update locale for dynamic flow hints

fix breaks in hint text

html/locale_en.json

@@ -197,13 +197,16 @@
   {"id":"","label":"Init Image Same As Control","localized":"","reload":"","hint":"Will additionally treat any image placed into the Control input window as a source for img2img type tasks, an image to modify for example."},
   {"id":"","label":"Separate Init Image","localized":"","reload":"","hint":"Creates an additional window next to Control input labeled Init input, so you can have a separate image for both Control operations and an init source."},
   {"id":"","label":"Override settings","localized":"","reload":"","hint":"If generation parameters deviate from your system settings override settings populated with those settings to override your system configuration for this workflow"},
-  {"id":"","label":"sigma method","localized":"","reload":"","hint":"Controls how noise levels (sigmas) are distributed across diffusion steps. Options:\n- default: the model default\n- karras: smoother noise schedule, higher quality with fewer steps\n- beta: based on beta schedule values\n- exponential: exponential decay of noise\n- lambdas: experimental, balances signal-to-noise\n- flowmatch: tuned for flow-matching models"},
-  {"id":"","label":"timestep spacing","localized":"","reload":"","hint":"Determines how timesteps are spaced across the diffusion process. Options:\n- default: the model default\n- leading: creates evenly spaced steps\n- linspace: includes the first and last steps and evenly selects the remaining intermediate steps\n- trailing: only includes the last step and evenly selects the remaining intermediate steps starting from the end"},
-  {"id":"","label":"beta schedule","localized":"","reload":"","hint":"Defines how beta (noise strength per step) grows. Options:\n- default: the model default\n- linear: evenly decays noise per step\n- scaled: squared version of linear, used only by Stable Diffusion\n- cosine: smoother decay, often better results with fewer steps\n- sigmoid: sharp transition, experimental"},
-  {"id":"","label":"prediction method","localized":"","reload":"","hint":"Defines what the model predicts at each step. Options:\n- default: the model default\n- epsilon: noise (most common for Stable Diffusion)\n- sample: direct denoised image prediction, also called as x0 prediction\n- v_prediction: velocity prediction, used by CosXL and NoobAI VPred models\n- flow_prediction: used with newer flow-matching models like SD3 and Flux"},
+  {"id":"","label":"sigma method","localized":"","reload":"","hint":"Controls how noise levels (sigmas) are distributed across diffusion steps. Options:<br>- default: the model default<br>- karras: smoother noise schedule, higher quality with fewer steps<br>- beta: based on beta schedule values<br>- exponential: exponential decay of noise<br>- lambdas: experimental, balances signal-to-noise<br>- flowmatch: tuned for flow-matching models"},
+  {"id":"","label":"timestep spacing","localized":"","reload":"","hint":"Determines how timesteps are spaced across the diffusion process. Options:<br>- default: the model default<br>- leading: creates evenly spaced steps<br>- linspace: includes the first and last steps and evenly selects the remaining intermediate steps<br>- trailing: only includes the last step and evenly selects the remaining intermediate steps starting from the end"},
+  {"id":"","label":"beta schedule","localized":"","reload":"","hint":"Defines how beta (noise strength per step) grows. Options:<br>- default: the model default<br>- linear: evenly decays noise per step<br>- scaled: squared version of linear, used only by Stable Diffusion<br>- cosine: smoother decay, often better results with fewer steps<br>- sigmoid: sharp transition, experimental"},
+  {"id":"","label":"prediction method","localized":"","reload":"","hint":"Defines what the model predicts at each step. Options:<br>- default: the model default<br>- epsilon: noise (most common for Stable Diffusion)<br>- sample: direct denoised image prediction, also called as x0 prediction<br>- v_prediction: velocity prediction, used by CosXL and NoobAI VPred models<br>- flow_prediction: used with newer flow-matching models like SD3 and Flux"},
   {"id":"","label":"sampler order","localized":"","reload":"","hint":"Order of solver updates in the sampler. Higher order improves stability/accuracy but increases compute cost."},
-  {"id":"","label":"flow shift","localized":"","reload":"","hint":"Adjustment for flow-based samplers. Shifts noise distribution during generation, useful for fine-tuning balance between detail and consistency."},
-  {"id":"","label":"resize mode","localized":"","reload":"","hint":"Defines how the input is resized or adapted in second-pass refinement:\n- none: no resizing, keep original resolution\n- fixed: force resize to target resolution (may distort)\n- crop: center-crop to fit target while keeping aspect ratio\n- fill: resize to fit and pad empty space with borders\n- outpaint: extend canvas beyond image borders\n- context aware: smart resize that blends or adapts surrounding areas"}
