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from pathlib import Path
import gradio as gr
from dotenv import load_dotenv
from fastrtc import WebRTC, get_twilio_turn_credentials
from gradio.utils import get_space
try:
from demo.llama_code_editor.handler import (
CodeHandler,
display_in_sandbox,
system_prompt,
)
except (ImportError, ModuleNotFoundError):
from handler import CodeHandler, display_in_sandbox, system_prompt
load_dotenv()
path = Path(__file__).parent / "assets"
with gr.Blocks(css=".code-component {max-height: 500px !important}") as demo:
history = gr.State([{"role": "system", "content": system_prompt}])
with gr.Row():
with gr.Column(scale=1):
gr.HTML(
"""
<h1 style='text-align: center'>
Llama Code Editor
</h1>
<h2 style='text-align: center'>
Powered by SambaNova and Gradio-WebRTC ⚡️
</h2>
<p style='text-align: center'>
Create and edit single-file HTML applications with just your voice!
</p>
<p style='text-align: center'>
Each conversation is limited to 90 seconds. Once the time limit is up you can rejoin the conversation.
</p>
"""
)
webrtc = WebRTC(
rtc_configuration=get_twilio_turn_credentials()
if get_space()
else None,
mode="send",
modality="audio",
)
with gr.Column(scale=10):
with gr.Tabs():
with gr.Tab("Sandbox"):
sandbox = gr.HTML(value=open(path / "sandbox.html").read())
with gr.Tab("Code"):
code = gr.Code(
language="html",
max_lines=50,
interactive=False,
elem_classes="code-component",
)
with gr.Tab("Chat"):
cb = gr.Chatbot(type="messages")
webrtc.stream(
CodeHandler,
inputs=[webrtc, history, code],
outputs=[webrtc],
time_limit=90 if get_space() else None,
concurrency_limit=10 if get_space() else None,
)
webrtc.on_additional_outputs(
lambda history, code: (history, code, history), outputs=[history, code, cb]
)
code.change(display_in_sandbox, code, sandbox, queue=False)
if __name__ == "__main__":
demo.launch()
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