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import os
import streamlit as st
from huggingface_hub import InferenceClient
from dotenv import load_dotenv
# Load .env (if you’re using one)
load_dotenv()
# Instantiate once
client = InferenceClient(
provider="auto",
api_key=os.environ["HUGGINGFACEHUB_API_TOKEN"]
)
# Page config
st.set_page_config(page_title="Educational Chatbot", layout="wide")
st.title("🎓 Educational Chatbot")
# Initialize history
if "history" not in st.session_state:
st.session_state.history = []
# Render existing messages
for sender, message in st.session_state.history:
if sender == "You":
st.chat_message("user").write(message)
else:
st.chat_message("assistant").write(message)
# Input box
user_input = st.chat_input("Ask me anything…")
if user_input:
# Display user message immediately
st.chat_message("user").write(user_input)
st.session_state.history.append(("You", user_input))
# Bot placeholder
placeholder = st.chat_message("assistant")
placeholder.write("⏳ Thinking...")
try:
# Call HF Inference API
completion = client.chat.completions.create(
model="deepseek-ai/DeepSeek-R1",
messages=[{"role": "user", "content": user_input}],
)
reply = completion.choices[0].message["content"]
except Exception as e:
reply = f"❌ API Error: {e}"
# Update placeholder with real response
placeholder.write(reply)
st.session_state.history.append(("Bot", reply))
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