System Architecture

2.1 Core Brain Architecture

BrainController

File: core/brain/brain_controller.py

The BrainController is the central orchestrator that owns every subsystem. It initializes more than 40 components, constructs the 18-stage pipeline, and manages boot sequencing, knowledge loading, memory persistence, and post-pipeline quality enforcement.

Key attributes (40+)

• Core: config, memory_manager, knowledge_router, reasoning_engine, context_manager, strategy_manager, meta_learning_engine
• Engines: hwa_engine (lazy), pbe_engine (lazy), dcl_engine, heartbeat_engine
• Personality: personality_engine
• Security: security_engine, ethics_engine, safety_layer
• Pipeline: pipeline (PipelineOrchestrator with 18 stages)
• CI components: 26 conversational intelligence components
• Agents: agent_registry (5 registered agents)
• Creative: quality_guardrail, emotion_palette_mapper (lazy), music_prompt_builder (lazy)
• Persistence: _storage_backend (SQLite)
• AI-OS: aios_kernel

Complexity

__init__: O(1) for fixed-size subsystem construction
process_request: O(Σ s_i) over pipeline stages

Post-pipeline flow

1. Output stabilization (OutputStabilizer)
2. Language enforcement (LanguageEnforcerV2)
3. Style engine (skipped for greet/clarify/emotional)
4. Safety check (SafetyLayer, always applies)
5. Quality guardrail gate (skipped for greet/clarify/emotional)
6. Memory auto-store (user input + response)

BrainState

File: core/brain/brain_state.py (@dataclass(frozen=True, slots=True))

An immutable state object that flows through the pipeline. Each stage produces a new copy via with_field() rather than mutating in place. The dataclass carries more than 30 fields.

Valid emotions

neutral, happy, sad, angry, anxious, grateful, confused, curious, philosophical, personal

Valid intents

greet, clarify, code, architect, analyze, emotional, command, explain, question, unknown

Intent priority order (for tie-breaking)

clarify (0), greet (1), code (2), architect (3), analyze (4),
emotional (5), command (6), explain (7), question (8), unknown (9)

BrainConfig

File: core/brain/brain_config.py (@dataclass(frozen=True, slots=True))

18-Stage Cognitive Pipeline

File: core/pipeline/pipeline_orchestrator.py

Core Subsystems

Memory System

• MemoryManager: Embedding-based memory backed by CRC32 hash vectors using a 256-dimensional bag-of-nibbles representation. An LRU cache sits in front of retrieval, with keyword-overlap search as a fallback path.
• MemoryStore: In-memory storage exposing add(), search(), all_items(), count(), save(), and load().
• MemoryItem: A frozen dataclass holding content, embedding, timestamp, access_count, and tags.
• Automatically stores user input after the pipeline completes, which is what enables multi-turn recall across a session.
• Persists to SQLite through the StorageBackend abstraction.

Knowledge System

• KnowledgeBackend: CRC32-based vector embeddings with an LRU cache and BM25-style retrieval scoring.
• KnowledgeRouter: Performs domain-filtered retrieval first, then falls back to an unfiltered search when the domain filter returns too few results.
• KnowledgeLoader: Loads knowledge from disk into memory at boot, capping at 50 chunks per domain and 2000 characters per chunk.
• Loads 21,917 items at boot from E:\Data\condrox\knowledge\.

Reasoning Engine

Symbolic reasoning engine with default rules loaded at initialization. Performs rule-based inference and ranks claims through ClaimRankerV2.

Strategy Manager

Selects a reasoning strategy using weighted context scoring. The weights are enriched at runtime by the MetaLearningEngine.

Meta-Learning Engine

Tracks strategy performance using an exponential moving average with alpha set to 0.3. The resulting weights feed back into the StrategyManager to bias future selection.

Security Engine

• Input: Detects injection attempts, enforces size limits, and blocks known malicious patterns before they reach the pipeline.
• Output: Scans generated text for PII including email addresses, phone numbers, and credit card numbers. Also checks for secret leakage and prompt injection echoes.

Ethics Engine

Enforces content policy by checking generated output against a list of blocked topics before delivery.

2.2 Conversational Intelligence (26 Components)

Directory: core/conversational/

All 26 components are implemented, tested, wired into the pipeline, and documented. There is no dead code in this layer.

Phase 2-A: Critical Stabilization (4 components)

Phase 2-B: Conversational Quality (5 components)

Phase 2-C: Observability & Safety (3 components)

Phase 2-D: Agent Coordination (3 components)

Phase 2-E: Advanced CI (7 components)

Phase 2-F: System-Level Properties (4 components)

2.3 Agent System (5 Modes)

Directory: core/agents/

Pipeline integration: Stage08bAgentExecution runs the mode-specific agent, merges reasoning output with retrieved evidence, and sets synthesized_output for Stage09 to consume during synthesis.

2.4 AI-Operating System (AI-OS)

Directory: core/os/

2.7 Word Identity System (Phase 14)

Directory: core/word_identity/

Architecture

Input Text → Tokenizer → Word Lookup (O(1)) → Intent Aggregation → Softmax
                                    ↓                ↓
                              Emotion Detection   Domain Routing

JSON Stores

Word Identity Record Structure

{
  "word": {
    "type": "concept|action|emotion|language|...",
    "category": "programming|architecture|emotion|...",
    "intent": "code|explain|analyze|architect|emotional|greet|...",
    "intent_weight": 0.0-1.0,
    "emotion": "neutral|sad|angry|anxious|happy|...",
    "meaning": "Human-readable definition"
  }
}

Pipeline Integration