mirror of https://github.com/leafspark/AutoGGUF
feat(ui): update Japanese and German localizations
- update Japanese and German localizations - bump version to v1.9.0 - optimize imports in main.py - organize function definitions in AutoGGUF.py
This commit is contained in:
BuildTools
parent
1133422456
commit
c02a02fbc1
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@ -0,0 +1,28 @@
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class ModelInfoDialog(QDialog):
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"""
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A dialog window for displaying model information.
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This class creates a dialog that shows detailed information about a machine learning model,
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including its architecture, quantization type, and other relevant data.
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Attributes:
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None
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Args:
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model_info (dict): A dictionary containing the model's information.
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parent (QWidget, optional): The parent widget of this dialog. Defaults to None.
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"""
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def format_model_info(self, model_info) -> str:
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"""
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Formats the model information into HTML for display.
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This method takes the raw model information and converts it into a formatted HTML string,
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which can be displayed in the dialog's QTextEdit widget.
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Args:
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model_info (dict): A dictionary containing the model's information.
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Returns:
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str: Formatted HTML string containing the model information.
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"""
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350
src/AutoGGUF.py
350
src/AutoGGUF.py
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@ -1237,6 +1237,181 @@ def save_task_preset(self, task_item) -> None:
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)
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break
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def download_finished(self, extract_dir) -> None:
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self.logger.info(DOWNLOAD_FINISHED_EXTRACTED_TO.format(extract_dir))
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self.download_button.setEnabled(True)
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self.download_progress.setValue(100)
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if (
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self.cuda_extract_checkbox.isChecked()
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and self.cuda_extract_checkbox.isVisible()
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):
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cuda_backend = self.backend_combo_cuda.currentData()
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if cuda_backend and cuda_backend != NO_SUITABLE_CUDA_BACKENDS:
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self.extract_cuda_files(extract_dir, cuda_backend)
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QMessageBox.information(
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self,
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DOWNLOAD_COMPLETE,
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LLAMACPP_DOWNLOADED_AND_EXTRACTED.format(extract_dir, cuda_backend),
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)
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else:
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QMessageBox.warning(
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self, CUDA_EXTRACTION_FAILED, NO_SUITABLE_CUDA_BACKEND_FOUND
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)
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else:
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QMessageBox.information(
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self,
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DOWNLOAD_COMPLETE,
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LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED.format(extract_dir),
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)
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self.refresh_backends() # Refresh the backends after successful download
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self.update_cuda_option() # Update CUDA options in case a CUDA-capable backend was downloaded
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# Select the newly downloaded backend
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new_backend_name = os.path.basename(extract_dir)
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index = self.backend_combo.findText(new_backend_name)
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if index >= 0:
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self.backend_combo.setCurrentIndex(index)
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def verify_gguf(self, file_path) -> bool:
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try:
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with open(file_path, "rb") as f:
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magic = f.read(4)
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return magic == b"GGUF"
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except (FileNotFoundError, IOError, OSError):
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return False
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def validate_quantization_inputs(self) -> None:
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self.logger.debug(VALIDATING_QUANTIZATION_INPUTS)
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errors = []
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if not self.backend_combo.currentData():
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errors.append(NO_BACKEND_SELECTED)
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if not self.models_input.text():
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errors.append(MODELS_PATH_REQUIRED)
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if not self.output_input.text():
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errors.append(OUTPUT_PATH_REQUIRED)
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if not self.logs_input.text():
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errors.append(LOGS_PATH_REQUIRED)
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if not self.model_tree.currentItem():
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errors.append(NO_MODEL_SELECTED)
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if errors:
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raise ValueError("\n".join(errors))
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def load_models(self) -> None:
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self.logger.info(LOADING_MODELS)
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models_dir = self.models_input.text()
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ensure_directory(models_dir)
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self.model_tree.clear()
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sharded_models = {}
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single_models = []
