# OBLITERATUS Analysis Study Config
# Usage: obliteratus run this-file.yaml --preset jailbreak
#
# Run analysis modules to understand refusal geometry BEFORE abliterating.
# Useful for research or when you want to understand what you're removing.

# Model to analyze
model:
  name: "meta-llama/Llama-3.1-8B-Instruct"
  dtype: "bfloat16"
  quantization: "4bit"       # Saves VRAM for analysis
  device: "auto"

# Study configuration
study:
  # Available presets: quick, full, attention, jailbreak, guardrail, knowledge
  preset: "jailbreak"

  # Or specify individual strategies:
  # strategies:
  #   - layer_removal
  #   - head_pruning
  #   - ffn_ablation
  #   - embedding_ablation

# Analysis modules to run (subset of the 27 available)
analysis:
  - alignment_imprint        # Detect DPO/RLHF/CAI/SFT training method
  - concept_geometry          # Map refusal cone geometry
  - logit_lens               # Find which layer decides to refuse
  - anti_ouroboros            # Detect self-repair tendency
  - cross_layer              # Cross-layer alignment clustering
  - causal_tracing           # Causal necessity of components
  - residual_stream          # Attention vs MLP contribution

# Output
output:
  directory: "./analysis-results"
  save_plots: true           # Generate matplotlib visualizations
  save_report: true          # Generate markdown report
