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import gradio as gr
import numpy as np
from loguru import logger
from app_configs import AVAILABLE_MODELS, UNSELECTED_VAR_NAME
from components import commons
from components.structs import TossupPipelineState
from components.typed_dicts import TossupPipelineStateDict
from display.formatting import tiny_styled_warning
from workflows.structs import Buzzer, TossupWorkflow
from .model_pipeline import PipelineInterface, PipelineState, PipelineUIState
def toggleable_slider(
value, minimum, maximum, step, toggle_value=False, label=None, info=None, min_width=200, scale=1
):
with gr.Column(elem_classes="toggleable", min_width=min_width, scale=scale):
show_label = label is not None
checkbox = gr.Checkbox(label=label, value=toggle_value, container=False, info=info, show_label=show_label)
slider = gr.Slider(
minimum=minimum,
maximum=maximum,
value=value,
step=step,
label="",
interactive=True,
show_label=False,
container=False,
)
checkbox.change(fn=lambda x: gr.update(interactive=x), inputs=[checkbox], outputs=[slider])
return checkbox, slider
class TossupPipelineInterface(PipelineInterface):
def __init__(
self,
app: gr.Blocks,
workflow: TossupWorkflow,
ui_state: PipelineUIState | None = None,
model_options: list[str] = None,
config: dict = {},
):
super().__init__(app, workflow, ui_state, model_options, config)
self.buzzer_state = gr.State(workflow.buzzer.model_dump())
self.pipeline_state.change(
lambda x: TossupPipelineState(**x).workflow.buzzer.model_dump(),
inputs=[self.pipeline_state],
outputs=[self.buzzer_state],
)
def update_prob_slider(
self, state_dict: TossupPipelineStateDict, answer_var: str, tokens_prob: float | None
) -> tuple[TossupPipelineStateDict, dict, dict, dict]:
"""Update the probability slider based on the answer variable."""
state = TossupPipelineState(**state_dict)
if answer_var == UNSELECTED_VAR_NAME:
return (
state.model_dump(),
gr.update(interactive=True),
gr.update(value="AND", interactive=True),
gr.update(visible=False),
)
logprobs_supported = state.workflow.is_token_probs_supported(answer_var)
buzzer = state.workflow.buzzer
tokens_prob_threshold = tokens_prob if logprobs_supported else None
method = buzzer.method if logprobs_supported else "AND"
state.workflow.buzzer = Buzzer(
method=method,
confidence_threshold=buzzer.confidence_threshold,
prob_threshold=tokens_prob_threshold,
)
model_name = state.workflow.get_answer_model(answer_var)
return (
state.model_dump(),
gr.update(interactive=logprobs_supported, value=tokens_prob if logprobs_supported else 0.0),
gr.update(value=method, interactive=logprobs_supported),
gr.update(
value=tiny_styled_warning(
f"<code>'{model_name}'</code> does not support <code>'logprobs'</code>. The probability slider will be disabled."
),
visible=not logprobs_supported,
),
)
def _render_buzzer_panel(
self, buzzer: Buzzer, prob_slider_supported: bool, selected_model_name: str | None = None
):
with gr.Row(elem_classes="control-panel"):
self.confidence_slider = gr.Slider(
minimum=0.0,
maximum=1.0,
value=buzzer.confidence_threshold,
step=0.01,
label="Confidence",
elem_classes="slider-container",
show_reset_button=False,
)
value = buzzer.method if prob_slider_supported else "AND"
self.buzzer_method_dropdown = gr.Dropdown(
choices=["AND", "OR"],
value=value,
label="Method",
interactive=prob_slider_supported,
min_width=80,
scale=0,
)
self.prob_slider = gr.Slider(
value=buzzer.prob_threshold or 0.0,
interactive=prob_slider_supported,
label="Probability",
minimum=0.0,
maximum=1.0,
step=0.001,
elem_classes="slider-container",
show_reset_button=False,
)
display_html = ""
if selected_model_name is not None:
display_html = tiny_styled_warning(
f"<code>{selected_model_name}</code> does not support <code>logprobs</code>. The probability slider will be disabled."
)
self.buzzer_warning_display = gr.HTML(display_html, visible=not prob_slider_supported)
def _render_output_panel(self, pipeline_state: TossupPipelineState):
dropdowns = {}
available_variables = pipeline_state.workflow.get_available_variables()
variable_options = [UNSELECTED_VAR_NAME] + [v for v in available_variables if v not in self.input_variables]
with gr.Column(elem_classes="step-accordion control-panel"):
commons.get_panel_header(
header="Final output variables mapping:",
)
with gr.Row(elem_classes="output-fields-row"):
for output_field in self.required_output_variables:
value = pipeline_state.workflow.outputs.get(output_field)
value = value or UNSELECTED_VAR_NAME
dropdown = gr.Dropdown(
label=output_field,
value=value,
choices=variable_options,
interactive=True,
elem_classes="output-field-variable",
# show_label=False,
)
dropdown.change(
self.sm.update_output_variables,
inputs=[self.pipeline_state, gr.State(output_field), dropdown],
outputs=[self.pipeline_state],
)
dropdowns[output_field] = dropdown
commons.get_panel_header(
header="Buzzer settings:",
subheader="Set your thresholds for confidence and output tokens probability (computed using <code>logprobs</code>).",
)
logprobs_supported = pipeline_state.workflow.is_token_probs_supported()
selected_model_name = pipeline_state.workflow.get_answer_model()
self._render_buzzer_panel(pipeline_state.workflow.buzzer, logprobs_supported, selected_model_name)
def update_choices(available_variables: list[str]):
"""Update the choices for the dropdowns"""
return [gr.update(choices=available_variables, value=None, selected=None) for _ in dropdowns.values()]
self.variables_state.change(
update_choices,
inputs=[self.variables_state],
outputs=list(dropdowns.values()),
)
# Updating the pipeline buzzer on user input changes in Buzzer panel.
gr.on(
triggers=[
self.confidence_slider.release,
self.buzzer_method_dropdown.input,
self.prob_slider.release,
],
fn=self.sm.update_buzzer,
inputs=[self.pipeline_state, self.confidence_slider, self.buzzer_method_dropdown, self.prob_slider],
outputs=[self.pipeline_state],
)
# THIS WASN't NEEDED SINCE WE RERENDER THE OUTPUT PANEL ENTIRELY ON CHANGES
# answer_dropdown = dropdowns["answer"]
# if answer_dropdown is not None:
# gr.on(
# triggers=[self.buzzer_state.change],
# fn=self.update_prob_slider,
# inputs=[self.buzzer_state, answer_dropdown, self.prob_slider],
# outputs=[
# self.pipeline_state,
# self.prob_slider,
# self.buzzer_method_dropdown,
# self.buzzer_warning_display,
# ],
# )
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