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""" | |
Credit to Derek Thomas, derek@huggingface.co | |
""" | |
import os | |
import logging | |
from pathlib import Path | |
from time import perf_counter | |
import gradio as gr | |
from jinja2 import Environment, FileSystemLoader | |
from backend.query_llm import generate_hf, generate_openai | |
from backend.semantic_search import retrieve, rerank | |
TOP_N = int(os.getenv("TOP_N", 12)) | |
TOP_K = int(os.getenv("TOP_K", 4)) | |
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') | |
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, api_kind): | |
query = history[-1][0] | |
if not query: | |
raise gr.Warning("Please submit a non-empty string as a prompt") | |
logger.info('Retrieving documents...') | |
# Retrieve documents relevant to query | |
document_start = perf_counter() | |
documents = retrieve(query, TOP_N) | |
document_time = perf_counter() - document_start | |
logger.info(f'Finished Retrieving documents in {round(document_time, 2)} seconds...') | |
logger.info('Reranking documents...') | |
# Retrieve documents relevant to query | |
document_start = perf_counter() | |
documents = rerank(query, documents, TOP_K) | |
document_time = perf_counter() - document_start | |
logger.info(f'Finished Reranking documents in {round(document_time, 2)} seconds...') | |
# Create Prompt | |
prompt = template.render(documents=documents, query=query) | |
prompt_html = template_html.render(documents=documents, query=query) | |
if api_kind == "HuggingFace": | |
generate_fn = generate_hf | |
elif api_kind == "OpenAI": | |
generate_fn = generate_openai | |
else: | |
raise gr.Error(f"API {api_kind} is not supported") | |
history[-1][1] = "" | |
for character in generate_fn(prompt, history[:-1]): | |
history[-1][1] = character | |
yield history, prompt_html | |
with gr.Blocks() as demo: | |
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) | |
api_kind = gr.Radio(choices=["HuggingFace", "OpenAI"], value="HuggingFace") | |
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, api_kind], [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, api_kind], [chatbot, prompt_html]) | |
# Turn it back on | |
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False) | |
demo.queue() | |
demo.launch(debug=True) | |