From 41198342d9028c7196ce25d5a1e77c1eeb67de73 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 1 Apr 2026 12:29:57 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 studio/backend/core/inference/llama_cpp.py | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/studio/backend/core/inference/llama_cpp.py b/studio/backend/core/inference/llama_cpp.py
index 87e570e94c..40c80c2c92 100644
--- a/studio/backend/core/inference/llama_cpp.py
+++ b/studio/backend/core/inference/llama_cpp.py
@@ -365,9 +365,8 @@ class LlamaCppBackend:
         if self._kv_lora_rank is not None:
             return True
         # Legacy: need embedding_length + head count
-        return (
-            self._embedding_length is not None
-            and (self._n_kv_heads is not None or self._n_heads is not None)
+        return self._embedding_length is not None and (
+            self._n_kv_heads is not None or self._n_heads is not None
         )
 
     def _estimate_kv_cache_bytes(
@@ -416,7 +415,10 @@ class LlamaCppBackend:
 
         # Path 2: Hybrid Mamba/Attention (Qwen3.5-27B, Qwen3.5-35B-A3B)
         # Only 1 in N layers is attention; the rest are Mamba (no KV cache).
-        if self._ssm_inner_size is not None and self._full_attention_interval is not None:
+        if (
+            self._ssm_inner_size is not None
+            and self._full_attention_interval is not None
+        ):
             fai = self._full_attention_interval
             n_attn = n_layers // fai if fai > 0 else n_layers
             if key_len is not None and val_len is not None:
@@ -427,14 +429,17 @@ class LlamaCppBackend:
         # Path 3: Sliding Window (Gemma-3, gpt-oss)
         # SWA layers only cache min(ctx, window) tokens; global layers cache full ctx.
         # Conservative: assume half layers are global, half are SWA.
-        if self._sliding_window is not None and key_len is not None and val_len is not None:
+        if (
+            self._sliding_window is not None
+            and key_len is not None
+            and val_len is not None
+        ):
             swa = self._sliding_window
             n_global = n_layers // 2
             n_swa = n_layers - n_global
             kv_per_token = n_kv * (key_len + val_len) * bpe
             return int(
-                n_global * n_ctx * kv_per_token
-                + n_swa * min(n_ctx, swa) * kv_per_token
+                n_global * n_ctx * kv_per_token + n_swa * min(n_ctx, swa) * kv_per_token
             )
 
         # Path 4: Standard GQA with explicit key/value dimensions