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concatenated_models = []
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shard_pattern = re.compile(r"(.*)-(\d+)-of-(\d+)\.gguf$")
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concat_pattern = re.compile(r"(.*)\.gguf\.part(\d+)of(\d+)$")
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for file in os.listdir(models_dir):
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full_path = os.path.join(models_dir, file)
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if file.endswith(".gguf"):
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if not self.verify_gguf(full_path):
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show_error(self.logger, INVALID_GGUF_FILE.format(file))
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continue
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match = shard_pattern.match(file)
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if match:
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base_name, shard_num, total_shards = match.groups()
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if base_name not in sharded_models:
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sharded_models[base_name] = []
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sharded_models[base_name].append((int(shard_num), file))
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else:
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single_models.append(file)
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else:
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match = concat_pattern.match(file)
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if match:
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concatenated_models.append(file)
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if hasattr(self, "imported_models"):
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for imported_model in self.imported_models:
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file_name = os.path.basename(imported_model)
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if (
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file_name not in single_models
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and file_name not in concatenated_models
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):
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if self.verify_gguf(imported_model):
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single_models.append(file_name)
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else:
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show_error(
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self.logger, INVALID_GGUF_FILE.format(imported_model)
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)
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for base_name, shards in sharded_models.items():
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parent_item = QTreeWidgetItem(self.model_tree)
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parent_item.setText(0, SHARDED_MODEL_NAME.format(base_name))
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first_shard = sorted(shards, key=lambda x: x[0])[0][1]
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parent_item.setData(0, Qt.ItemDataRole.UserRole, first_shard)
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for _, shard_file in sorted(shards):
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child_item = QTreeWidgetItem(parent_item)
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child_item.setText(0, shard_file)
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child_item.setData(0, Qt.ItemDataRole.UserRole, shard_file)
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for model in sorted(single_models):
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self.add_model_to_tree(model)
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for model in sorted(concatenated_models):
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item = self.add_model_to_tree(model)
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item.setForeground(0, Qt.gray)
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item.setToolTip(0, CONCATENATED_FILE_WARNING)
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self.model_tree.expandAll()
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self.logger.info(
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LOADED_MODELS.format(
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len(single_models) + len(sharded_models) + len(concatenated_models)
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)
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)
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if concatenated_models:
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self.logger.warning(
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CONCATENATED_FILES_FOUND.format(len(concatenated_models))
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)
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def add_model_to_tree(self, model) -> QTreeWidgetItem:
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item = QTreeWidgetItem(self.model_tree)
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item.setText(0, model)
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if hasattr(self, "imported_models") and model in [
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os.path.basename(m) for m in self.imported_models
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]:
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full_path = next(
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m for m in self.imported_models if os.path.basename(m) == model
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)
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item.setData(0, Qt.ItemDataRole.UserRole, full_path)
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item.setToolTip(0, IMPORTED_MODEL_TOOLTIP.format(full_path))
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else:
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item.setData(0, Qt.ItemDataRole.UserRole, model)
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return item
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def extract_cuda_files(self, extract_dir, destination) -> None:
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self.logger.info(EXTRACTING_CUDA_FILES.format(extract_dir, destination))
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for root, dirs, files in os.walk(extract_dir):
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for file in files:
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if file.lower().endswith(".dll"):
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source_path = os.path.join(root, file)
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dest_path = os.path.join(destination, file)
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shutil.copy2(source_path, dest_path)
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def download_error(self, error_message) -> None:
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self.logger.error(DOWNLOAD_ERROR.format(error_message))
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self.download_button.setEnabled(True)
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self.download_progress.setValue(0)
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show_error(self.logger, DOWNLOAD_FAILED.format(error_message))
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# Clean up any partially downloaded files
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asset = self.asset_combo.currentData()
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if asset:
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partial_file = os.path.join(os.path.abspath("llama_bin"), asset["name"])
