File size: 1,921 Bytes
acfcb6f 6b3dc32 acfcb6f 6b3dc32 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
from ailab_crs import NLP_tasks_crs, Prompt_engineering_crs
import gradio as gr
from googletrans import LANGUAGES
def main():
nlp_tasks = NLP_tasks_crs()
supported_langs = list(LANGUAGES.values())
with gr.Blocks() as demo:
gr.Markdown("# 🧠 NaanAI 💡")
with gr.Row():
with gr.Column():
text = gr.Textbox(label="Your Query", lines=8)
with gr.Column():
with gr.Accordion("Other Parameters (For Translation or Summarization Tasks)", open= True):
# language = gr.Textbox(label="Language")
language = gr.Dropdown(choices=supported_langs, label="Select Target Language", value="english")
style = gr.Textbox(label="Choose Your Style", value="polite")
with gr.Row(scale=5):
with gr.Column(scale=1, min_width=1):
btn = gr.Button("Q&A")
with gr.Column(scale=2, min_width=1):
btn1 = gr.Button("Translator")
with gr.Column(scale=2, min_width=1):
btn2 = gr.Button("Summarizer")
with gr.Column(scale=2, min_width=1):
btn3 = gr.Button("Translator_Summarizer")
answer = gr.Textbox(label="AI Answer", lines=2)
btn.click(
fn= nlp_tasks.question_answer,
inputs= text,
outputs=answer
)
btn1.click(
fn= nlp_tasks.translator,
inputs= [text, language, style],
outputs=answer
)
btn2.click(
fn= nlp_tasks.summarization,
inputs= text,
outputs=answer
)
btn3.click(
fn= nlp_tasks.translator_summarization,
inputs= [text, language, style],
outputs=answer
)
return demo.launch()
if __name__ == "__main__":
main()
|