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import logging
from pathlib import Path
import gradio as gr
import os
from jinja2 import Environment, FileSystemLoader
from src.chat import Chat
from src.rag import FaissDB, AICompletion, define_query
from src.prompts import *
chat_model = AICompletion()
chat = Chat(system_prompt=SYSTEM_PROMPT)
faiss_index = FaissDB(emb_model=os.environ["OPENAI_EMBEDDINGS_MODEL"])
faiss_index.load_index(os.environ["PATH_TO_INDEX"])
proj_dir = Path(__file__).parent
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
env = Environment(loader=FileSystemLoader(proj_dir / 'templates'))
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):
user_query = history[-1][0]
if not user_query:
raise gr.Warning("Please submit a non-empty string")
logger.info('Retrieving documents...')
retrieve_query = define_query(user_query, chat_model)
documents = faiss_index.similarity_search(retrieve_query) if retrieve_query else ''
user_prompt = USER_PROMPT(user_query, '\n'.join(documents))
prompt_html = template_html.render(documents=documents, query=retrieve_query if retrieve_query else 'No query')
stream = chat.stream(user_prompt)
history[-1][1] = ""
for character in stream:
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)
prompt_html = gr.HTML()
txt_msg = txt_btn.click(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, [chatbot], [chatbot, prompt_html])
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
txt_msg = txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
bot, [chatbot], [chatbot, prompt_html])
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [txt], queue=False)
demo.queue()
demo.launch(debug=True)
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