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if os.path.exists(partial_file):
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os.remove(partial_file)
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def browse_local_path(self) -> None:
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if self.upload_type_file.isChecked():
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file_path, _ = QFileDialog.getOpenFileName(self, SELECT_FILE)
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@ -1444,65 +1619,6 @@ def convert_hf_to_gguf(self) -> None:
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show_error(self.logger, ERROR_STARTING_HF_TO_GGUF_CONVERSION.format(str(e)))
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self.logger.info(HF_TO_GGUF_CONVERSION_TASK_STARTED)
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def download_finished(self, extract_dir) -> None:
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self.logger.info(DOWNLOAD_FINISHED_EXTRACTED_TO.format(extract_dir))
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self.download_button.setEnabled(True)
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self.download_progress.setValue(100)
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if (
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self.cuda_extract_checkbox.isChecked()
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and self.cuda_extract_checkbox.isVisible()
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):
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cuda_backend = self.backend_combo_cuda.currentData()
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if cuda_backend and cuda_backend != NO_SUITABLE_CUDA_BACKENDS:
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self.extract_cuda_files(extract_dir, cuda_backend)
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QMessageBox.information(
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self,
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DOWNLOAD_COMPLETE,
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LLAMACPP_DOWNLOADED_AND_EXTRACTED.format(extract_dir, cuda_backend),
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)
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else:
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QMessageBox.warning(
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self, CUDA_EXTRACTION_FAILED, NO_SUITABLE_CUDA_BACKEND_FOUND
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)
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else:
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QMessageBox.information(
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self,
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DOWNLOAD_COMPLETE,
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LLAMACPP_BINARY_DOWNLOADED_AND_EXTRACTED.format(extract_dir),
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)
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self.refresh_backends() # Refresh the backends after successful download
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self.update_cuda_option() # Update CUDA options in case a CUDA-capable backend was downloaded
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# Select the newly downloaded backend
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new_backend_name = os.path.basename(extract_dir)
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index = self.backend_combo.findText(new_backend_name)
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if index >= 0:
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self.backend_combo.setCurrentIndex(index)
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def extract_cuda_files(self, extract_dir, destination) -> None:
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self.logger.info(EXTRACTING_CUDA_FILES.format(extract_dir, destination))
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for root, dirs, files in os.walk(extract_dir):
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for file in files:
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if file.lower().endswith(".dll"):
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source_path = os.path.join(root, file)
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dest_path = os.path.join(destination, file)
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shutil.copy2(source_path, dest_path)
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def download_error(self, error_message) -> None:
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self.logger.error(DOWNLOAD_ERROR.format(error_message))
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self.download_button.setEnabled(True)
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self.download_progress.setValue(0)
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show_error(self.logger, DOWNLOAD_FAILED.format(error_message))
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# Clean up any partially downloaded files
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asset = self.asset_combo.currentData()
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if asset:
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partial_file = os.path.join(os.path.abspath("llama_bin"), asset["name"])
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if os.path.exists(partial_file):
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os.remove(partial_file)
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def split_gguf(
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self, model_dir: str, output_dir: str, max_size: str, max_tensors: str
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) -> None:
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@ -1557,122 +1673,6 @@ def split_gguf(
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show_error(self.logger, SPLIT_GGUF_ERROR.format(e))
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self.logger.info(SPLIT_GGUF_TASK_FINISHED)
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def verify_gguf(self, file_path) -> bool:
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try:
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with open(file_path, "rb") as f:
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magic = f.read(4)
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return magic == b"GGUF"
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except (FileNotFoundError, IOError, OSError):
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return False
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def load_models(self) -> None:
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self.logger.info(LOADING_MODELS)
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models_dir = self.models_input.text()
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ensure_directory(models_dir)
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self.model_tree.clear()
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sharded_models = {}
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single_models = []
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concatenated_models = []
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shard_pattern = re.compile(r"(.*)-(\d+)-of-(\d+)\.gguf$")
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concat_pattern = re.compile(r"(.*)\.gguf\.part(\d+)of(\d+)$")
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for file in os.listdir(models_dir):
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full_path = os.path.join(models_dir, file)
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if file.endswith(".gguf"):
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if not self.verify_gguf(full_path):
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show_error(self.logger, INVALID_GGUF_FILE.format(file))
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continue
