import os
import gradio as gr
from together import Together

# Function to interact with the model and process responses
def chatbot_response(query):
    # Hugging Face API key setup (replace with your actual key)
    api_key = os.getenv("TOGETHER_API_KEY")
    if not api_key:
        return "Error: API key not found. Please configure your TOGETHER_API_KEY."
    
    client = Together(api_key=api_key)
    
    # Chat request to Hugging Face model
    response = client.chat.completions.create(
        model="NousResearch/Hermes-3-Llama-3.1-405B-Turbo",
        messages=[{"role": "user", "content": query}],
    )
    
    # Extract and return the response
    return response.choices[0].message.content

# Navigation and feature-specific responses
def website_navigation(query):
    lower_query = query.lower()

    if "mentorship" in lower_query:
        return "You can explore our mentorship programs here: [Mentorship Program](#)"
    elif "alumni events" in lower_query or "meetups" in lower_query:
        return "Check out upcoming alumni events: [Alumni Events](#)"
    elif "career guidance" in lower_query:
        return "For career guidance sessions, visit: [Career Guidance](#)"
    elif "academic support" in lower_query:
        return "Need academic support? Find resources here: [Academic Support](#)"
    elif "placement assistance" in lower_query:
        return "Our placement assistance services are available here: [Placement Assistance](#)"
    elif "forums" in lower_query or "discussions" in lower_query:
        return "Join discussions on our forum: [Discussion Forums](#)"
    else:
        # Fallback to AI-generated responses
        return chatbot_response(query)

# Gradio Interface
with gr.Blocks() as demo:
    gr.Markdown("<h1>Alumni-Student Interaction Platform Assistant</h1>")
    gr.Markdown("Ask me about mentorship, alumni events, career guidance, academic support, placement assistance, or anything related to our platform.")
    
    chatbot = gr.Chatbot()
    query_input = gr.Textbox(placeholder="Type your question here (e.g., 'How can I find career guidance?')")
    
    def respond(query, chat_history):
        # Get response from website navigation or AI
        response = website_navigation(query)
        chat_history.append((query, response))
        return chat_history, chat_history
    
    query_input.submit(respond, [query_input, chatbot], [chatbot, chatbot])

# Launch the app
demo.launch()