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State Enforcement (v2.0):
- .state file as single source of truth for task phase
- Approval gates for research, decomposition, design, test_design
- status.py --transition refuses illegal phase transitions
- status.py --validate-folder detects out-of-order artifacts
- status.py --audit checks all tasks for violations
- status.py --create-task is the only valid way to create tasks
- Pre-v2.0 tasks without .state are UNTRACKED -- all commands refuse them
- New --upgrade command bootstraps .state files for existing tasks
Project Scoping:
- --project flag added to all status.py commands across 16+ files
- _find_project_dir errors instead of silently falling back to ~/.automaton/
- --scope-check marks framework files OUT_OF_SCOPE when working on a project
- Dashboard handlers use stored project_root instead of re-detecting from CWD
- Prompts reference ~/.automaton/scripts/vram_detect.py (not {project}/.automaton/)
Harness Integration:
- status.py --can-edit now supports project-level checks (no --task required)
- --can-edit --file checks file scope without --task
- --json output for machine-readable harness integration
- opencode plugin (plugins/automaton-guard/plugin.ts) intercepts edit/write
- Git pre-commit hook (scripts/git-hooks/pre-commit) blocks commits without task
- Formal integration contract (contracts/harness-integration.md)
Other:
- upgrade.sh delegates to status.py --upgrade instead of manual heuristics
- Phase prompts reference --project {project} for multi-project scoping
- 200 tests passing (14 new)
67 lines
2.1 KiB
Markdown
67 lines
2.1 KiB
Markdown
# Framework Configuration
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This file contains global framework settings that apply across all projects.
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## VRAM Configuration
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Settings for task decomposition based on available VRAM.
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- **Auto-detect**: Yes # Detect GPU VRAM, RAM, and model context window automatically
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- **Target context**: 16k tokens # Override auto-detect if needed
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- **Headroom**: 25% # Leave headroom for code, context, and reasoning
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- **Max peak context per sub-task**: 12k tokens # Max context for any single sub-task
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### Auto-detection
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When `Auto-detect: Yes`, the framework probes your system to detect:
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- GPU VRAM (via `nvidia-smi` or `lspci`)
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- System RAM (via `/proc/meminfo` or `sysctl`)
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- Model context window (via API config or model name lookup)
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- Framework overhead (by reading all loaded prompt files)
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To disable auto-detection and use manual values:
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```
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## VRAM Configuration
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- **Auto-detect**: No
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- **Target context**: 8k
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- **Headroom**: 30%
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- **Max peak context per sub-task**: 5.6k
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```
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## Model Configuration
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Settings for the LLM model being used.
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- **Model**: auto # Use auto-detection from API config, or specify explicitly (e.g., gpt-4o, claude-3-5-sonnet)
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- **Override context window**: auto # Override auto-detection, or specify (e.g., 128k, 200k)
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### Auto-detection
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When `Model: auto`, the framework detects the model name from:
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1. `.agent.md` in the project (if specified there)
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2. API config files (`.env`, `config.yaml`, `config.json`, etc.)
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3. Model name lookup by name (e.g., gpt-4o → 128k, claude-3-5-sonnet → 200k)
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To disable auto-detection and use manual values:
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```
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## Model Configuration
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- **Model**: gpt-4o
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- **Override context window**: 128k
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```
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## System Requirements
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Requirements for the environment the framework runs in.
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- **nvidia-smi**: Required if NVIDIA GPU (for VRAM detection)
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- **lspci**: Fallback if NVIDIA GPU not available (for AMD GPU VRAM detection)
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- **/proc/meminfo**: Required for RAM detection (Linux)
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- **sysctl**: Fallback for RAM detection (macOS)
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## Framework Version
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- **Version**: 2.0
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- **State enforcement**: enabled (`.state` file + `status.py`)
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