rag / app.py
Deepak Sahu
first look
33080cc
raw
history blame
2.25 kB
import numpy as np
import gradio as gr
from z_generate import ServerlessInference
# STATIC TEXT DISPLAY
TXT_APP_DESCRIPTION = '''
Just another Retrieval Augmented Generation that also retrieves images
'''
TXT_SOURCE_DOC_DESCRIPTION = '''
Manually Downloaded as HTML files:
1. https://en.wikipedia.org/wiki/MS_Dhoni
2. https://en.wikipedia.org/wiki/Jharkhand
2. https://en.wikipedia.org/wiki/Cricket_World_Cup
'''
# UI Interface
demo = gr.Blocks()
llm = ServerlessInference()
# Processing Functions
def update_response(query:str = "something"):
return llm.test(query)
def update_gallery(text:str = "hell"):
imgs = [
("http://www.marketingtool.online/en/face-generator/img/faces/avatar-1151ce9f4b2043de0d2e3b7826127998.jpg", "Some Description"),
("http://www.marketingtool.online/en/face-generator/img/faces/avatar-116b5e92936b766b7fdfc242649337f7.jpg", "Another Description")
]
return imgs
def ask_bot(text):
return update_response(text), update_gallery(text)
# UI Layout
with demo:
gr.Markdown(TXT_APP_DESCRIPTION)
with gr.Tabs():
with gr.TabItem("Ask Bot"):
with gr.Row(equal_height=True):
with gr.Column(scale=3):
text_input = gr.Textbox(
label="You query here",
placeholder="What positions apart from crickter did Dhoni held?"
)
with gr.Column(scale=1):
btn_generate = gr.Button("Generate Answer")
with gr.Row():
with gr.Column(scale=3):
text_output = gr.Textbox(label="Bot Response:", placeholder="Type in Query before I could answer")
with gr.Column(scale=2):
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery"
, columns=[3], rows=[1], object_fit="contain", height="auto"
)
btn_generate.click(ask_bot, text_input, outputs=[text_output, gallery])
####
with gr.TabItem("Source Documents"):
gr.Markdown(TXT_SOURCE_DOC_DESCRIPTION)
demo.launch(debug=True)