genai exception handling and lint all

Signed-off-by: vladmandic <mandic00@live.com>

.ruff.toml

@@ -72,6 +72,7 @@ select = [
 ignore = [
   "B006",   # Do not use mutable data structures for argument defaults
   "B008",   # Do not perform function call in argument defaults
+  "B905",   # Strict zip() usage
   "C420",   # Unnecessary dict comprehension for iterable; use `dict.fromkeys` instead
   "C408",   # Unnecessary `dict` call
   "I001",   # Import block is un-sorted or un-formatted

javascript/contextMenus.js

@@ -109,7 +109,7 @@ const generateForever = (genbuttonid) => {
         busy = outerButton?.classList.contains('generate') && outerButton?.classList.contains('active');
       }
       return busy;
-    }
+    };
     log('generateForever: start');
     if (!isBusy()) genbutton.click();
     window.generateOnRepeatInterval = setInterval(() => {

javascript/control.js

@@ -5,7 +5,7 @@ function controlInputMode(inputMode, ...args) {
   if (!tab) return ['Image', ...args];
   // let inputTab = tab.innerText;
   const tabs = Array.from(gradioApp().querySelectorAll('#control-tab-input button'));
-  const tabIdx = tabs.findIndex((btn) => btn.classList.contains('selected'))
+  const tabIdx = tabs.findIndex((btn) => btn.classList.contains('selected'));
   const tabNames = ['Image', 'Video', 'Batch', 'Folder'];
   let inputTab = tabNames[tabIdx] || 'Image';
   log('controlInputMode', { mode: inputMode, tab: inputTab, kanvas: typeof Kanvas });

modules/lora/network.py

@@ -116,7 +116,7 @@ class NetworkOnDisk:
         if self.filename is not None:
             fn = os.path.splitext(self.filename)[0] + '.txt'
             if os.path.exists(fn):
-                with open(fn, "r") as file:
+                with open(fn, "r", encoding="utf-8") as file:
                     return file.read()
         return None
 

modules/postprocess/yolo.py

@@ -147,7 +147,7 @@ class YoloRestorer(Detailer):
                     try:
                         seg = (255 * seg).astype(np.uint8)
                         seg = Image.fromarray(seg).resize(image.size).convert('L')
-                    except:
+                    except Exception:
                         seg = None
                 cls = int(cls)
                 label = prediction.names[cls] if cls < len(prediction.names) else f'cls{cls}'

modules/video_models/google_veo.py

@@ -136,11 +136,12 @@ class GoogleVeoVideoPipeline():
             log.error(f'Cloud video: model="{self.model}" {operation} {e}')
             return None
 
-        if operation is None or operation.response is None or operation.response.generated_videos is None or len(operation.response.generated_videos) == 0:
+        try:
+            response: genai.types.GeneratedVideo = operation.response.generated_videos[0]
+        except Exception:
             log.error(f'Cloud video: model="{self.model}" no response {operation}')
             return None
         try:
-            response: genai.types.GeneratedVideo = operation.response.generated_videos[0]
             self.client.files.download(file=response.video)
             video_bytes = response.video.video_bytes
             return { 'bytes': video_bytes, 'images': [] }

pipelines/model_google.py

@@ -1,5 +1,6 @@
 import io
 import os
+import time
 from PIL import Image
 from installer import install, reload, log
 
@@ -110,10 +111,17 @@ class GoogleNanoBananaPipeline():
         # log.debug(f'Cloud: config={self.config}')
 
         try:
+            t0 = time.time()
             if image is not None:
                 response = self.img2img(prompt, image)
             else:
                 response = self.txt2img(prompt)
+            t1 = time.time()
+            try:
+                tokens = response.usage_metadata.total_token_count
+            except Exception:
+                tokens = 0
+            log.debug(f'Cloud: model="{self.model}" tokens={tokens} time={(t1 - t0):.2f}')
         except Exception as e:
             log.error(f'Cloud: model="{self.model}" {e}')
             return None
@@ -121,10 +129,16 @@ class GoogleNanoBananaPipeline():
         image = None
         if getattr(response, 'prompt_feedback', None) is not None:
             log.error(f'Cloud: model="{self.model}" {response.prompt_feedback}')
-        if not hasattr(response, 'candidates') or (response.candidates is None) or (len(response.candidates) == 0) or (response.candidates[0].content is None) or (len(response.candidates[0].content.parts) == 0):
+
+        parts = []
+        try:
+            for candidate in response.candidates:
+                parts.extend(candidate.content.parts)
+        except Exception:
             log.error(f'Cloud: model="{self.model}" no images received')
             return None
-        for part in response.candidates[0].content.parts:
+
+        for part in parts:
             if part.inline_data is not None:
                 image = Image.open(io.BytesIO(part.inline_data.data))
         return image