app.py

import gradio as gr
from huggingface_hub import InferenceClient

from query_data import query_data
from create_database import split_text
import os
import shutil 


import logging

logging.basicConfig(filename='myapp.log',format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
logger = logging.getLogger(__name__)

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""


CHROMA_PATH = "chroma"
DATA_PATH = "./data"


accesstoken = os.environ['HF_TOKEN']
checkpoint = "HuggingFaceH4/zephyr-7b-beta"
client = InferenceClient(checkpoint,token = accesstoken)

def upload_file(file):
    if not os.path.exists(DATA_PATH):
        os.mkdir(DATA_PATH)

    shutil.copy(file,DATA_PATH)
    gr.Info("File uploading")


logger.info("### Inference client: "+checkpoint)



def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    logger.info(messages)
    response = query_data(message)
    yield response


"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
with gr.Blocks() as demo: 

    upload_button = gr.UploadButton("Click the button to upload")
    upload_button.upload(upload_file,upload_button)

    gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot that helps searching knowledge into scientific articles.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        )
                ],
)


if __name__ == "__main__":
    demo.launch()