+  {"id":"","label":"flow shift","localized":"","reload":"","hint":"Shift value for flowmatching models. Controls thedistribution of denoising steps.<br><br>Values:<br>- >1.0: allocate more steps to early denoising (better structure)<br>-<1.0: allocate more steps to late denoising (better fine details)<br>- 1.0: balanced schedule<br><br>Most flowmatchingmodels use the value of 3 as default. Effectively inactive if dynamic shift is enabled."},
+  {"id":"","label":"dynamic","localized":"","reload":"","hint":"Dynamic shifting automatically adjuststhe denoising schedule based on your image resolution.<br><br>The scheduler interpolates between base_shift andmax_shift based on actual image resolution.<br><br>Enabling disables static Flow shift."},
+  {"id":"","label":"base shift","localized":"","reload":"","hint":"Minimum shift value for low resolutions when using dynamic shifting."},
+  {"id":"","label":"max shift","localized":"","reload":"","hint":"Maximum shift value for high resolutions when using dynamic shifting."},
+  {"id":"","label":"resize mode","localized":"","reload":"","hint":"Defines how the input is resized or adapted in second-pass refinement:<br>- none: no resizing, keep original resolution<br>- fixed: force resize to target resolution (may distort)<br>- crop: center-crop to fit target while keeping aspect ratio<br>- fill: resize to fit and pad empty space with borders<br>- outpaint: extend canvas beyond image borders<br>- context aware: smart resize that blends or adapts surrounding areas"}
 ],
 "other": [
   {"id":"","label":"Install","localized":"","reload":"","hint":"Install"},
@@ -277,7 +280,7 @@
   {"id":"","label":"Final denoising strength","localized":"","reload":"","hint":"The denoising strength for the final loop of each image in the batch"},
   {"id":"","label":"Denoising strength curve","localized":"","reload":"","hint":"The denoising curve controls the rate of denoising strength change each loop. Aggressive: Most of the change will happen towards the start of the loops. Linear: Change will be constant through all loops. Lazy: Most of the change will happen towards the end of the loops"},
   {"id":"","label":"Tile overlap","localized":"","reload":"","hint":"For SD upscale, how much overlap in pixels should there be between tiles. Tiles overlap so that when they are merged back into one picture, there is no clearly visible seam"},
-  {"id":"","label":"ACI: Color to Mask","localized":"","reload":"","hint":"Pick the color you want to mask and inpaint. Click on the color in the image to automatically select it.\n Advised to use images like green screens to get precise results."},
+  {"id":"","label":"ACI: Color to Mask","localized":"","reload":"","hint":"Pick the color you want to mask and inpaint. Click on the color in the image to automatically select it.<br> Advised to use images like green screens to get precise results."},
   {"id":"","label":"ACI: Color Tolerance","localized":"","reload":"","hint":"Adjust the tolerance to include similar colors in the mask. Lower values = mask only very similar colors. Higher = values mask a wider range of similar colors."},
   {"id":"","label":"ACI: Mask Erode","localized":"","reload":"","hint":"Adjust padding to apply a inside offset to the mask. (Recommended value = 2 to remove leftovers at edges)"},
   {"id":"","label":"ACI: Mask Blur","localized":"","reload":"","hint":"Adjust blur to apply a smooth transition between image and inpainted area. (Recommended value = 0 for sharpness)"},
@@ -651,7 +654,6 @@
   {"id":"","label":"dropdown","localized":"","reload":"","hint":"dropdown"},
   {"id":"","label":"duration","localized":"","reload":"","hint":"duration"},
   {"id":"","label":"dwpose","localized":"","reload":"","hint":"dwpose"},
-  {"id":"","label":"dynamic","localized":"","reload":"","hint":"dynamic"},
   {"id":"","label":"dynamic attention slicing rate in gb","localized":"","reload":"","hint":"dynamic attention slicing rate in gb"},
   {"id":"","label":"dynamic attention trigger rate in gb","localized":"","reload":"","hint":"dynamic attention trigger rate in gb"},
   {"id":"","label":"edge","localized":"","reload":"","hint":"edge"},
@@ -1070,7 +1072,6 @@
   {"id":"","label":"same latent","localized":"","reload":"","hint":"same latent"},
   {"id":"","label":"sample","localized":"","reload":"","hint":"sample"},
   {"id":"","label":"sampler","localized":"","reload":"","hint":"sampler"},
-  {"id":"","label":"sampler dynamic shift","localized":"","reload":"","hint":"sampler dynamic shift"},
   {"id":"","label":"sampler shift","localized":"","reload":"","hint":"sampler shift"},
   {"id":"","label":"sana: use complex human instructions","localized":"","reload":"","hint":"sana: use complex human instructions"},
   {"id":"","label":"saturation","localized":"","reload":"","hint":"saturation"},