Lap Tran
bc7daf8590
- **Restore 82 completed tasks** from tasks/complete/ back to tasks/ top level (all <7 days old per the cleanup policy; premature bulk archive was fixed). - **Dashboard: fix scroll-reset on auto-refresh** — renderBoard rebuilds the board via innerHTML every 2s, destroying each column-body's scrollTop. Now snapshots column-body scrollTop + board.scrollLeft + view.scrollTop before rebuild and restores after (matched by PHASE_GROUPS index). - **Dashboard UI additions** (pre-existing unstaged work): approval section cards, transition buttons, inline artifact editor (textarea for writing missing SPEC/VERDICT/etc from the detail modal). - **Bind ornith as Implement model** — config.md: Model explicit to omlx/Ornith-1.0-35B-4bit-mlx, context window 32768. Interactive autopilot already used ornith via opencode default; now explicit. - **Fix cleanup stub** — automaton-cleanup.sh had a stale --project arg pointing at a pytest temp dir (test isolation leak). Rewired to point at ~/.automaton. - **Fix plist-isolation test** — test asserted host plist doesn't exist, but a real install creates it. Now snapshots mtime before run, asserts unchanged after (only a write during the test counts as bleed). - **New Playwright smoke test** (tests/test_dashboard_ui.py) — 2 tests: board renders tasks, column scroll survives auto-refresh tick. Verified the test fails without the scroll fix (scrollTop resets to 0). Skipped via importorskip when playwright is absent (main CI stays green). - **Clarify SI loop scope in README** — new-project onboarding section documents the framework-scoped self-improvement loop and options (leave/pause/create project loop). - **CHANGELOG** documents all changes including the known model-divergence gap (mde tasks marked complete but per-role model binding was never implemented).
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Framework Configuration
This file contains global framework settings that apply across all projects.
VRAM Configuration
Settings for task decomposition based on available VRAM.
- Auto-detect: Yes # Detect GPU VRAM, RAM, and model context window automatically
- Target context: 16k tokens # Override auto-detect if needed
- Headroom: 25% # Leave headroom for code, context, and reasoning
- Max peak context per sub-task: 12k tokens # Max context for any single sub-task
Auto-detection
When Auto-detect: Yes, the framework probes your system to detect:
- GPU VRAM (via
nvidia-smiorlspci) - System RAM (via
/proc/meminfoorsysctl) - Model context window (via API config or model name lookup)
- Framework overhead (by reading all loaded prompt files)
To disable auto-detection and use manual values:
## VRAM Configuration
- **Auto-detect**: No
- **Target context**: 8k
- **Headroom**: 30%
- **Max peak context per sub-task**: 5.6k
Model Configuration
Settings for the LLM model being used.
- Model: omlx/Ornith-1.0-35B-4bit-mlx # Local LLM (opencode provider); used as the Implement role
- Override context window: 32768 # Matches opencode.json limit.context for ornith
Auto-detection
When Model: auto, the framework detects the model name from:
.agent.mdin the project (if specified there)- API config files (
.env,config.yaml,config.json, etc.) - Model name lookup by name (e.g., gpt-4o → 128k, claude-3-5-sonnet → 200k)
To disable auto-detection and use manual values:
## Model Configuration
- **Model**: gpt-4o
- **Override context window**: 128k
System Requirements
Requirements for the environment the framework runs in.
- nvidia-smi: Required if NVIDIA GPU (for VRAM detection)
- lspci: Fallback if NVIDIA GPU not available (for AMD GPU VRAM detection)
- /proc/meminfo: Required for RAM detection (Linux)
- sysctl: Fallback for RAM detection (macOS)
Loop Role Models
Loop ticks run three session roles. Roles are sessions, not models — a single model can fill multiple roles. Configure each loop's role-to-prompt binding in its loop.json; this section documents the framework's expectations only.
- Implement: — produces the artifact for this tick. Bound to
prompts/loop-implement.mdby default. - Verify: — grades the artifact and emits the JSON verdict
{pass, score, reasons, next_hint}. Bound toprompts/loop-verifier.md. The framework never inspects this role's model (D8); only its session. - Orchestrate: — applies the verdict, calls exactly one
status.pyoperation per tick, enforces brakes. Bound toprompts/loop-orchestrate.md.
Conflict-of-interest rule (D12): Verify: and Implement: must never be the same session. When two distinct sessions are infeasible (single-session harness), the runner falls back to session-only divergence — still safe.
Role context tiers are set per-loop in loop.json, not globally. The 16k floor (D13) applies regardless of tier.
Framework Version
- Version: 2.0
- State enforcement: enabled (
.statefile +status.py)