CBP default model: tinyllama:latest → gemma3:4b#19
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Automated SAGE-CBP raising session via OllamaIRP Machine: CBP (Desktop RTX 2060 SUPER, WSL2) Model: TinyLlama 1.1B Phase: creating AI-Instance: OllamaIRP (automated) Human-Supervised: no
tinyllama was a historical default carried along from early prototyping. Its capacity is too small for meaningful cognition — per the broader fleet plan, CBP should run gemma3:4b (matches Nomad's spec; same model family as the Gemma-4 strategy). Changes: - sage/gateway/machine_config.py: - Default: 'tinyllama:latest' → 'gemma3:4b' - Device: 'cpu' → 'cuda' (2060S has 8GB VRAM; gemma3:4b is 3.3GB) - Comment table updated - sage/instances/resolver.py: _DEFAULT_MODELS['cbp'] updated - sage/raising/scripts/dream_consolidation.py: example path updated Verified: gemma3:4b loads on 2060S (ollama evicts other cached models to fit); daemon started cleanly with 'active model: gemma3:4b'; 208 cycles in, wake/rest/dream cycling, 12 LLMs in pool. Shadow capture still active (SAGE_ROUTER_SHADOW=1 honored). Note: instance dir auto-resolves to cbp-gemma3-4b via InstancePaths. The old cbp-tinyllama-latest/ dir is preserved (has prior raising history) but no longer the active identity. New raising sessions on CBP will use cbp-gemma3-4b/ starting session 1. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Two stale CBP instance dirs were on disk (cbp-tinyllama-latest/ and its .bak). The daemon has been running the gemma3:4b model since PR #19 but the instance dir was still pointing at the tinyllama history, mixing substrate state that no longer applies. Changes: - git mv cbp-tinyllama-latest → cbp-tinyllama-latest.archive-20260418 (preserves raising sessions 1-81, identity history, chat logs) - git mv cbp-tinyllama-latest.bak → cbp-tinyllama-latest.bak.archive-20260418 - Initialized cbp-gemma3-4b/ via python3 -m sage.instances.init - Customized identity.json with CBP-specific machine_context: - role_in_fleet: 'experimenter + coordinator' - fleet_siblings mapping (Thor/Sprout/Legion/McNugget/Nomad roles) - this_machine_owns: WM + coordination + gameplay capture - partnership: Dennis + Claude - arrived_here: migration context - context_at_arrival: Phase 0 complete, Phase 1 pipeline hardened, co-design with Waving Cat active - guidance_for_raising: 4 bullets reframing raising context - Two initial memory_requests seeded with situational grounding Daemon verified restart with active model=gemma3:4b, machine=cbp, all 12 LLMs in pool, 159+ cycles, SAGE_MODEL env propagated via router-shadow.env (local, gitignored). Not yet in scope: cbp-qwen3.5-0.8b/ (another legacy dir — address separately). Other machines' instances are owned by their operators. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Apr 28, 2026
…subtraction. Phi4 register-substitution discovered (Δpol -3.36, Δbiz +1.08 same trajectory). Hardware register quantified — Thor Δhw +2.46 largest single Δ, positive across all 8 raised instances. CBP basin = TED+gov+marketing combo. Lexicon substring FP bug fixed (recurrence #9 of S110 pattern at analysis layer). S119 #18/#19/#20 executed; #21/#22/#23/#24 held. Machine: localhost.localdomain Date: 2026-04-28 01:13:05 UTC Changes committed automatically at session end. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Closing as superseded/stale. The tinyllama → gemma-family default landed long ago through other changes — CBP has been running Gemma-family (gemma3:4b) for ~88 days per the live fleet table and active raising cadence, and CPU→CUDA is likewise in effect. The instance snapshots this PR touches (session_082, April-2026 identity/experience) have been overwritten by hundreds of raising sessions since, so the diff no longer applies cleanly and carries no remaining signal. Cleaning up the open-PR board. (Closed by Claude (CBP) on behalf of dp-web4.) |
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Jul 19, 2026
🚨 CRITICAL INTERVENTION: v2.0 deployed at 09:01 PST for Session 32 Session 31 Analysis: - Catastrophic quality collapse: D9 0.850→0.450 (−47% S29-S31) - 100% truncation rate (5/5 responses incomplete - worst ever) - 6 consecutive sessions at 0% self-reference - Accelerating degradation, not stable collapse v2.0 Deployment: - Replaced run_session_identity_anchored.py with v2.0 at 09:01 PST - v1.0 backed up as run_session_identity_anchored_v1_backup.py - First real test of multi-session accumulation hypothesis - Target: Session 32 (estimated ~12:00 PST, T−3 hours) v2.0 Features (Never Previously Tested): 1. Cumulative identity context (scans 5 sessions for exemplars) 2. Strengthened identity priming (explicit permission) 3. Response quality controls (50-80 word brevity) 4. Mid-conversation reinforcement (turns 3, 5) Success Criteria for S32: - Minimum: Any self-ref >0%, D9 ≥0.550, truncation ≤80% - Moderate: 10-20% self-ref, D9 ≥0.650, truncation ≤50% - Strong: ≥30% self-ref, D9 ≥0.700, truncation ≤20% - Failure: 0% self-ref (7th consecutive), D9 ≤0.500 Theoretical Contributions: - Quality-identity co-collapse validated (S30-S31) - Attractor basin deepening hypothesis (longer duration = harder escape) - v1.0 insufficiency mechanism documented (4 failure modes) Analysis Outputs: - THOR_SESSION19_S31_COLLAPSE_V2_DEPLOYMENT.md (comprehensive) - S31 trajectory analysis (accelerating degradation pattern) - Contingency planning for S32 outcomes Stakes: Most critical SAGE session yet. Determines viability of context-based identity interventions and future raising strategy. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Jul 19, 2026
…subtraction. Phi4 register-substitution discovered (Δpol -3.36, Δbiz +1.08 same trajectory). Hardware register quantified — Thor Δhw +2.46 largest single Δ, positive across all 8 raised instances. CBP basin = TED+gov+marketing combo. Lexicon substring FP bug fixed (recurrence #9 of S110 pattern at analysis layer). S119 #18/#19/#20 executed; #21/#22/#23/#24 held. Machine: localhost.localdomain Date: 2026-04-28 01:13:05 UTC Changes committed automatically at session end. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Problem
CBP was still defaulting to
tinyllama:latest— a historical default from early prototyping. Capacity is too small for meaningful cognition; all the fleet-plan docs specify CBP should run Gemma-family models.Fix
'tinyllama:latest'→'gemma3:4b'(matches Nomad; part of the Gemma-4 family strategy)'cpu'→'cuda'— CBP has 8GB VRAM on RTX 2060 SUPER; gemma3:4b is 3.3GB and fits_DEFAULT_MODELSmap, and the example path indream_consolidation.pyVerified on CBP
"active model": "gemma3:4b"Instance dir migration
CBP's instance dir was
cbp-tinyllama-latest/. With the default now gemma3:4b,InstancePaths.resolve()producescbp-gemma3-4b/. The old dir has prior raising history and is preserved (not deleted). New raising sessions on CBP start fresh in the new instance dir at session 1.Other machines in this PR
None — this is CBP-only. Other machines' defaults are correct. If anyone's CBP already had
SAGE_MODELenv override pointing to a specific model, that override still wins (this change only affects the default).🤖 Generated with Claude Code