import streamlit as st
from huggingface_hub import InferenceApi
import os
import requests
api_token = os.getenv('HF_API_TOKEN')
API_URL = "https://api-inference.huggingface.co/models/sadiji/acadgpt"
headers = {"Authorization": "Bearer "+os.getenv('HF_API_TOKEN')}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()
st.title("AcademiaGPT")

# Initialize session state to store chat history
if 'history' not in st.session_state:
    st.session_state.history = []

# User input
user_input = st.text_input("You: ", "")

if user_input:
    # Add user message to chat history
    st.session_state.history.append({"role": "user", "content": user_input})

    # Generate a response from the model
    output =query({
    "inputs": user_input,
    "parameters": {
        "max_length": 100,  # Increase this value to generate longer responses
        "temperature": 0.7,  # Optional: Adjust for more randomness in the output
        "top_p": 0.9,  # Optional: Adjust for nucleus sampling
        "top_k": 30  # Optional: Adjust for top-k sampling
    }
})

    # Extract the generated text
    try:
        bot_response = output[0]
    except Exception:
        bot_response = str(Exception)
    # Add bot response to chat history
    st.session_state.history.append({"role": "bot", "content": bot_response})

# Display chat history
for message in st.session_state.history:
    if message["role"] == "user":
        st.write(f"You: {message['content']}")
    else:
        st.write(f"Bot: {message['content']}")