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import gradio as gr
import pandas as pd
import numpy as np
import os
import time
import re
import json
from auditqa.sample_questions import QUESTIONS
from auditqa.engine.prompts import audience_prompts
from auditqa.reports import POSSIBLE_REPORTS, files
from auditqa.doc_process import process_pdf
from langchain_core.messages import (
HumanMessage,
SystemMessage,
)
from langchain_huggingface import ChatHuggingFace
from langchain_core.output_parsers import StrOutputParser
from langchain_huggingface import HuggingFaceEndpoint
from dotenv import load_dotenv
load_dotenv()
HF_token = os.environ["HF_TOKEN"]
#process_pdf()
# --------------------------------------------------------------------
# Gradio
# --------------------------------------------------------------------
# Set up Gradio Theme
theme = gr.themes.Base(
primary_hue="blue",
secondary_hue="red",
font=[gr.themes.GoogleFont("Poppins"), "ui-sans-serif", "system-ui", "sans-serif"],
text_size = gr.themes.utils.sizes.text_sm,
)
init_prompt = """
Hello, I am Audit Q&A, a conversational assistant designed to help you understand audit Reports. I will answer your questions by using **Audit reports publishsed by Auditor General Office**.
💡 How to use (tabs on right)
- **Reports**: You can choose to address your question to either specific report or a collection of report like District or Ministry focused reports. \
If you dont select any then the Consolidated report is relied upon to answer your question.
- **Examples**: We have curated some example questions,select a particular question from category of questions.
- **Sources**: This tab will display the relied upon paragraphs from the report, to help you in assessing or fact checking if the answer provided by Audit Q&A assitant is correct or not.
⚠️ For limitations of the tool please check **Disclaimer** tab.
"""
with gr.Blocks(title="Audit Q&A", css= "style.css", theme=theme,elem_id = "main-component") as demo:
# user_id_state = gr.State([user_id])
with gr.Tab("AuditQ&A"):
with gr.Row(elem_id="chatbot-row"):
with gr.Column(scale=2):
# state = gr.State([system_template])
chatbot = gr.Chatbot(
value=[(None,init_prompt)],
show_copy_button=True,show_label = False,elem_id="chatbot",layout = "panel",
avatar_images = (None,"data-collection.png"),
)#,avatar_images = ("assets/logo4.png",None))
# bot.like(vote,None,None)
with gr.Row(elem_id = "input-message"):
textbox=gr.Textbox(placeholder="Ask me anything here!",show_label=False,scale=7,lines = 1,interactive = True,elem_id="input-textbox")
demo.queue()
demo.launch() |