Add tuned lens as supplementary projection mode for logit lens

Rename 'counterfactual' terminology to 'input ablation' in docstrings

Fix margin winner_token in margin_data and extract _classify_stability helper

Add margin-based decision analysis, interventional counterfactuals, and run comparison (v3.0)

Add deep inspection: data-driven pattern classification, attention/MLP tracking, logit lens

Change default model to Devstral and optimise attention extraction

Fix MistralTokenizer loading and token section boundaries

Fix MistralTokenizer not loaded during model switch

feat: add top-k/top-p sampling and detailed logits/probability tracking

fix: Improve token alternatives numerical stability and temperature control

Store matrices as numpy arrays instead of Python lists

Add per-step memory cleanup for large model support

Fix RAM exhaustion for large token generation

feat: add auto_complete parameter for token generation

fix: add QKV extraction support for Mistral/Devstral architecture

feat: implement lazy-loading for attention matrices

Add avg_entropy calculation for attention heads

Revert QKV visualization fixes - need better approach for data streaming

Add safety checks for missing QKV keys

Limit QKV matrices to top 5 heads per layer to reduce response size

Fix QKV matrix extraction for Mistral/Devstral architecture

Fix QKV visualization for Mistral/Devstral architecture

Fix: Import time module at top level for SSE events

Add SSE streaming endpoint for real-time analysis progress

feat: Include token metadata in analysis response

feat: Implement tier-based model filtering by device type

Fix: Add attn_implementation="eager" to model switch function

Add tokenSections boundaries and update system prompt

Fix: Handle MistralCommonTokenizer pad_token setter

Integrate mistral-common for correct Devstral tokenization

Remove mistral_common to fix dependency conflict

Use mistral_common for proper Devstral prompt formatting

Add system prompt support for instruction-tuned models

fix: Simpler prompt format and temperature=0 for Devstral

fix: Sanitize JSON response for NaN/Inf float values

fix: Check chat_template is set before using apply_chat_template

fix: Add chat template support for Devstral instruct model

fix: Convert bfloat16 to float32 for numpy compatibility

fix: Use eager attention for output_attentions support

Add vocabSize to modelInfo response

Add recommended_dtype to model configs

Phase 2: Add Devstral backend support

Add DEVICE env var to force CPU mode on DGX Spark

Make zarr/numcodecs imports optional for ARM64 compatibility

Phase 1: DGX Spark infrastructure

Make QKV hook robust against shape mismatches

Fix research attention endpoint model compatibility

Add research attention analysis endpoint with real CodeGen tokenization

Add research attention analysis endpoints with Q/K/V extraction

Fix ablation study for Code Llama compatibility