mirror of https://github.com/leafspark/AutoGGUF
141 lines
4.3 KiB
Python
141 lines
4.3 KiB
Python
from PySide6.QtCore import QTimer
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from PySide6.QtGui import Qt
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from Localizations import *
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import psutil
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from error_handling import show_error
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def toggle_gpu_offload_auto(self, state) -> None:
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is_auto = state == Qt.CheckState.Checked
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self.gpu_offload_slider.setEnabled(not is_auto)
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self.gpu_offload_spinbox.setEnabled(not is_auto)
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def update_model_info(logger, self, model_info) -> None:
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logger.debug(UPDATING_MODEL_INFO.format(model_info))
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pass
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def update_system_info(self) -> None:
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ram = psutil.virtual_memory()
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cpu = psutil.cpu_percent()
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# Smooth transition for RAM bar
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animate_bar(self, self.ram_bar, ram.percent)
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# Smooth transition for CPU bar
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animate_bar(self, self.cpu_bar, cpu)
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self.ram_bar.setFormat(
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RAM_USAGE_FORMAT.format(
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ram.percent, ram.used // 1024 // 1024, ram.total // 1024 // 1024
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)
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)
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self.cpu_label.setText(CPU_USAGE_FORMAT.format(cpu))
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def animate_bar(self, bar, target_value) -> None:
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current_value = bar.value()
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difference = target_value - current_value
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if abs(difference) <= 1: # Avoid animation for small changes
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bar.setValue(target_value)
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return
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step = 1 if difference > 0 else -1 # Increment or decrement based on difference
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timer = QTimer(self)
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timer.timeout.connect(lambda: _animate_step(bar, target_value, step, timer))
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timer.start(10) # Adjust the interval for animation speed
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def _animate_step(bar, target_value, step, timer) -> None:
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current_value = bar.value()
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new_value = current_value + step
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if (step > 0 and new_value > target_value) or (
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step < 0 and new_value < target_value
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):
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bar.setValue(target_value)
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timer.stop()
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else:
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bar.setValue(new_value)
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def update_download_progress(self, progress) -> None:
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self.download_progress.setValue(progress)
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def update_cuda_backends(self) -> None:
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self.logger.debug(UPDATING_CUDA_BACKENDS)
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self.backend_combo_cuda.clear()
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llama_bin = os.path.abspath("llama_bin")
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if os.path.exists(llama_bin):
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for item in os.listdir(llama_bin):
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item_path = os.path.join(llama_bin, item)
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if os.path.isdir(item_path) and "cudart-llama" not in item.lower():
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if "cu1" in item.lower(): # Only include CUDA-capable backends
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self.backend_combo_cuda.addItem(item, userData=item_path)
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if self.backend_combo_cuda.count() == 0:
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self.backend_combo_cuda.addItem(NO_SUITABLE_CUDA_BACKENDS)
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self.backend_combo_cuda.setEnabled(False)
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else:
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self.backend_combo_cuda.setEnabled(True)
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def update_threads_spinbox(self, value) -> None:
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self.threads_spinbox.setValue(value)
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def update_threads_slider(self, value) -> None:
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self.threads_slider.setValue(value)
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def update_gpu_offload_spinbox(self, value) -> None:
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self.gpu_offload_spinbox.setValue(value)
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def update_gpu_offload_slider(self, value) -> None:
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self.gpu_offload_slider.setValue(value)
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def update_cuda_option(self) -> None:
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self.logger.debug(UPDATING_CUDA_OPTIONS)
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asset = self.asset_combo.currentData()
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# Handle the case where asset is None
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if asset is None:
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self.logger.warning(NO_ASSET_SELECTED_FOR_CUDA_CHECK)
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self.cuda_extract_checkbox.setVisible(False)
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self.cuda_backend_label.setVisible(False)
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self.backend_combo_cuda.setVisible(False)
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return # Exit the function early
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is_cuda = asset and "cudart" in asset["name"].lower()
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self.cuda_extract_checkbox.setVisible(is_cuda)
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self.cuda_backend_label.setVisible(is_cuda)
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self.backend_combo_cuda.setVisible(is_cuda)
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if is_cuda:
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self.update_cuda_backends()
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def update_assets(self) -> None:
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self.logger.debug(UPDATING_ASSET_LIST)
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self.asset_combo.clear()
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release = self.release_combo.currentData()
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if release:
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if "assets" in release:
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for asset in release["assets"]:
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self.asset_combo.addItem(asset["name"], userData=asset)
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else:
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show_error(
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self.logger, NO_ASSETS_FOUND_FOR_RELEASE.format(release["tag_name"])
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)
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self.update_cuda_option()
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def update_base_model_visibility(self, index) -> None:
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is_gguf = self.lora_output_type_combo.itemText(index) == "GGUF"
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self.base_model_wrapper.setVisible(is_gguf)
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