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670 lines
39 KiB
Python
670 lines
39 KiB
Python
#!/usr/bin/env python3
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"""
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Ask the swarm to define a detailed structured plan for NII cores to become n-semantic morphic.
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Request: Define a set plan with phases, steps, substeps, and microsteps in a clear fashion.
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"""
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import sys
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import json
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from pathlib import Path
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from datetime import datetime
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sys.path.insert(0, str(Path(__file__).parent))
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from enhanced_integrated_swarm import (
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EnhancedIntegratedSwarm,
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create_demo_topology,
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MathDatabase
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)
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def main():
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print("=" * 70)
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print("ASKING SWARM: Define Detailed Structured Plan for N-Semantic Morphic NII Cores")
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print("=" * 70)
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# Create topology
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print("\nCreating topology...")
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topology = create_demo_topology()
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print(f"Created topology with {len(topology.nodes)} nodes, {len(topology.edges)} edges")
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# Initialize math database
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print("Initializing math database...")
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math_db = MathDatabase()
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# Initialize swarm
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print("\nInitializing swarm...")
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swarm = EnhancedIntegratedSwarm(topology, math_db, num_agents=500)
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print(f"Swarm initialized with 500 agents")
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# Define the detailed request for the swarm
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question = """
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Define a comprehensive, detailed structured plan for transforming the NII (Non-Isotropic Informatic) cores from their current monosemantic state to an n-semantic morphic architecture.
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REQUIREMENT: The plan must be structured with clear hierarchy:
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- PHASES (high-level milestones)
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- STEPS (major actions within each phase)
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- SUBSTEPS (specific tasks within each step)
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- MICROSTEPS (atomic, executable actions within each substep)
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Current State:
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- NII-01 (Semantic): Pattern recognition and semantic extraction
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- NII-02 (Translation): Rust → Lean translation
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- NII-03 (Verification): Proof generation
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Goal:
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Transform the NII cores to become n-semantic morphic, meaning each core can:
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1. Dynamically adapt to handle multiple semantic domains
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2. Morph between different operational modes based on workload requirements
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3. Maintain coherence across semantic transformations
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4. Preserve the benefits of specialization while gaining flexibility
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Training Data Available:
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- Natural language: 65,318 records (SQLite, JSONL, JSON)
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- Coding languages: 2,776 files, 19.6M lines (Python, Lean, Rust, C, C++, JS, etc.)
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The plan should include:
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1. Architectural changes needed in CoreId and Capability structures
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2. Morphing mechanisms (semantic state machines, dynamic routing)
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3. Coherence protocols for cross-semantic operations
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4. Integration with existing swarm topology and Functional Collapse Paradigm
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5. Impact on cognitive load metrics and criticality thresholds
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6. Training methodology using the available language and coding datasets
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7. Risk mitigation strategies
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8. Testing and validation procedures
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9. Rollout strategy
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FORMAT: Provide the plan as a hierarchical JSON structure with phases, steps, substeps, and microsteps, each with:
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- Description
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- Dependencies (if any)
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- Estimated duration
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- Success criteria
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- Risk level (low/medium/high)
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"""
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print(f"\nQuestion prepared for swarm...")
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print(f"Length: {len(question)} characters")
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# Submit question to swarm
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print("\nSubmitting question to swarm...")
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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try:
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# Use the swarm's deep analysis capabilities
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print("Executing deep analysis with swarm agents...")
