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import gradio as gr
import numpy as np
import os
from resources.data import fixed_messages, topic_lists
from utils.ui import add_candidate_message, add_interviewer_message
def change_code_area(interview_type):
if interview_type == "coding":
return gr.update(
label="Please write your code here. You can use any language, but only Python syntax highlighting is available.",
language="python",
)
elif interview_type == "sql":
return gr.update(
label="Please write your query here.",
language="sql",
)
else:
return gr.update(
label="Please write any notes for your solution here.",
language=None,
)
def get_problem_solving_ui(llm, tts, stt, default_audio_params, audio_output):
with gr.Tab("Interview", render=False, elem_id=f"tab") as problem_tab:
chat_history = gr.State([])
previous_code = gr.State("")
hi_markdown = gr.Markdown(
"<h2 style='text-align: center;'> Hi! I'm here to guide you through a practice session for your technical interview. Choose the interview settings to begin.</h2>\n"
)
with gr.Row() as init_acc:
with gr.Column(scale=3):
interview_type_select = gr.Dropdown(
show_label=False,
info="Type of the interview.",
choices=["coding", "ml_design", "ml_theory", "system_design", "math", "sql"],
value="coding",
container=True,
allow_custom_value=False,
elem_id=f"interview_type_select",
scale=2,
)
difficulty_select = gr.Dropdown(
show_label=False,
info="Difficulty of the problem.",
choices=["Easy", "Medium", "Hard"],
value="Medium",
container=True,
allow_custom_value=True,
elem_id=f"difficulty_select",
scale=2,
)
topic_select = gr.Dropdown(
show_label=False,
info="Topic (you can type any value).",
choices=topic_lists[interview_type_select.value],
value=np.random.choice(topic_lists[interview_type_select.value]),
container=True,
allow_custom_value=True,
elem_id=f"topic_select",
scale=2,
)
with gr.Column(scale=4):
requirements = gr.Textbox(
label="Requirements",
show_label=False,
placeholder="Specify additional requirements if any.",
container=False,
lines=5,
elem_id=f"requirements",
)
with gr.Row():
terms_checkbox = gr.Checkbox(
label="",
container=False,
value=not os.getenv("IS_DEMO", False),
interactive=True,
elem_id=f"terms_checkbox",
min_width=20,
)
with gr.Column(scale=100):
gr.Markdown(
"#### I agree to the [terms and conditions](https://github.com/IliaLarchenko/Interviewer?tab=readme-ov-file#important-legal-and-compliance-information)"
)
start_btn = gr.Button("Generate a problem", elem_id=f"start_btn", interactive=not os.getenv("IS_DEMO", False))
with gr.Accordion("Problem statement", open=True, visible=False) as problem_acc:
description = gr.Markdown(elem_id=f"problem_description", line_breaks=True)
with gr.Accordion("Solution", open=True, visible=False) as solution_acc:
with gr.Row() as content:
with gr.Column(scale=2):
code = gr.Code(
label="Please write your code here.",
language="python",
lines=46,
elem_id=f"code",
)
with gr.Column(scale=1):
end_btn = gr.Button("Finish the interview", interactive=False, variant="stop", elem_id=f"end_btn")
chat = gr.Chatbot(label="Chat", show_label=False, show_share_button=False, elem_id=f"chat")
message = gr.Textbox(
label="Message",
show_label=False,
lines=3,
max_lines=3,
interactive=True,
container=False,
elem_id=f"message",
)
send_btn = gr.Button("Send", interactive=False, elem_id=f"send_btn")
audio_input = gr.Audio(interactive=False, **default_audio_params, elem_id=f"audio_input")
audio_buffer = gr.State(np.array([], dtype=np.int16))
transcript = gr.State({"words": [], "not_confirmed": 0, "last_cutoff": 0, "text": ""})
with gr.Accordion("Feedback", open=True, visible=False) as feedback_acc:
feedback = gr.Markdown(elem_id=f"feedback", line_breaks=True)
# Start button click action chain
start_btn.click(fn=add_interviewer_message(fixed_messages["start"]), inputs=[chat], outputs=[chat]).success(
fn=tts.read_last_message, inputs=[chat], outputs=[audio_output]
).success(
fn=lambda: (
gr.update(visible=False),
gr.update(interactive=False),
gr.update(interactive=False),
gr.update(interactive=False),
gr.update(visible=False),
),
outputs=[init_acc, start_btn, terms_checkbox, interview_type_select, hi_markdown],
).success(
fn=lambda: (gr.update(visible=True)),
outputs=[problem_acc],
).success(
fn=llm.get_problem,
inputs=[requirements, difficulty_select, topic_select, interview_type_select],
outputs=[description],
scroll_to_output=True,
).success(
fn=llm.init_bot, inputs=[description, interview_type_select], outputs=[chat_history]
).success(
fn=lambda: (gr.update(visible=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True)),
outputs=[solution_acc, end_btn, audio_input, send_btn],
)
end_btn.click(fn=lambda x: add_candidate_message("Let's stop here.", x), inputs=[chat], outputs=[chat]).success(
fn=add_interviewer_message(fixed_messages["end"]),
inputs=[chat],
outputs=[chat],
).success(fn=tts.read_last_message, inputs=[chat], outputs=[audio_output]).success(
fn=lambda: (
gr.update(open=False),
gr.update(interactive=False),
gr.update(open=False),
gr.update(interactive=False),
gr.update(interactive=False),
),
outputs=[solution_acc, end_btn, problem_acc, audio_input, send_btn],
).success(
fn=lambda: (gr.update(visible=True)),
outputs=[feedback_acc],
).success(
fn=llm.end_interview, inputs=[description, chat_history, interview_type_select], outputs=[feedback]
)
send_btn.click(fn=add_candidate_message, inputs=[message, chat], outputs=[chat]).success(
fn=lambda: None, outputs=[message]
).success(
fn=llm.send_request,
inputs=[code, previous_code, chat_history, chat],
outputs=[chat_history, chat, previous_code],
).success(
fn=tts.read_last_message, inputs=[chat], outputs=[audio_output]
).success(
fn=lambda: np.array([], dtype=np.int16), outputs=[audio_buffer]
).success(
fn=lambda: {"words": [], "not_confirmed": 0, "last_cutoff": 0, "text": ""}, outputs=[transcript]
)
if stt.streaming:
audio_input.stream(
stt.process_audio_chunk,
inputs=[audio_input, audio_buffer, transcript],
outputs=[transcript, audio_buffer, message],
show_progress="hidden",
)
audio_input.stop_recording(fn=lambda: gr.update(interactive=True), outputs=[send_btn])
else:
audio_input.stop_recording(fn=stt.speech_to_text_full, inputs=[audio_input], outputs=[message]).success(
fn=lambda: gr.update(interactive=True), outputs=[send_btn]
).success(fn=lambda: None, outputs=[audio_input])
interview_type_select.change(
fn=lambda x: gr.update(choices=topic_lists[x], value=np.random.choice(topic_lists[x])),
inputs=[interview_type_select],
outputs=[topic_select],
).success(fn=change_code_area, inputs=[interview_type_select], outputs=[code])
terms_checkbox.change(fn=lambda x: gr.update(interactive=x), inputs=[terms_checkbox], outputs=[start_btn])
return problem_tab
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