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"""
Credit to Derek Thomas, [email protected]
"""
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
from dotenv import load_dotenv
load_dotenv()
TOP_K = int(os.getenv("TOP_K", 4))
HF_TOKEN = os.getenv("HF_TOKEN")
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):
logger.info(f'Adding text: {text}')
history = [] if history is None else history
history = history + [(text, None)]
logger.info(f'Updated history: {history}')
return history, gr.Textbox(value="", interactive=False)
def bot(history, api_kind):
logger.info(f'Bot function called with history: {history} and api_kind: {api_kind}')
query = history[-1][0]
logger.info(f'Query: {query}')
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_K)
document_time = perf_counter() - document_start
logger.info(f'Finished Retrieving 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)
logger.info(f'Prompt created: {prompt}')
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(
fn=add_text,
inputs=[chatbot, txt],
outputs=[chatbot, txt]
).then(
fn=bot,
inputs=[chatbot, api_kind],
outputs=[chatbot, prompt_html]
)
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(
fn=add_text,
inputs=[chatbot, txt],
outputs=[chatbot, txt]
).then(
fn=bot,
inputs=[chatbot, api_kind],
outputs=[chatbot, prompt_html]
)
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
demo.queue()
demo.launch(debug=True) |