Update app.py

app.py

@@ -271,22 +271,6 @@ def _with_telemetry(text: str, n_tok: int, ttft: float, t_start: float) -> str:
     return text + telemetry
 
 
-# Few-shot "anchoring": Veylon is a CONTINUATION-only base model, never
-# instruction-tuned -- it has no concept of "Input:"/"Output:" turns, so
-# priming it with instruction-style examples (as generic small-LM advice
-# often suggests) would push it OUT of its training distribution, not
-# into it. What anchoring means correctly here is different: prepend a
-# short, clean, well-formed piece of narrative prose so the model's
-# recent-attention window is dominated by coherent English *before*
-# generation starts, nudging it away from degenerating into word salad.
-# This consumes some of the context budget, so it's short and toggleable.
-ANCHOR_TEXT = (
-    "The old lighthouse stood at the edge of the cliff, its light "
-    "sweeping slowly across the dark water. Every night, the keeper "
-    "climbed the narrow stairs to check the lamp, and every night the "
-    "sea answered with the steady sound of waves against the rocks.\n\n"
-)
-
 # ============================================================
 # Gradio UI — Arya
 # ============================================================