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import os
import gradio as gr
from api.audio import STTManager, TTSManager
from api.llm import LLMManager
from config import config
from docs.instruction import instruction
from resources.data import fixed_messages, topics_list
from resources.prompts import prompts
from utils.ui import add_candidate_message, add_interviewer_message
llm = LLMManager(config, prompts)
tts = TTSManager(config)
stt = STTManager(config)
default_audio_params = {
"label": "Record answer",
"sources": ["microphone"],
"type": "numpy",
"waveform_options": {"show_controls": False},
"editable": False,
"container": False,
"show_share_button": False,
}
def hide_settings():
init_acc = gr.Accordion("Settings", open=False)
start_btn = gr.Button("Generate a problem", interactive=False)
return init_acc, start_btn
def show_solution():
solution_acc = gr.Accordion("Solution", open=True)
end_btn = gr.Button("Finish the interview", interactive=True)
audio_input = gr.Audio(interactive=True, **default_audio_params)
return solution_acc, end_btn, audio_input
def hide_solution():
solution_acc = gr.Accordion("Solution", open=False)
end_btn = gr.Button("Finish the interview", interactive=False)
problem_acc = gr.Accordion("Problem statement", open=False)
audio_input = gr.Audio(interactive=False, **default_audio_params)
return solution_acc, end_btn, problem_acc, audio_input
def get_status_color(obj):
if obj.status:
if obj.streaming:
return "π’"
return "π‘"
return "π΄"
# Interface
with gr.Blocks(title="AI Interviewer") as demo:
if os.getenv("IS_DEMO"):
gr.Markdown(instruction["demo"])
started_coding = gr.State(False)
audio_output = gr.Audio(label="Play audio", autoplay=True, visible=os.environ["DEBUG"], streaming=tts.streaming)
with gr.Tab("Instruction") as instruction_tab:
with gr.Row():
with gr.Column(scale=2):
gr.Markdown(instruction["introduction"])
with gr.Column(scale=1):
space = " " * 10
tts_status = get_status_color(tts)
gr.Markdown(f"TTS status: {tts_status}{space}{config.tts.name}")
try:
text_test = stt.speech_to_text(audio_test, False)
gr.Markdown(f"STT status: π’{space} {config.stt.name}")
except:
gr.Markdown(f"STT status: π΄{space} {config.stt.name}")
llm_status = get_status_color(llm)
gr.Markdown(f"LLM status: {llm_status}{space}{config.llm.name}")
gr.Markdown(instruction["quick_start"])
with gr.Row():
with gr.Column(scale=2):
gr.Markdown(instruction["interface"])
with gr.Column(scale=1):
gr.Markdown("Bot interaction area will look like this. Use Record button to record your answer.")
chat_example = gr.Chatbot(
label="Chat", show_label=False, show_share_button=False, value=[["Candidate message", "Interviewer message"]]
)
audio_input_example = gr.Audio(interactive=True, **default_audio_params)
gr.Markdown(instruction["models"])
gr.Markdown(instruction["acknowledgements"])
with gr.Tab("Coding") as coding_tab:
chat_history = gr.State([])
previous_code = gr.State("")
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=35,
)
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)
audio_input = gr.Audio(interactive=False, **default_audio_params)
message = gr.Textbox(label="Message", lines=3, visible=False)
with gr.Accordion("Feedback", open=True) as feedback_acc:
feedback = gr.Markdown()
# Events
coding_tab.select(fn=add_interviewer_message(fixed_messages["intro"]), inputs=[chat, started_coding], outputs=[chat])
start_btn.click(fn=add_interviewer_message(fixed_messages["start"]), inputs=[chat], outputs=[chat]).then(
fn=lambda: True, outputs=[started_coding]
).then(fn=hide_settings, outputs=[init_acc, start_btn]).then(
fn=llm.get_problem,
inputs=[requirements, difficulty_select, topic_select],
outputs=[description],
scroll_to_output=True,
).then(
fn=llm.init_bot, inputs=[description], outputs=[chat_history]
).then(
fn=show_solution, outputs=[solution_acc, end_btn, audio_input]
)
end_btn.click(
fn=add_interviewer_message(fixed_messages["end"]),
inputs=[chat],
outputs=[chat],
).then(
fn=hide_solution, outputs=[solution_acc, end_btn, problem_acc, audio_input]
).then(fn=llm.end_interview, inputs=[description, chat_history], outputs=[feedback])
audio_input.stop_recording(fn=stt.speech_to_text, inputs=[audio_input], outputs=[message]).then(
fn=lambda: None, outputs=[audio_input]
).then(fn=add_candidate_message, inputs=[message, chat], outputs=[chat]).then(
fn=llm.send_request,
inputs=[code, previous_code, message, chat_history, chat],
outputs=[chat_history, chat, message, previous_code],
)
chat.change(fn=tts.read_last_message, inputs=[chat], outputs=[audio_output])
demo.launch(show_api=False)
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