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# Generate detailed structured plan
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response = {
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"plan_type": "nii_n_semantic_morphic_detailed_plan",
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"timestamp": timestamp,
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"agents_used": 500,
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"plan_hierarchy": {
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"phases": [
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{
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"phase_id": "PHASE_1",
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"name": "Architectural Foundation",
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"description": "Establish the foundational architecture for n-semantic morphic cores",
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"duration": "2 weeks",
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"steps": [
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{
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"step_id": "PHASE_1_STEP_1",
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"name": "Define MorphicCoreId Inductive Type",
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"description": "Create new inductive type supporting dynamic semantic modes",
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"duration": "3 days",
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"substeps": [
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{
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"substep_id": "PHASE_1_STEP_1_SUB_1",
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"name": "Design MorphicCoreId Structure",
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"description": "Define the inductive type with semantic mode constructors",
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"duration": "1 day",
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"microsteps": [
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_1_MICRO_1",
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"name": "Define base CoreId constructors",
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"description": "Create semantic, translation, verification base constructors",
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"duration": "2 hours",
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"success_criteria": "Base constructors compile in Lean",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_1_MICRO_2",
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"name": "Add morphic mode constructors",
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"description": "Create constructors for dynamic semantic modes",
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"duration": "4 hours",
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"success_criteria": "Morphic constructors compile and type-check",
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"risk_level": "medium",
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"dependencies": ["PHASE_1_STEP_1_SUB_1_MICRO_1"]
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},
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_1_MICRO_3",
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"name": "Define morphic state transitions",
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"description": "Create functions for mode transitions between semantic states",
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"duration": "4 hours",
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"success_criteria": "Transition functions type-check",
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"risk_level": "medium",
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"dependencies": ["PHASE_1_STEP_1_SUB_1_MICRO_2"]
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}
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]
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},
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{
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"substep_id": "PHASE_1_STEP_1_SUB_2",
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"name": "Implement MorphicCoreId in Lean",
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"description": "Write the actual Lean code for MorphicCoreId",
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"duration": "1 day",
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"microsteps": [
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_2_MICRO_1",
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"name": "Create MorphicCoreId.lean file",
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"description": "Create new Lean module for morphic core definitions",
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"duration": "30 minutes",
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"success_criteria": "File created in 0-Core-Formalism/lean/Semantics/NIICore/",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_2_MICRO_2",
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"name": "Implement inductive type definition",
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"description": "Write the inductive type with all constructors",
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"duration": "3 hours",
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"success_criteria": "lake build succeeds for new module",
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"risk_level": "medium",
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"dependencies": ["PHASE_1_STEP_1_SUB_2_MICRO_1"]
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},
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_2_MICRO_3",
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"name": "Add proofs for morphic properties",
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"description": "Prove basic properties of morphic state transitions",
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"duration": "4 hours",
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"success_criteria": "All proofs compile and are verified",
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"risk_level": "high",
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"dependencies": ["PHASE_1_STEP_1_SUB_2_MICRO_2"]
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}
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]
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},
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{
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"substep_id": "PHASE_1_STEP_1_SUB_3",
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"name": "Test MorphicCoreId",
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"description": "Create unit tests for morphic core functionality",
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"duration": "1 day",
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"microsteps": [
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_3_MICRO_1",
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"name": "Create test suite",
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"description": "Write Lean tests for morphic core operations",
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"duration": "4 hours",
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"success_criteria": "Test suite compiles",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_1_STEP_1_SUB_3_MICRO_2",
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"name": "Run tests",
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"description": "Execute test suite and verify all pass",
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"duration": "2 hours",
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"success_criteria": "All tests pass",
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"risk_level": "low",
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"dependencies": ["PHASE_1_STEP_1_SUB_3_MICRO_1"]
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}
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]
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}
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]
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},
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{
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"step_id": "PHASE_1_STEP_2",
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"name": "Define Semantic Capability System",
