Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
File size: 8,510 Bytes
2e537f7 eac3e5b 3248077 c39d2dc 4a27127 d5a9071 6fb73c4 d5a9071 1075df3 d5a9071 e461efe 6216345 e461efe d5a9071 e461efe 2e537f7 a7b80ba 2e537f7 d26ce45 2e537f7 22666cd 2e537f7 22666cd 2e537f7 4739ff2 2e537f7 4739ff2 2e537f7 |
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 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 |
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.reports import POSSIBLE_REPORTS
from auditqa.engine.prompts import audience_prompts
async def chat(query,history,audience,sources,reports):
"""taking a query and a message history, use a pipeline (reformulation, retriever, answering) to yield a tuple of:
(messages in gradio format, messages in langchain format, source documents)"""
print(f">> NEW QUESTION : {query}")
print(f"history:{history}")
print(f"audience:{audience}")
print(f"sources:{sources}")
print(f"reports:{reports}")
if audience == "Children":
audience_prompt = audience_prompts["children"]
elif audience == "General public":
audience_prompt = audience_prompts["general"]
elif audience == "Experts":
audience_prompt = audience_prompts["experts"]
else:
audience_prompt = audience_prompts["experts"]
# Prepare default values
if len(sources) == 0:
sources = ["IPCC"]
if len(reports) == 0:
reports = []
history = [tuple(x) for x in history]
docs_html = ""
output_query = ""
output_language = "ENG"
yield history,docs_html,output_query,output_language
# --------------------------------------------------------------------
# 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"],
)
init_prompt = """
Hello, I am Audit Q&A, a conversational assistant designed to help you understand audit Reports. I will answer your questions by **crawling through the Audit reports publishsed by Auditor General Office**.
❓ How to use
- **Language**: You can ask me your questions in any language.
- **Audience**: You can specify your audience (children, general public, experts) to get a more adapted answer.
- **Sources**: You can choose to search in the Annual or District or Department focused reports, or all.
⚠️ Limitations
*Please note that the AI is not perfect and may sometimes give irrelevant answers. If you are not satisfied with the answer, please ask a more specific question or report your feedback to help us improve the system.*
What do you want to learn ?
"""
# Setting Tabs
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,"https://i.ibb.co/YNyd5W2/logo4.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")
# submit = gr.Button("",elem_id = "submit-button",scale = 1,interactive = True,icon = "https://static-00.iconduck.com/assets.00/settings-icon-2048x2046-cw28eevx.png")
with gr.Column(scale=1, variant="panel",elem_id = "right-panel"):
with gr.Tabs() as tabs:
with gr.TabItem("Examples",elem_id = "tab-examples",id = 0):
examples_hidden = gr.Textbox(visible = False)
first_key = list(QUESTIONS.keys())[0]
dropdown_samples = gr.Dropdown(QUESTIONS.keys(),value = first_key,interactive = True,show_label = True,label = "Select a category of sample questions",elem_id = "dropdown-samples")
samples = []
for i,key in enumerate(QUESTIONS.keys()):
examples_visible = True if i == 0 else False
with gr.Row(visible = examples_visible) as group_examples:
examples_questions = gr.Examples(
QUESTIONS[key],
[examples_hidden],
examples_per_page=8,
run_on_click=False,
elem_id=f"examples{i}",
api_name=f"examples{i}",
# label = "Click on the example question or enter your own",
# cache_examples=True,
)
samples.append(group_examples)
with gr.Tab("Sources",elem_id = "tab-citations",id = 1):
sources_textbox = gr.HTML(show_label=False, elem_id="sources-textbox")
docs_textbox = gr.State("")
# with Modal(visible = False) as config_modal:
with gr.Tab("Configuration",elem_id = "tab-config",id = 2):
gr.Markdown("Reminder: You can talk in any language, Audit Q&A is multi-lingual!")
dropdown_sources = gr.CheckboxGroup(
["ABC", "XYZ"],
label="Select source",
value=["ABC"],
interactive=True,
)
dropdown_reports = gr.Dropdown(
POSSIBLE_REPORTS,
label="Or select specific reports",
multiselect=True,
value=None,
interactive=True,
)
dropdown_audience = gr.Dropdown(
["Children","General public","Experts"],
label="Select audience",
value="Experts",
interactive=True,
)
output_query = gr.Textbox(label="Query used for retrieval",show_label = True,elem_id = "reformulated-query",lines = 2,interactive = False)
output_language = gr.Textbox(label="Language",show_label = True,elem_id = "language",lines = 1,interactive = False)
with gr.Tab("About",elem_classes = "max-height other-tabs"):
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("See more info at [https://www.oag.go.ug/](https://www.oag.go.ug/welcome)")
def start_chat(query,history):
history = history + [(query,None)]
history = [tuple(x) for x in history]
return (gr.update(interactive = False),gr.update(selected=1),history)
def finish_chat():
return (gr.update(interactive = True,value = ""))
(textbox
.submit(start_chat, [textbox,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_textbox")
.then(chat, [textbox,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language],concurrency_limit = 8,api_name = "chat_textbox")
.then(finish_chat, None, [textbox],api_name = "finish_chat_textbox")
)
(examples_hidden
.change(start_chat, [examples_hidden,chatbot], [textbox,tabs,chatbot],queue = False,api_name = "start_chat_examples")
.then(chat, [examples_hidden,chatbot,dropdown_audience, dropdown_sources,dropdown_reports], [chatbot,sources_textbox,output_query,output_language],concurrency_limit = 8,api_name = "chat_examples")
.then(finish_chat, None, [textbox],api_name = "finish_chat_examples")
)
def change_sample_questions(key):
index = list(QUESTIONS.keys()).index(key)
visible_bools = [False] * len(samples)
visible_bools[index] = True
return [gr.update(visible=visible_bools[i]) for i in range(len(samples))]
dropdown_samples.change(change_sample_questions,dropdown_samples,samples)
demo.queue()
demo.launch() |