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match = shard_pattern.match(file)
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if match:
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base_name, shard_num, total_shards = match.groups()
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if base_name not in sharded_models:
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sharded_models[base_name] = []
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sharded_models[base_name].append((int(shard_num), file))
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else:
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single_models.append(file)
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else:
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match = concat_pattern.match(file)
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if match:
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concatenated_models.append(file)
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if hasattr(self, "imported_models"):
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for imported_model in self.imported_models:
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file_name = os.path.basename(imported_model)
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if (
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file_name not in single_models
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and file_name not in concatenated_models
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):
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if self.verify_gguf(imported_model):
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single_models.append(file_name)
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else:
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show_error(
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self.logger, INVALID_GGUF_FILE.format(imported_model)
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)
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for base_name, shards in sharded_models.items():
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parent_item = QTreeWidgetItem(self.model_tree)
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parent_item.setText(0, SHARDED_MODEL_NAME.format(base_name))
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first_shard = sorted(shards, key=lambda x: x[0])[0][1]
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parent_item.setData(0, Qt.ItemDataRole.UserRole, first_shard)
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for _, shard_file in sorted(shards):
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child_item = QTreeWidgetItem(parent_item)
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child_item.setText(0, shard_file)
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child_item.setData(0, Qt.ItemDataRole.UserRole, shard_file)
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for model in sorted(single_models):
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self.add_model_to_tree(model)
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for model in sorted(concatenated_models):
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item = self.add_model_to_tree(model)
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item.setForeground(0, Qt.gray)
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item.setToolTip(0, CONCATENATED_FILE_WARNING)
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self.model_tree.expandAll()
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self.logger.info(
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LOADED_MODELS.format(
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len(single_models) + len(sharded_models) + len(concatenated_models)
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)
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)
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if concatenated_models:
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self.logger.warning(
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CONCATENATED_FILES_FOUND.format(len(concatenated_models))
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)
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def add_model_to_tree(self, model) -> QTreeWidgetItem:
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item = QTreeWidgetItem(self.model_tree)
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item.setText(0, model)
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if hasattr(self, "imported_models") and model in [
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os.path.basename(m) for m in self.imported_models
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]:
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full_path = next(
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m for m in self.imported_models if os.path.basename(m) == model
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)
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item.setData(0, Qt.ItemDataRole.UserRole, full_path)
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item.setToolTip(0, IMPORTED_MODEL_TOOLTIP.format(full_path))
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else:
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item.setData(0, Qt.ItemDataRole.UserRole, model)
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return item
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def validate_quantization_inputs(self) -> None:
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self.logger.debug(VALIDATING_QUANTIZATION_INPUTS)
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errors = []
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if not self.backend_combo.currentData():
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errors.append(NO_BACKEND_SELECTED)
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if not self.models_input.text():
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errors.append(MODELS_PATH_REQUIRED)
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if not self.output_input.text():
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errors.append(OUTPUT_PATH_REQUIRED)
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if not self.logs_input.text():
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errors.append(LOGS_PATH_REQUIRED)
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if not self.model_tree.currentItem():
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errors.append(NO_MODEL_SELECTED)
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if errors:
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raise ValueError("\n".join(errors))
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def quantize_model(self) -> None:
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self.logger.info(STARTING_MODEL_QUANTIZATION)
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try:
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|
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File diff suppressed because it is too large
Load Diff
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@ -7,7 +7,7 @@
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from PySide6.QtCore import QTimer
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from PySide6.QtWidgets import QApplication
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from fastapi import FastAPI, Query, Depends, HTTPException, Security
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from fastapi.security.api_key import APIKeyHeader, APIKey
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from fastapi.security.api_key import APIKeyHeader
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from pydantic import BaseModel, Field
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from uvicorn import Config, Server
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