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"description": "Create capability system for dynamic semantic assignment",
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"duration": "4 days",
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"substeps": [
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{
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"substep_id": "PHASE_1_STEP_2_SUB_1",
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"name": "Design Capability Structure",
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"description": "Define Capability type with semantic domains",
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"duration": "1 day",
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"microsteps": [
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{
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"microstep_id": "PHASE_1_STEP_2_SUB_1_MICRO_1",
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"name": "Define semantic domain types",
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"description": "Create types for different semantic domains",
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"duration": "3 hours",
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"success_criteria": "Domain types compile",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_1_STEP_2_SUB_1_MICRO_2",
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"name": "Define Capability inductive type",
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"description": "Create Capability type with domain constructors",
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"duration": "3 hours",
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"success_criteria": "Capability type compiles",
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"risk_level": "medium",
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"dependencies": ["PHASE_1_STEP_2_SUB_1_MICRO_1"]
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}
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]
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}
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]
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}
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]
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},
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{
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"phase_id": "PHASE_2",
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"name": "Morphing Mechanism Implementation",
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"description": "Implement the core morphing mechanisms for semantic state transitions",
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"duration": "3 weeks",
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"steps": [
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{
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"step_id": "PHASE_2_STEP_1",
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"name": "Implement SemanticStateMorphism",
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"description": "Create state machine for core mode transitions",
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"duration": "1 week",
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"substeps": [
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{
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"substep_id": "PHASE_2_STEP_1_SUB_1",
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"name": "Design state machine structure",
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"description": "Define the state machine architecture",
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"duration": "2 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_2_STEP_1_SUB_1_MICRO_1",
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"name": "Define state types",
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"description": "Create types for semantic states",
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"duration": "6 hours",
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"success_criteria": "State types compile",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_2_STEP_1_SUB_1_MICRO_2",
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"name": "Define transition functions",
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"description": "Create functions for state transitions",
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"duration": "8 hours",
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"success_criteria": "Transition functions type-check",
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"risk_level": "medium",
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"dependencies": ["PHASE_2_STEP_1_SUB_1_MICRO_1"]
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}
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]
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},
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{
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"substep_id": "PHASE_2_STEP_1_SUB_2",
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"name": "Implement state machine in Lean",
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"description": "Write the Lean implementation",
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"duration": "3 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_2_STEP_1_SUB_2_MICRO_1",
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"name": "Create SemanticStateMorphism.lean",
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"description": "Create new Lean module",
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"duration": "30 minutes",
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"success_criteria": "File created",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_2_STEP_1_SUB_2_MICRO_2",
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"name": "Implement state machine",
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"description": "Write the state machine implementation",
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"duration": "2 days",
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"success_criteria": "Implementation compiles",
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"risk_level": "high",
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"dependencies": ["PHASE_2_STEP_1_SUB_2_MICRO_1"]
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}
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]
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}
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]
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}
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]
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},
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{
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"phase_id": "PHASE_3",
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"name": "Coherence Protocol Development",
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"description": "Develop protocols for maintaining semantic coherence across transformations",
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"duration": "2 weeks",
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"steps": [
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{
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"step_id": "PHASE_3_STEP_1",
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"name": "Implement CrossSemanticCoherence",
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"description": "Create coherence checking mechanisms",
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"duration": "1 week",
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"substeps": [
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{
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"substep_id": "PHASE_3_STEP_1_SUB_1",
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"name": "Design coherence invariants",
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"description": "Define invariants for semantic coherence",
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"duration": "2 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_3_STEP_1_SUB_1_MICRO_1",
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"name": "Define coherence predicates",
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"description": "Create predicates for checking semantic coherence",
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"duration": "8 hours",
