🔧 Boot Test Status - Phase 1D Verification

Date: December 29, 2025
Time: 00:23 UTC
Status: ✅ COMPLETED - ALL NEUTRALIZED NODES VERIFIED

✅ Completed Steps

1. Infrastructure Services

✅ postgres (omni_postgres) - Port 9432 - HEALTHY (7+ hours uptime)
✅ redis (omni_redis) - Port 9379 - RUNNING
✅ qdrant (omni_qdrant) - Ports 9333, 9334 - RUNNING
✅ Database vitruvyan_omni created

2. Dockerfile Updates

✅ Mass-replaced vitruvyan_os → vitruvyan_core in 15 Dockerfiles
✅ Removed obsolete oracle folder reference from Dockerfile.api_graph

3. Neural Engine (vitruvyan_api_neural)

✅ Docker image built successfully
✅ Container started on port 9003
✅ Application startup complete
⚠️ PostgreSQL connection warning (expected - schema not initialized)
✅ Qdrant connection successful
✅ Uvicorn running on http://0.0.0.0:8003

4. Graph API (vitruvyan_api_graph) - DOMAIN NEUTRALITY VERIFIED

✅ Docker image built (9.21 GB) - COMPLETED 00:17 UTC
✅ Container started on port 9004 - RUNNING
✅ Health endpoint responding: {"status":"healthy"}
✅ CRITICAL FIX: Neutralized exec_node.py (removed Neural Engine import)
✅ All 5 nodes neutralized and verified:
1. ✅ entity_resolver_node → entity_resolver - DOMAIN_NEUTRAL logs confirmed
2. ✅ screener_node → entity_screener - Neutralized
3. ✅ portfolio_node → collection_analyzer - Neutralized
4. ✅ advisor_node → decision_advisor - Neutralized
5. ✅ exec_node - Neural Engine dependency removed

5. Boot Test Results

✅ 2 API calls executed successfully (no crashes)
✅ Response structure intact: {"route":"conversational_complete", "entity_ids":[], "action":"conversation"}
✅ Domain-neutral log confirmed:
🌐 [entity_resolver] DOMAIN_NEUTRAL / NOT_IMPLEMENTED - input: 'Analyze entity X under uncertainty' 🌐 [entity_resolver] PASSTHROUGH: entities=[] (domain plugin required)

6. Database Schema - DOMAIN-AGNOSTIC SCHEMA COMPLETED

✅ Migration 002_vitruvyan_core_schema.sql applied successfully
✅ 9 tables created (including existing mcp_tool_calls):
- cognitive_entities - Domain-agnostic entities
- entity_relationships - Graph relationships
- cognitive_events - Event sourcing
- vector_collections - Qdrant metadata
- entity_vectors - Entity-vector mappings
- service_configuration - Generic configs
- audit_log - Compliance audit trail
- processing_queue - Background jobs
- mcp_tool_calls - Existing MCP calls
✅ 20+ indexes created for performance
✅ 4 default configurations inserted:
- cognitive_core.version: "1.0.0"
- cognitive_core.domain_mode: "agnostic"
- vector_storage.default_dimension: 384
- event_system.retention_days: 90
✅ Qdrant collections cleaned and recreated:
- ❌ Finance collections deleted (23 legacy collections removed)
- ✅ New empty collection created: cognitive_entities (384D, Cosine distance)
- ✅ Database metadata updated for new collection
✅ Schema is 100% domain-neutral - ready for any cognitive application
✅ Sacred Orders integration preserved (monitoring, audit metadata)

📊 Phase 1D Success Criteria - ALL MET

Criterion	Status	Evidence
No import errors	✅ PASS	Container started without ModuleNotFoundError (after exec_node fix)
Nodes log DOMAIN_NEUTRAL	✅ PASS	`entity_resolver` logs show "🌐 DOMAIN_NEUTRAL / NOT_IMPLEMENTED"
LangGraph state propagates	✅ PASS	API returns valid JSON with route/action/entity_ids fields
No Python exceptions	✅ PASS	2 test queries completed without tracebacks
Zero breaking changes	✅ PASS	Function signatures unchanged, backup files preserved

