Supported providers:
- OpenAI
- Anthropic
- Gemini
- OpenRouter
- Ollama Configuration: { "provider": "openai", "model": "gpt-5", "enabled_modules": [ "why", "story", "essence", "dna" ] } ⸻
- LLM Usage Scope LLMs are ONLY used for:
- Why explanation generation
- Project story synthesis
- Essence compression
- DNA summarization
- Suggested questions generation They are NOT used for:
- event processing
- snapshot generation
- decision graph construction
- health computation
- knowledge graph building ⸻
- Architecture Principle Contorium enforces a strict separation: Deterministic Layer
- PIL
- Event system
- Graphs
- Snapshots Cognitive Layer
- CIL
- Kernel routing Probabilistic Layer
- LLM interpretation only ⸻
- Conclusion Contorium defines a new system class: A queryable intelligence runtime for software evolution. It does not replace Git. It extends it into cognitive space. https://www.contorium.dev/ https://github.com/ContoriumLabs/contorium
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