79 lines
3.1 KiB
Markdown
79 lines
3.1 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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## Loop Role Models
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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.
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- **Implement:** — produces the artifact for this tick. Bound to `prompts/loop-implement.md` by default.
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- **Verify:** — grades the artifact and emits the JSON verdict `{pass, score, reasons, next_hint}`. Bound to `prompts/loop-verifier.md`. The framework never inspects this role's model (D8); only its session.
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- **Orchestrate:** — applies the verdict, calls exactly one `status.py` operation per tick, enforces brakes. Bound to `prompts/loop-orchestrate.md`.
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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.
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Role context tiers are set per-loop in `loop.json`, not globally. The 16k floor (D13) applies regardless of tier.
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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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