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import gradio as gr | |
import numpy as np | |
from resources.data import fixed_messages, topics_list | |
from utils.ui import add_candidate_message, add_interviewer_message | |
def get_codding_ui(llm, tts, stt, default_audio_params, audio_output): | |
with gr.Tab("Coding", render=False) as coding_tab: | |
chat_history = gr.State([]) | |
previous_code = gr.State("") | |
started_coding = gr.State(False) | |
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=topics_list, value="Arrays", 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): | |
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, | |
) | |
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], | |
outputs=[description], | |
scroll_to_output=True, | |
).success( | |
fn=llm.init_bot, inputs=[description], 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], 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]) | |
coding_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 coding_tab | |