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v1.2.9 — Stable Baseline Release

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@simeon-kepp simeon-kepp released this 29 Apr 13:09
· 4544 commits to main since this release
v1.2.9
3130f1b
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status architecture memory compliance language

Overview

This release marks the transition from experimental builds to a stable, stateful, and operational system.

For the first time, the Ternary Intelligence Stack (TIS) behaves as a coherent runtime environment, not a collection of loosely coupled components.

In practical terms:
You can now build on top of it, not just experiment with it.

Core Highlights

64-bit Runtime Support

The execution layer now operates fully in 64-bit across the stack.

Impact:

  • Larger parameter spaces
  • Improved numerical stability
  • Compatibility with real-world workloads

Under the hood:

  • Memory model redesign
  • Execution alignment fixes
  • Kernel-level assumption updates

Persistent Memory Layer — RuVectorDB

Introduced a database-backed memory system with cryptographic timestamping.

Capabilities:

  • Deterministic recall across sessions
  • Structured, persistent state (no more resets)
  • Traceable memory evolution

Result:
→ Enables long-running, stateful agents

Repository Restructure — “Ordnung”

The codebase now reflects actual system architecture rather than historical growth.

Improvements:

  • Clear separation: runtime / memory / interface
  • Centralized documentation
  • Reduced cross-module coupling
  • Simplified utilities

Outcome:
→ Faster onboarding, fewer hidden dependencies

Proactive Runtime Behavior

Albert transitions from passive executor → active system participant

New behaviors:

  • Tracks internal state transitions
  • Adapts its own memory schema
  • Performs environment validation

Shift:
→ From execution engine to system-aware runtime

PyTern Integration

Python interoperability is now a first-class citizen.

  • pytern added as core crate
  • Unified versioning (v1.2.9)
  • Foundation for hybrid workflows

Unlocks:

  • Python scripting layers
  • External tool integration
  • Research-friendly interfaces

TernAudit Guard (Compliance Layer)

Refactored from ternlang-audit into a structured observability system.

Components:

  • DashboardManager → real-time system visibility
  • AuditEvent pipeline → structured logging

Purpose:
→ Production-grade auditability & compliance

UX & CLI Improvements (albert-cli)

  • ⚡ Faster startup (reduced boot latency)
  • ⌨️ Optimized typewriter responsiveness (120ms tick)
  • 🎛️ Smooth, decoupled UI animations
  • 🧾 Enhanced session report (model + UX hints)
  • 🧠 Inline HITL (Human-in-the-Loop) interaction cards
  • 🧩 Fixed markdown rendering (“geometry leak”)
  • 🔐 Resolved sandbox permission issues (uid_map)

Reliability & Recovery

This release includes a full workspace recovery event:

  • Rebuilt all Cargo.toml files after accidental wipe
  • Restored and validated entire workspace structure
  • Fixed dependency graph inconsistencies
  • Cleaned dead references

Takeaway:
→ The system is now resilient at scale

Versioning & Distribution

  • All 26+ crates bumped to v1.2.9
  • Full ecosystem published to crates.io
  • Standalone crates (pytern, ternaudit-guard) aligned
  • Git history rebased and synchronized

Why This Matters

This release establishes a true operational baseline for:

  • Running larger models locally
  • Building persistent agent systems
  • Integrating external tooling (Python, dashboards, audits)
  • Transitioning from experimentation → reproducibility

Design Philosophy

This version prioritizes:

  • Stability > Features
  • Structure > Speed
  • Foundations > Optimization
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