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import gradio as gr
import numpy as np
from resources.data import fixed_messages, topic_lists
from utils.ui import add_candidate_message, add_interviewer_message
def get_problem_solving_ui(llm, tts, stt, default_audio_params, audio_output, name="Coding", interview_type="coding"):
with gr.Tab(name, render=False) as problem_tab:
chat_history = gr.State([])
previous_code = gr.State("")
started_coding = gr.State(False)
interview_type = gr.State(interview_type)
with gr.Accordion("Settings") as init_acc:
with gr.Row():
with gr.Column():
gr.Markdown("##### Problem settings")
with gr.Row():
gr.Markdown("Difficulty")
difficulty_select = gr.Dropdown(
label="Select difficulty",
choices=["Easy", "Medium", "Hard"],
value="Medium",
container=False,
allow_custom_value=True,
)
with gr.Row():
gr.Markdown("Topic (can type custom value)")
topic_select = gr.Dropdown(
label="Select topic",
choices=topic_lists[interview_type.value],
value=topic_lists[interview_type.value][0],
container=False,
allow_custom_value=True,
)
with gr.Column(scale=2):
requirements = gr.Textbox(label="Requirements", placeholder="Specify additional requirements", lines=5)
start_btn = gr.Button("Generate a problem")
with gr.Accordion("Problem statement", open=True) as problem_acc:
description = gr.Markdown()
with gr.Accordion("Solution", open=False) as solution_acc:
with gr.Row() as content:
with gr.Column(scale=2):
if interview_type == "coding":
code = gr.Code(
label="Please write your code here. You can use any language, but only Python syntax highlighting is available.",
language="python",
lines=46,
)
else:
code = gr.Textbox(
label="Please write any notes for your solution here.",
lines=46,
max_lines=46,
show_label=False,
)
with gr.Column(scale=1):
end_btn = gr.Button("Finish the interview", interactive=False)
chat = gr.Chatbot(label="Chat", show_label=False, show_share_button=False)
message = gr.Textbox(
label="Message",
placeholder="Your message will appear here",
show_label=False,
lines=3,
max_lines=3,
interactive=False,
)
send_btn = gr.Button("Send", interactive=False)
audio_input = gr.Audio(interactive=False, **default_audio_params)
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) as feedback_acc:
feedback = gr.Markdown()
start_btn.click(fn=add_interviewer_message(fixed_messages["start"]), inputs=[chat], outputs=[chat]).success(
fn=lambda: True, outputs=[started_coding]
).success(fn=tts.read_last_message, inputs=[chat], outputs=[audio_output]).success(
fn=lambda: (gr.update(open=False), gr.update(interactive=False)), outputs=[init_acc, start_btn]
).success(
fn=llm.get_problem,
inputs=[requirements, difficulty_select, topic_select, interview_type],
outputs=[description],
scroll_to_output=True,
).success(
fn=llm.init_bot, inputs=[description, interview_type], outputs=[chat_history]
).success(
fn=lambda: (gr.update(open=True), gr.update(interactive=True), gr.update(interactive=True)),
outputs=[solution_acc, end_btn, audio_input],
)
end_btn.click(
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)),
outputs=[solution_acc, end_btn, problem_acc, audio_input],
).success(
fn=llm.end_interview, inputs=[description, chat_history, interview_type], 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: gr.update(interactive=False), outputs=[send_btn]
).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])
problem_tab.select(fn=add_interviewer_message(fixed_messages["intro"]), inputs=[chat, started_coding], outputs=[chat]).success(
fn=tts.read_last_message, inputs=[chat], outputs=[audio_output]
)
return problem_tab
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