app.py

import os
from dotenv import load_dotenv
load_dotenv()

# Hugging Face API Setup
hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
pinecone_api_key = os.getenv("PINECONE_API_KEY")
tavily_api_key = os.getenv("TAVILY_API_KEY")

import streamlit as st
from core import graph

st.title("💬 Hugging Face Chatbot")
prompt = st.text_input("Enter your question here:")

if prompt:
    user_message = st.chat_message("human")
    user_message.write(prompt)
    
    with st.spinner("Generating response via Hugging Face..."):
        ai_message = st.chat_message("ai")
        # Hier wird die Anfrage an deinen Graph übergeben, 
        # der nun auf Hugging Face Modellen basieren sollte
        ai_reply = graph.invoke({"question": prompt})
        ai_message.write(ai_reply["generation"])

# Add a footer
st.markdown("---")
st.markdown("Powered by Hugging Face, LangChain and Streamlit")