fix: make model caching non-blocking to bypass huggingface auth errors

Dockerfile

@@ -47,7 +47,7 @@ RUN python -c "\
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM; \
 AutoTokenizer.from_pretrained('ai4bharat/indictrans2-en-indic-dist-200M', trust_remote_code=True, cache_dir='/app/models/indictrans2/en_to_indic'); \
 AutoModelForSeq2SeqLM.from_pretrained('ai4bharat/indictrans2-en-indic-dist-200M', trust_remote_code=True, cache_dir='/app/models/indictrans2/en_to_indic'); \
-print('✓ IndicTrans2 English→Indic model cached')"
+print('✓ IndicTrans2 English→Indic model cached')" || echo "⚠️ IndicTrans2 en-indic cache failed (non-blocking)"
 
 # ── Layer 5b: Pre-cache IndicTrans2 Indic→English model ──────
 # This is the REVERSE direction model (Sprint 18).
@@ -57,7 +57,7 @@ RUN python -c "\
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM; \
 AutoTokenizer.from_pretrained('ai4bharat/indictrans2-indic-en-dist-200M', trust_remote_code=True, cache_dir='/app/models/indictrans2/indic_to_en'); \
 AutoModelForSeq2SeqLM.from_pretrained('ai4bharat/indictrans2-indic-en-dist-200M', trust_remote_code=True, cache_dir='/app/models/indictrans2/indic_to_en'); \
-print('✓ IndicTrans2 Indic→English model cached')"
+print('✓ IndicTrans2 Indic→English model cached')" || echo "⚠️ IndicTrans2 indic-en cache failed (non-blocking)"
 
 # ── Layer 6: Copy application code LAST ──────────────────────
 # Code changes don't invalidate the expensive model cache layers.