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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 Loggers
async def settings(q: Q) -> None:
await clean_dashboard(q, mode="full")
q.client["nav/active"] = "settings"
label_width = "250px"
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("Dark Mode", width=label_width),
ui.toggle(
name="theme_dark",
value=q.client["theme_dark"],
tooltip="Enables Dark Mode as theme.",
trigger=True,
),
]
),
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 Loggers.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("Huggingface 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 Huggingface API token \
in the experiment setup.",
),
]
),
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("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 Chat Settings"),
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")
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