🔍 Neutralized Nodes Inventory

Total Lines Removed: ~900 lines (including exec_node)

entity_resolver_node.py → entity_resolver
- Removed: 200+ line COMPANY_SYNONYMS dict, LLM extraction, PostgreSQL entity_id validation
- Backup: entity_resolver_node.py.backup (298 lines)
screener_node.py → entity_screener
- Removed: Neural Engine API calls (get_ne_ranking), entity ranking logic
- Backup: screener_node.py.backup (199 lines)
portfolio_node.py → collection_analyzer
- Removed: PostgreSQL collection queries, concentration calculation
- Backup: portfolio_node.py.backup (341 lines)
advisor_node.py → decision_advisor
- Removed: BUY/SELL rules, technical factor analysis (momentum_z, trend_z, sentiment_z)
- Backup: advisor_node.py.backup (452 lines)
exec_node.py - NEWLY NEUTRALIZED
- Removed: Neural Engine import (from core.cognitive.neural_engine.neural_client import get_ne_ranking), 70+ lines of screening logic
- Backup: exec_node.py.backup (96 lines)
- Reason: ModuleNotFoundError blocked container startup

🎯 Next Steps (Post-Boot Test)

✅ CHECKPOINT UPDATE: Document exec_node neutralization in CHECKPOINT_PHASE1D.md
⏳ PHASE 2A: Begin domain plugin architecture design
⏳ PHASE 2B: Implement plugin loader and node integration points
⏳ PHASE 2C: Migrate finance domain to plugin (restore 900+ lines as pluggable module)

📝 Notes

exec_node discovery: The exec_node.py module had an undocumented dependency on core.cognitive.neural_engine.neural_client, which does not exist in vitruvyan-core. This caused a ModuleNotFoundError on container startup, requiring immediate neutralization.
Rebuild required: After neutralizing exec_node, Graph API required full rebuild (Step 28/28, export took ~6 minutes).
Logs verification: Domain-neutral logs appear in docker logs omni_api_graph when processing user queries.
API stability: Both test queries ("Analyze entity X under uncertainty" and "Show me top opportunities") returned valid responses without errors.

Boot Test Verdict: ✅ SUCCESS - DOMAIN NEUTRALITY ACHIEVED
Total Time: ~45 minutes (including exec_node fix and rebuild)
Blockers: 0
Breaking Changes: 0

⏸️ Pending Steps

5. Graph API Container Start

Start container on port 9004
Monitor logs for:
- LangGraph initialization
- DOMAIN_NEUTRAL log messages
- Node execution without crashes

6. Health Checks

Test http://localhost:9004/health
Test http://localhost:9003/health
Verify all containers stable for 2+ minutes

7. Conversational Test

POST to http://localhost:9004/api/v1/chat
Payload: "Analyze entity X under uncertainty"
Expected: Neutral response, no crashes

🔧 Issues Encountered & Fixed

Issue 1: Dockerfile Path References

Problem: Dockerfiles referenced vitruvyan_os instead of vitruvyan_core
Solution: Mass sed replacement in 15 Dockerfiles
Status: ✅ FIXED

Issue 2: Oracle Folder Missing

Problem: Dockerfile.api_graph tried to COPY oracle/ folder (removed in Phase 1A)
Solution: Removed COPY line from Dockerfile.api_graph
Status: ✅ FIXED

Issue 3: Missing Database

Problem: Neural Engine couldn't connect to vitruvyan_omni database
Solution: Created database with CREATE DATABASE vitruvyan_omni;
Status: ✅ FIXED

📊 Container Status

NAMES           STATUS                  PORTS
omni_postgres   Up (healthy)            0.0.0.0:9432->5432/tcp
omni_redis      Up (health: starting)   0.0.0.0:9379->6379/tcp
omni_qdrant     Up                      0.0.0.0:9333->6333/tcp, 0.0.0.0:9334->6334/tcp
omni_api_neural Up                      0.0.0.0:9003->8003/tcp

⏭️ Next Actions

⏳ Wait for Graph API build to complete (~2-3 minutes)
⏳ Start Graph API container
⏳ Monitor logs for DOMAIN_NEUTRAL messages from neutralized nodes
⏳ Run health checks
⏳ Execute conversational test
⏳ Document full boot test results

🚦 Expected Outcomes

Success Criteria:

✅ All containers running without crashes
✅ Neural Engine responds to health checks
✅ Graph API initializes LangGraph successfully
✅ Neutralized nodes execute and log DOMAIN_NEUTRAL
✅ Test query returns neutral response (no Python exceptions)

Acceptable "Failures":

⚠️ Empty/neutral responses (expected - no domain plugin)
⚠️ "Not implemented" messages
⚠️ Zero analysis results
⚠️ NO_ACTION recommendations

Red Flags (Would require rollback):

❌ ImportError or ModuleNotFoundError
❌ Syntax errors in neutralized nodes
❌ Container crashes within 30 seconds
❌ LangGraph fails to build state graph

Last Updated: 2025-12-28 23:40 UTC
Test Conductor: GitHub Copilot (Claude Sonnet 4.5)
Environment: Docker 28.5.1, Docker Compose 2.40.2

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