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| import multiprocessing | |
| import torch | |
| from h2o_wave import Q, ui | |
| from llm_studio.app_utils.sections.common import clean_dashboard | |
| from llm_studio.app_utils.setting_utils import Secrets | |
| from llm_studio.src.loggers import ExternalLoggers | |
| async def settings(q: Q) -> None: | |
| await clean_dashboard(q, mode="full") | |
| q.client["nav/active"] = "settings" | |
| label_width = "280px" | |
| textbox_width = "350px" | |
| q.page["settings/content"] = ui.form_card( | |
| box="content", | |
| items=[ | |
| ui.message_bar( | |
| type="info", | |
| text="Setting changes are directly applied for the \ | |
| current session and can be made persistent by using the \ | |
| ***Save settings persistently*** button below. To reload \ | |
| the persistently saved settings, use the ***Load settings*** button.", | |
| ), | |
| ui.separator("Credential Storage"), | |
| ui.inline( | |
| items=[ | |
| ui.label("Credential Handler", width=label_width), | |
| ui.dropdown( | |
| name="credential_saver", | |
| value=q.client["credential_saver"], | |
| choices=[ui.choice(name, name) for name in Secrets.names()], | |
| trigger=False, | |
| width="300px", | |
| ), | |
| ] | |
| ), | |
| ui.message_bar( | |
| type="info", | |
| text="""Method used to save credentials (passwords) \ | |
| for ***Save settings persistently***. \ | |
| The recommended approach for saving credentials (passwords) is to \ | |
| use either Keyring or to avoid permanent storage \ | |
| (requiring re-entry upon app restart). \ | |
| Keyring will be disabled if it is not set up on the host machine. \ | |
| Only resort to local .env if your machine's \ | |
| accessibility is restricted to you.\n\ | |
| When you select ***Save settings persistently***, \ | |
| credentials will be removed from all non-selected methods. \ | |
| ***Restore Default Settings*** will clear credentials from all methods. | |
| """, | |
| ), | |
| ui.separator("Appearance"), | |
| ui.inline( | |
| items=[ | |
| ui.label("Delete Dialogs", width=label_width), | |
| ui.toggle( | |
| name="delete_dialogs", | |
| value=q.client["delete_dialogs"], | |
| trigger=False, | |
| tooltip=( | |
| "Whether to show delete dialogs before deleting " | |
| "datasets or experiments." | |
| ), | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Maximum Chart Points", width=label_width), | |
| ui.spinbox( | |
| name="chart_plot_max_points", | |
| label=None, | |
| min=1, | |
| max=10000, | |
| step=1000, | |
| value=q.client["chart_plot_max_points"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum number of points shown in the " | |
| "experiment chart plots. Plots will be sub-sampled if " | |
| "needed.", | |
| ), | |
| ] | |
| ), | |
| ui.separator("Default Connector Settings"), | |
| ui.inline( | |
| items=[ | |
| ui.label("AWS S3 bucket name", width=label_width), | |
| ui.textbox( | |
| name="default_aws_bucket_name", | |
| label=None, | |
| value=q.client["default_aws_bucket_name"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the value for the AWS bucket for \ | |
| dataset import. S3 bucket name including relative paths.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("AWS access key", width=label_width), | |
| ui.textbox( | |
| name="default_aws_access_key", | |
| label=None, | |
| value=q.client["default_aws_access_key"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the AWS access key \ | |
| for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("AWS secret key", width=label_width), | |
| ui.textbox( | |
| name="default_aws_secret_key", | |
| label=None, | |
| value=q.client["default_aws_secret_key"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the AWS secret key \ | |
| for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Azure Datalake connection string", width=label_width), | |
| ui.textbox( | |
| name="default_azure_conn_string", | |
| label=None, | |
| value=q.client["default_azure_conn_string"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the Azure Datalake \ | |
| connection string for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Azure Datalake container name", width=label_width), | |
| ui.textbox( | |
| name="default_azure_container", | |
| label=None, | |
| value=q.client["default_azure_container"], | |
| width=textbox_width, | |
| password=False, | |
| trigger=False, | |
| tooltip="Set the value for the Azure Datalake \ | |
| container name for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Kaggle username", width=label_width), | |
| ui.textbox( | |
| name="default_kaggle_username", | |
| label=None, | |
| value=q.client["default_kaggle_username"], | |
| width=textbox_width, | |
| password=False, | |
| trigger=False, | |
| tooltip="Set the value for the Kaggle username \ | |
| for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Kaggle secret key", width=label_width), | |
| ui.textbox( | |
