arabic-RAG / app.py
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import logging
from functools import partial
from pathlib import Path
from time import perf_counter
import gradio as gr
from jinja2 import Environment, FileSystemLoader
from transformers import AutoTokenizer
from backend.query_llm import check_endpoint_status, generate
from backend.semantic_search import retriever
proj_dir = Path(__file__).parent
# Setting up the logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Set up the template environment with the templates directory
env = Environment(loader=FileSystemLoader(proj_dir / 'templates'))
# Load the templates directly from the environment
template = env.get_template('template.j2')
template_html = env.get_template('template_html.j2')
# Initialize tokenizer
tokenizer = AutoTokenizer.from_pretrained('derek-thomas/jais-13b-chat-hf')
# Examples
examples = ['ู…ู† ูƒุงู† ุทุฑููŠ ู…ุนุฑูƒุฉ ุงูƒุชูŠูˆู… ุงู„ุจุญุฑูŠุฉุŸ',
'ู„ู… ุงู„ุณู…ุงุก ุฒุฑู‚ุงุกุŸ',
"ู…ู† ูุงุฒ ุจูƒุฃุณ ุงู„ุนุงู„ู… ู„ู„ุฑุฌุงู„ ููŠ ุนุงู… 2014ุŸ",]
def add_text(history, text):
history = [] if history is None else history
history = history + [(text, None)]
return history, gr.Textbox(value="", interactive=False)
def bot(history, hyde=False):
top_k = 5
query = history[-1][0]
logger.warning('Retrieving documents...')
# Retrieve documents relevant to query
document_start = perf_counter()
if hyde:
hyde_document = generate(f"Write a wikipedia article intro paragraph to answer this query: {query}").split('### Response: [|AI|]')[-1]
logger.warning(hyde_document)
documents = retriever(hyde_document, top_k=top_k)
else:
documents = retriever(query, top_k=top_k)
document_time = perf_counter() - document_start
logger.warning(f'Finished Retrieving documents in {round(document_time, 2)} seconds...')
# Function to count tokens
def count_tokens(text):
return len(tokenizer.encode(text))
# Create Prompt
prompt = template.render(documents=documents, query=query)
# Check if the prompt is too long
token_count = count_tokens(prompt)
while token_count > 2048:
# Shorten your documents here. This is just a placeholder for the logic you'd use.
documents.pop() # Remove the last document
prompt = template.render(documents=documents, query=query) # Re-render the prompt
token_count = count_tokens(prompt) # Re-count tokens
prompt_html = template_html.render(documents=documents, query=query)
history[-1][1] = ""
response = generate(prompt)
history[-1][1] = response.split('### Response: [|AI|]')[-1]
return history, prompt_html
with gr.Blocks() as demo:
endpoint_status = gr.Textbox(check_endpoint_status, label="Endpoint Status (send chat to wake up)", every=1)
with gr.Tab("Arabic-RAG"):
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
avatar_images=('https://aui.atlassian.com/aui/8.8/docs/images/avatar-person.svg',
'https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.svg'),
bubble_full_width=False,
show_copy_button=True,
show_share_button=True,
)
with gr.Row():
txt = gr.Textbox(
scale=3,
show_label=False,
placeholder="Enter text and press enter",
container=False,
)
txt_btn = gr.Button(value="Submit text", scale=1)
gr.Examples(examples, txt)
prompt_html = gr.HTML()
# Turn off interactivity while generating if you click
txt_msg = txt_btn.click(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, chatbot, [chatbot, prompt_html])
# Turn it back on
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
# Turn off interactivity while generating if you hit enter
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, chatbot, [chatbot, prompt_html])
# Turn it back on
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
with gr.Tab("Arabic-RAG + HyDE"):
hyde_chatbot = gr.Chatbot(
[],
elem_id="chatbot",
avatar_images=('https://aui.atlassian.com/aui/8.8/docs/images/avatar-person.svg',
'https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.svg'),
bubble_full_width=False,
show_copy_button=True,
show_share_button=True,
)
with gr.Row():
hyde_txt = gr.Textbox(
scale=3,
show_label=False,
placeholder="Enter text and press enter",
container=False,
)
hyde_txt_btn = gr.Button(value="Submit text", scale=1)
gr.Examples(examples, hyde_txt)
hyde_prompt_html = gr.HTML()
# Turn off interactivity while generating if you click
hyde_txt_msg = hyde_txt_btn.click(add_text, [hyde_chatbot, hyde_txt], [hyde_chatbot, hyde_txt],
queue=False).then(
partial(bot, hyde=True), [hyde_chatbot], [hyde_chatbot, hyde_prompt_html])
# Turn it back on
hyde_txt_msg.then(lambda: gr.Textbox(interactive=True), None, [hyde_txt], queue=False)
# Turn off interactivity while generating if you hit enter
hyde_txt_msg = hyde_txt.submit(add_text, [hyde_chatbot, hyde_txt], [hyde_chatbot, hyde_txt], queue=False).then(
partial(bot, hyde=True), [hyde_chatbot], [hyde_chatbot, hyde_prompt_html])
# Turn it back on
hyde_txt_msg.then(lambda: gr.Textbox(interactive=True), None, [hyde_txt], queue=False)
# Examples
demo.queue()
demo.launch(debug=True)