Spaces:
Running
Running
File size: 3,297 Bytes
0aa5d4d f0e795d 0aa5d4d |
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 63 64 65 66 67 68 69 70 71 72 73 |
import random
import time
import gradio as gr
from create_query_engine import *
logo_filepath = 'Readable.png'
robot_filepath = 'Robot.png'
custom_css = """
.column {
align-items: center;
}
.column_el {
flex-grow: 1;
}
"""
def respond(message, chat_history, query_engine, sql_engine):
response = query_engine.query(message)
bot_message = response.response
chat_history.append((message, bot_message))
time.sleep(2)
return "", chat_history, display_question_and_answer(chat_history), query(sql_engine, response.metadata['sql_query']), response.metadata['sql_query']
def display_question_and_answer(tuple_list):
qa_history = ""
for i, (q, a) in enumerate(tuple_list):
qa_history += f"<details><summary>Q: {q}</summary><p>A: {a}</p></details>"
return qa_history
with gr.Blocks(css=custom_css) as demo:
with gr.Tab("Home"):
with gr.Row(variant='compact'):
with gr.Column(scale=1, elem_classes='column'):
logo = gr.Image(value=logo_filepath, type='pil', show_label=False, show_download_button=False, container=False, elem_classes='column_el')
agent = gr.State()
file = gr.File(file_types=['pdf'], file_count='single', show_label=False, elem_classes='column_el', height=75)
SQLidx = gr.State()
sql_engine = gr.State()
# Connect to database + give context pane
with gr.Accordion("Command String Details"):
gr.Markdown("Enter command string details here")
with gr.Row():
user = gr.Textbox(value='postgres', label="Username")
password = gr.Textbox(value='aimfall23',label="Password")
with gr.Row():
host = gr.Textbox(value='aim-23-text-to-sql.cv6cnzb0rcuo.us-east-1.rds.amazonaws.com',label="Host")
port = gr.Textbox(value='5432', label="Port")
myDB = gr.Textbox(value='sample_db', label="mydatabase")
upload_status = gr.Textbox(value="Database not connected yet", label="Connect Status")
submit_SQL_btn = gr.Button("Submit postgres details")
submit_SQL_btn.click(fn=create_query_engine, inputs = [file, user, password, host, port, myDB], outputs=[SQLidx, sql_engine, upload_status])
robot = gr.Image(value=robot_filepath, type='pil', show_label=False, show_download_button=False, container=False, width=125, height=125, elem_classes='column_el')
with gr.Column(scale=3, elem_classes='column'):
df = gr.Dataframe()
chatbot = gr.Chatbot(elem_classes='column_el')
msg = gr.Textbox(show_label=False, elem_classes='column_el')
with gr.Accordion("Executed SQL Query"):
sql_statement = gr.Textbox(label="", lines=5)
with gr.Tab("Chat History"):
history = gr.HTML()
msg.submit(respond, [msg, chatbot, SQLidx, sql_engine], [msg, chatbot, history, df, sql_statement])
demo.launch() |