app.py

import streamlit as st

from PIL import Image
from tool_loader import ToolLoader
from app_user_desc import app_user_desc
from app_dev_desc import app_dev_desc
from logger import log_response
from logger import log_enabled
from app_chat import app_chat
import numpy as np
import re,sys,unicodedata

from app_agent_config import AgentConfig 

st.set_page_config(
    page_title="Custom Transformers can realy do anything...",
    page_icon="👋",
)
# Create an instance of AgentConfig
agent_config = AgentConfig()


import streamlit as st
import logging

# Set up the logger
transformers_logger = logging.getLogger("transformers.file_utils")

# Load the logs from the Transformers library
logs = transformers_logger.get_logs()

# Create a Streamlit app 

# Add a button to trigger the modal
st.button("Open App User Desc Modal")

# Define a function to display the modal
def display_modal():
    # Display the logs in a modal
    st.write(logs)

# Add the modal to the app
st.add_modal(display_modal)


#######

import pandas as pd
from io import StringIO
with st.sidebar:

    st.header("Set Tools and Option. ")

    with st.expander("Configure the agent and activate tools"):

            agent_config.configure()

    with st.expander("Set Content and Context"):

            agent_config.content_and_context()
         
# Create a page with tabs
tabs = st.tabs(["Chat","User Description"])

with tabs[0]: 
    st.title("Hugging Face Agent and Tools")

## LB https://huggingface.co/spaces/qiantong-xu/toolbench-leaderboard

    st.markdown("Welcome to the Hugging Face Agent and Tools app! This app allows you to interact with various tools using the Hugging Face Inference API.  CustomTransformers can do anything \n🤪🤗😄🤗🤪.")

    #st.markdown("Start to chat. e.g. Generate an image of a boat. This will make the agent use the tool text2image to generate an image. Set content, context, Inference URL , tools and logging in the sidebar.")
 
with tabs[1]:
    app_user_desc()
       
app_chat(agent_config)