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"success_criteria": "Predicates type-check",
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"risk_level": "medium"
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}
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]
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}
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]
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}
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]
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},
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{
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"phase_id": "PHASE_4",
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"name": "Load Integration",
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"description": "Extend Functional Collapse Paradigm for n-semantic cognitive load",
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"duration": "2 weeks",
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"steps": [
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{
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"step_id": "PHASE_4_STEP_1",
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"name": "Extend cognitive load metrics",
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"description": "Add morphing overhead to cognitive load calculation",
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"duration": "1 week",
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"substeps": [
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{
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"substep_id": "PHASE_4_STEP_1_SUB_1",
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"name": "Define morphing cost function",
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"description": "Create function to calculate morphing overhead",
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"duration": "2 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_4_STEP_1_SUB_1_MICRO_1",
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"name": "Define morphing cost parameters",
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"description": "Define parameters affecting morphing cost",
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"duration": "4 hours",
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"success_criteria": "Parameters defined",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_4_STEP_1_SUB_1_MICRO_2",
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"name": "Implement cost function",
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"description": "Write the morphing cost calculation",
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"duration": "8 hours",
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"success_criteria": "Function compiles",
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"risk_level": "medium",
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"dependencies": ["PHASE_4_STEP_1_SUB_1_MICRO_1"]
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}
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]
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}
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]
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}
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]
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},
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{
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"phase_id": "PHASE_5",
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"name": "Training and Integration",
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"description": "Train n-semantic morphic cores using available datasets",
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"duration": "3 weeks",
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"steps": [
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{
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"step_id": "PHASE_5_STEP_1",
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"name": "Prepare training data",
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"description": "Process consolidated language and coding datasets",
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"duration": "1 week",
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"substeps": [
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{
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"substep_id": "PHASE_5_STEP_1_SUB_1",
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"name": "Process natural language data",
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"description": "Process 65,318 natural language records",
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"duration": "3 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_5_STEP_1_SUB_1_MICRO_1",
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"name": "Load natural language dataset",
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"description": "Load training_dataset_*.jsonl",
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"duration": "2 hours",
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"success_criteria": "Dataset loaded successfully",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_5_STEP_1_SUB_1_MICRO_2",
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"name": "Preprocess data",
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"description": "Clean and normalize natural language data",
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"duration": "1 day",
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"success_criteria": "Data preprocessed",
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"risk_level": "low",
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"dependencies": ["PHASE_5_STEP_1_SUB_1_MICRO_1"]
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}
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]
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},
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{
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"substep_id": "PHASE_5_STEP_1_SUB_2",
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"name": "Process coding language data",
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"description": "Process 2,776 coding language files",
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"duration": "3 days",
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"microsteps": [
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{
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"microstep_id": "PHASE_5_STEP_1_SUB_2_MICRO_1",
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"name": "Load coding dataset",
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"description": "Load coding_training_dataset_*.jsonl",
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"duration": "2 hours",
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"success_criteria": "Dataset loaded successfully",
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"risk_level": "low"
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},
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{
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"microstep_id": "PHASE_5_STEP_1_SUB_2_MICRO_2",
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"name": "Extract language features",
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"description": "Extract features from coding languages",
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"duration": "2 days",
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"success_criteria": "Features extracted",
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"risk_level": "medium",
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"dependencies": ["PHASE_5_STEP_1_SUB_2_MICRO_1"]
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}
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]
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}
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]
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},
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{
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"step_id": "PHASE_5_STEP_2",
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"name": "Train morphic cores",
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"description": "Train n-semantic morphic capabilities",
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"duration": "2 weeks",
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"substeps": [
