import streamlit as st
import requests
from transformers import pipeline

# Initialize the language model (Hugging Face's pre-trained model for text generation)
generator = pipeline('text-generation', model='gpt-2')  # You can choose any suitable language model

# Title and Description of the App
st.title("AI-powered Opportunity Finder for Youth")
st.write("Find scholarships, internships, competitions, and more based on your skills and interests using AI!")

# Collect user input
interests = st.text_input("Enter your interests (e.g., AI, web development, etc.)")
skills = st.text_input("Enter your skills (e.g., Python, Data Analysis, etc.)")
location = st.text_input("Enter your location")

# Button to trigger the AI recommendations
if st.button("Find Opportunities"):
    # Combine the input into a prompt for the language model
    prompt = f"Find scholarships, internships, competitions, and online courses for a person interested in {interests}, skilled in {skills}, and located in {location}. Provide recommendations with details like title, link, and description."
    
    # Use the language model to generate recommendations
    response = generator(prompt, max_length=150, num_return_sequences=1)
    
    # Parse and display the generated text
    recommendations = response[0]['generated_text']
    
    # Display the generated recommendations
    st.write("Recommended Opportunities based on your input:")
    st.write(recommendations)

    # Example to further integrate Groq API (if you need more personalized results)
    # You can replace the following code with an actual API request to Groq for more detailed results
    # Make sure to replace the placeholder with your Groq API endpoint and parameters
    try:
        api_response = requests.post("https://api.groq.com/recommendations", json={
            "interests": interests,
            "skills": skills,
            "location": location
        })

        if api_response.status_code == 200:
            api_recommendations = api_response.json()
            st.write("Groq API Recommendations:")
            for rec in api_recommendations:
                st.write(f"- {rec['title']}: {rec['link']}")
        else:
            st.write("Unable to fetch recommendations from Groq API.")

    except Exception as e:
        st.write(f"Error while fetching recommendations from Groq API: {e}")