| name="default_kaggle_secret_key", | |
| label=None, | |
| value=q.client["default_kaggle_secret_key"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the Kaggle secret key \ | |
| for dataset import.", | |
| ), | |
| ] | |
| ), | |
| ui.separator("Default Experiment Settings"), | |
| ui.inline( | |
| items=[ | |
| ui.label("Number of Workers", width=label_width), | |
| ui.spinbox( | |
| name="default_number_of_workers", | |
| label=None, | |
| min=1, | |
| max=multiprocessing.cpu_count(), | |
| step=1, | |
| value=q.client["default_number_of_workers"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the value for the number of workers \ | |
| sliders in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Logger", width=label_width), | |
| ui.dropdown( | |
| name="default_logger", | |
| value=q.client["default_logger"], | |
| choices=[ | |
| ui.choice(name, name) for name in ExternalLoggers.names() | |
| ], | |
| trigger=False, | |
| width="100px", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Neptune Project", width=label_width), | |
| ui.textbox( | |
| name="default_neptune_project", | |
| label=None, | |
| value=q.client["default_neptune_project"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the value for the neptune project \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Neptune API Token", width=label_width), | |
| ui.textbox( | |
| name="default_neptune_api_token", | |
| label=None, | |
| value=q.client["default_neptune_api_token"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the Neptune API token \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Wandb Project", width=label_width), | |
| ui.textbox( | |
| name="default_wandb_project", | |
| label=None, | |
| value=q.client["default_wandb_project"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the value for the Wandb project \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Wandb Entity", width=label_width), | |
| ui.textbox( | |
| name="default_wandb_entity", | |
| label=None, | |
| value=q.client["default_wandb_entity"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the value for the Wandb entity \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Wandb API Token", width=label_width), | |
| ui.textbox( | |
| name="default_wandb_api_token", | |
| label=None, | |
| value=q.client["default_wandb_api_token"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the Wandb API token \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Hugging Face API Token", width=label_width), | |
| ui.textbox( | |
| name="default_huggingface_api_token", | |
| label=None, | |
| value=q.client["default_huggingface_api_token"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the Hugging Face API token \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Hugging Face Hub Enable HF Transfer", width=label_width), | |
| ui.toggle( | |
| name="default_hf_hub_enable_hf_transfer", | |
| value=( | |
| True | |
| if q.client["default_hf_hub_enable_hf_transfer"] | |
| else False | |
| ), | |
| tooltip=( | |
| "Toggle to enable \ | |
| <a href='https://github.com/huggingface/hf_transfer' \ | |
| target='_blank'>HF Transfer</a> for faster \ | |
| downloads. Toggle, if you are experiencing issues on down-\ | |
| or upload. EXPERIMENTAL." | |
| ), | |
| trigger=False, | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("OpenAI API Token", width=label_width), | |
| ui.textbox( | |
| name="default_openai_api_token", | |
| label=None, | |
| value=q.client["default_openai_api_token"], | |
| width=textbox_width, | |
| password=True, | |
| trigger=False, | |
| tooltip="Set the value for the OpenAI API token \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("GPT evaluation max samples", width=label_width), | |
| ui.spinbox( | |
| name="default_gpt_eval_max", | |
| label=None, | |
| value=q.client["default_gpt_eval_max"], | |
| width=textbox_width, | |
| min=1, | |
| max=10000, | |
| step=1, | |
| trigger=False, | |
| tooltip="Set the maximum samples for GPT evaluation. \ | |
| This is used to prevent unexpected high API costs. \ | |
| Increase at your own risk.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Use OpenAI API on Azure", width=label_width), | |
| ui.toggle( | |
| name="default_openai_azure", | |
| value=q.client["default_openai_azure"], | |
| tooltip=( | |
| "Toggle to use Microsoft Azure Endpoints for the " | |
| "OpenAI API." | |
| ), | |
| trigger=True, | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("OpenAI API Endpoint", width=label_width), | |
| ui.textbox( | |
| name="default_openai_api_base", | |
| label=None, | |
| value=q.client["default_openai_api_base"], | |
| width=textbox_width, | |
| password=False, | |
| trigger=False, | |
| tooltip=( | |
| "Set the value for the OpenAI API endpoint. " | |
| "Use when on Azure." | |
| ), | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("OpenAI API Deployment ID", width=label_width), | |
| ui.textbox( | |
| name="default_openai_api_deployment_id", | |