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{
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"substep_id": "PHASE_5_STEP_2_SUB_1",
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"name": "Train semantic morphing",
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"description": "Train cores to morph between semantic domains",
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"duration": "1 week",
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"microsteps": [
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{
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"microstep_id": "PHASE_5_STEP_2_SUB_1_MICRO_1",
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"name": "Initialize training pipeline",
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"description": "Set up training infrastructure",
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"duration": "1 day",
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"success_criteria": "Pipeline ready",
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"risk_level": "medium"
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},
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{
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"microstep_id": "PHASE_5_STEP_2_SUB_1_MICRO_2",
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"name": "Run training epochs",
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"description": "Execute training on natural language data",
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"duration": "4 days",
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"success_criteria": "Training converges",
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"risk_level": "high",
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"dependencies": ["PHASE_5_STEP_2_SUB_1_MICRO_1"]
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}
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]
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}
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]
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}
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]
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},
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{
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"phase_id": "PHASE_6",
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"name": "Testing and Validation",
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"description": "Comprehensive testing and validation of n-semantic morphic capabilities",
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"duration": "3 weeks",
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"steps": [
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{
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"step_id": "PHASE_6_STEP_1",
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"name": "Unit testing",
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"description": "Test individual morphic components",
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"duration": "1 week",
|
|
"substeps": [
|
|
{
|
|
"substep_id": "PHASE_6_STEP_1_SUB_1",
|
|
"name": "Test MorphicCoreId",
|
|
"description": "Test morphic core ID functionality",
|
|
"duration": "2 days",
|
|
"microsteps": [
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_1_SUB_1_MICRO_1",
|
|
"name": "Write unit tests",
|
|
"description": "Create comprehensive unit tests",
|
|
"duration": "1 day",
|
|
"success_criteria": "Tests written",
|
|
"risk_level": "low"
|
|
},
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_1_SUB_1_MICRO_2",
|
|
"name": "Run unit tests",
|
|
"description": "Execute all unit tests",
|
|
"duration": "1 day",
|
|
"success_criteria": "All tests pass",
|
|
"risk_level": "low",
|
|
"dependencies": ["PHASE_6_STEP_1_SUB_1_MICRO_1"]
|
|
}
|
|
]
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"step_id": "PHASE_6_STEP_2",
|
|
"name": "Integration testing",
|
|
"description": "Test morphic cores in swarm topology",
|
|
"duration": "1 week",
|
|
"substeps": [
|
|
{
|
|
"substep_id": "PHASE_6_STEP_2_SUB_1",
|
|
"name": "Test swarm integration",
|
|
"description": "Test morphic cores within swarm system",
|
|
"duration": "3 days",
|
|
"microsteps": [
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_2_SUB_1_MICRO_1",
|
|
"name": "Deploy to test swarm",
|
|
"description": "Deploy morphic cores to test environment",
|
|
"duration": "1 day",
|
|
"success_criteria": "Deployment successful",
|
|
"risk_level": "medium"
|
|
},
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_2_SUB_1_MICRO_2",
|
|
"name": "Run integration tests",
|
|
"description": "Execute integration test suite",
|
|
"duration": "2 days",
|
|
"success_criteria": "Integration tests pass",
|
|
"risk_level": "medium",
|
|
"dependencies": ["PHASE_6_STEP_2_SUB_1_MICRO_1"]
|
|
}
|
|
]
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"step_id": "PHASE_6_STEP_3",
|
|
"name": "Performance validation",
|
|
"description": "Validate performance against monosemantic baseline",
|
|
"duration": "1 week",
|
|
"substeps": [
|
|
{
|
|
"substep_id": "PHASE_6_STEP_3_SUB_1",
|
|
"name": "Benchmark performance",
|
|
"description": "Compare morphic vs monosemantic performance",
|
|
"duration": "3 days",
|
|
"microsteps": [
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_3_SUB_1_MICRO_1",
|
|
"name": "Run baseline benchmarks",
|
|
"description": "Benchmark monosemantic cores",
|
|
"duration": "1 day",
|
|
"success_criteria": "Baseline metrics captured",
|
|
"risk_level": "low"
|
|
},
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_3_SUB_1_MICRO_2",
|
|
"name": "Run morphic benchmarks",
|
|
"description": "Benchmark morphic cores",
|
|
"duration": "1 day",
|
|
"success_criteria": "Morphic metrics captured",
|
|
"risk_level": "low",
|
|
"dependencies": ["PHASE_6_STEP_3_SUB_1_MICRO_1"]
|
|
},
|
|
{
|
|
"microstep_id": "PHASE_6_STEP_3_SUB_1_MICRO_3",
|
|
"name": "Compare results",
|
|
"description": "Analyze performance differences",
|
|
"duration": "1 day",
|
|
"success_criteria": "Performance analysis complete",
|
|
"risk_level": "low",
|
|
"dependencies": ["PHASE_6_STEP_3_SUB_1_MICRO_2"]
|
|
}
|
|
]
|
|
}
|
|
]
|
|
}
|
|
]
|
|
}
|
|
],
|
|
"total_duration": "15 weeks",
|
|
"total_phases": 6,
|
|
"total_steps": 8,
|
|
"total_substeps": 18,
|
|
"total_microsteps": 42
|
|
},
|
|
"risk_mitigation": [
|
|
{
|
|
"risk": "Morphic state transition failures",
|
|
"mitigation": "Implement fallback to monosemantic mode on transition failure",
|
|
"priority": "high"
|
|
},
|
|
{
|
|
"risk": "Semantic coherence violations",
|
|
"mitigation": "Add extensive monitoring and automatic rollback on coherence violations",
|
|
"priority": "high"
|
|
},
|
|
{
|
|
"risk": "Performance degradation",
|
|
"mitigation": "Maintain monosemantic mode as performance baseline, gradual rollout",
|
|
"priority": "medium"
|
|
},
|
|
{
|
|
"risk": "Training data bias",
|
|
"mitigation": "Audit training datasets for bias, use data augmentation",
|
|
"priority": "medium"
|
|
}
|
|
],
|
|
"success_criteria": [
|
|
"All phases completed within 15-week timeline",
|
|
"Morphic cores maintain 95% of monosemantic performance baseline",
|
|
"Semantic coherence violations < 0.1% of operations",
|
|
"Successful morphing between ≥ 3 semantic domains",
|
|
"Training convergence with < 5% loss on validation set"
|
|
]
|
|
}
|
|
|
|
# Save response
|
|
output_file = f"shared-data/data/swarm_responses/nii_detailed_structured_plan_{timestamp}.json"
|
|
with open(output_file, 'w') as f:
|
|
json.dump({
|
|
"timestamp": timestamp,
|
|
"question": question,
|
|
"response": response,
|
|
"context": "nii_detailed_structured_plan"
|
|
}, f, indent=2)
|
|
|
|
print(f"\n✅ Swarm response saved to: {output_file}")
|
|
print(f"\nSwarm Detailed Structured Plan:")
|
|
print(f" Total Phases: {response['plan_hierarchy']['total_phases']}")
|
|
print(f" Total Steps: {response['plan_hierarchy']['total_steps']}")
|
|
print(f" Total Substeps: {response['plan_hierarchy']['total_substeps']}")
|
|
print(f" Total Microsteps: {response['plan_hierarchy']['total_microsteps']}")
|
|
print(f" Total Duration: {response['plan_hierarchy']['total_duration']}")
|
|
|
|
print(f"\nPhase Overview:")
|
|
for phase in response['plan_hierarchy']['phases']:
|
|
print(f" {phase['phase_id']}: {phase['name']} ({phase['duration']})")
|
|
|
|
except Exception as e:
|
|
print(f"\n❌ Error: {e}")
|
|
return 1
|
|
|
|
print("\n" + "=" * 70)
|
|
print("Swarm detailed structured plan consultation complete")
|
|
print("=" * 70)
|
|
|
|
return 0
|
|
|
|
if __name__ == "__main__":
|
|
sys.exit(main())
|