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 PyTorch dynamo cache directory issue in containers

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

Add future considerations doc for response size optimization

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 Phase 5: Performance optimizations to phased plan

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

fix: Skip heavy ML deps in CI security checks

fix: Update torch to 2.3+ for transformers compatibility

fix: Update transformers for Devstral support

docs: Mark GPU HF Space Devstral deployment complete

docs: Update phased plan with Phase 2/2b/2c completion status

Add vocabSize to modelInfo response

Update .env.spark.example: TORCH_DTYPE now auto-detected

Add recommended_dtype to model configs