| label=None, | |
| value=q.client["default_openai_api_deployment_id"], | |
| width=textbox_width, | |
| password=False, | |
| trigger=False, | |
| tooltip=( | |
| "Set the value for the OpenAI API deployment ID. " | |
| "Use when on Azure." | |
| ), | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("OpenAI API version", width=label_width), | |
| ui.textbox( | |
| name="default_openai_api_version", | |
| label=None, | |
| value=q.client["default_openai_api_version"], | |
| width=textbox_width, | |
| password=False, | |
| trigger=False, | |
| tooltip=( | |
| "Set the value for the OpenAI API version. " | |
| "Use when on Azure." | |
| ), | |
| ), | |
| ] | |
| ), | |
| ui.separator("Experiment Maximum Settings"), | |
| ui.inline( | |
| items=[ | |
| ui.label("Number of Epochs", width=label_width), | |
| ui.spinbox( | |
| name="set_max_epochs", | |
| label=None, | |
| min=1, | |
| max=2000, | |
| step=1, | |
| value=q.client["set_max_epochs"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the epoch slider \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Batch Size", width=label_width), | |
| ui.spinbox( | |
| name="set_max_batch_size", | |
| label=None, | |
| min=1, | |
| max=4096, | |
| step=1, | |
| value=q.client["set_max_batch_size"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the batch size slider \ | |
| in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Num Classes", width=label_width), | |
| ui.spinbox( | |
| name="set_max_num_classes", | |
| label=None, | |
| min=1, | |
| max=16384, | |
| step=1, | |
| value=q.client["set_max_num_classes"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the num classes \ | |
| slider in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Max Length", width=label_width), | |
| ui.spinbox( | |
| name="set_max_max_length", | |
| label=None, | |
| min=1, | |
| max=16384 * 8, | |
| step=1, | |
| value=q.client["set_max_max_length"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the max length \ | |
| slider in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("Gradient clip", width=label_width), | |
| ui.spinbox( | |
| name="set_max_gradient_clip", | |
| label=None, | |
| min=1, | |
| max=16384, | |
| step=1, | |
| value=q.client["set_max_gradient_clip"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the gradient clip \ | |
| slider in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("LoRA R", width=label_width), | |
| ui.spinbox( | |
| name="set_max_lora_r", | |
| label=None, | |
| min=1, | |
| max=16384, | |
| step=1, | |
| value=q.client["set_max_lora_r"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the LoRA R \ | |
| slider in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("LoRA alpha", width=label_width), | |
| ui.spinbox( | |
| name="set_max_lora_alpha", | |
| label=None, | |
| min=1, | |
| max=16384, | |
| step=1, | |
| value=q.client["set_max_lora_alpha"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the maximum value for the LoRA Alpha \ | |
| slider in the experiment setup.", | |
| ), | |
| ] | |
| ), | |
| ui.separator("Default System Settings"), | |
| ui.inline( | |
| items=[ | |
| ui.label("GPU used for Download", width=label_width), | |
| ui.dropdown( | |
| name="gpu_used_for_download", | |
| label=None, | |
| value=q.client["gpu_used_for_download"], | |
| width=textbox_width, | |
| choices=[ | |
| ui.choice(str(d), str(d)) | |
| for d in ["cpu", "cpu_shard"] | |
| + [ | |
| f"cuda:{idx}" | |
| for idx in range(torch.cuda.device_count()) | |
| ] | |
| ], | |
| tooltip=( | |
| "The local device to prepare the model before pushing " | |
| "it to HF or downloading. CPU will never load the weights " | |
| "to the GPU, which can be useful " | |
| "for large models, but will be significantly slower. " | |
| "Cpu_shard will first load on CPU and then shard " | |
| "on all GPUs before pushing to HF." | |
| ), | |
| ), | |
| ] | |
| ), | |
| ui.inline( | |
| items=[ | |
| ui.label("GPU used for Chat", width=label_width), | |
| ui.spinbox( | |
| name="gpu_used_for_chat", | |
| label=None, | |
| min=1, | |
| max=torch.cuda.device_count(), | |
| step=1, | |
| value=q.client["gpu_used_for_chat"], | |
| width=textbox_width, | |
| trigger=False, | |
| tooltip="Set the gpu id that is used for the chat window.", | |
| ), | |
| ] | |
| ), | |
| ], | |
| ) | |
| q.client.delete_cards.add("settings/content") | |
| q.page["settings/footer"] = ui.form_card( | |
| box="footer", | |
| items=[ | |
| ui.inline( | |
| items=[ | |
| ui.button( | |
| name="save_settings", | |
| label="Save settings persistently", | |
| primary=True, | |
| ), | |
| ui.button( | |
| name="load_settings", label="Load settings", primary=False | |
| ), | |
| ui.button( | |
| name="restore_default_settings", | |
| label="Restore default settings", | |
| primary=False, | |
| ), | |
| ], | |
| justify="start", | |
| ) | |
| ], | |
| ) | |
| q.client.delete_cards.add("settings/footer") | |