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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
import logging
from app_agent_config import AgentConfig
# Create an instance of AgentConfig ## holds all data and settings
agent_config = AgentConfig()
st.set_page_config(
page_title="Custom Transformers can realy do anything...",
page_icon="👋",
)
#####
def on_close():
print("The modal was closed!")
def open_modal():
print("Todo")
# st.modal("User Guide", "app_user_desc()")
st.button("User Description", open_modal())
# Define a callback function that will be called when the button is clicked
#def open_modal():
# st.modal("User Guide", app_user_desc())
# Create a button that opens the 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) |