import os
import gradio as gr
from groq import Groq
from googletrans import Translator
import asyncio

# Function to get recommendations from Groq AI based on user input
def get_opportunities(user_interests, user_skills, user_location):
    # Fetch the API key from the environment variable
    api_key = "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"
    
    if not api_key:
        raise ValueError("API key is missing. Make sure to set the GROQ_API_KEY environment variable.")
    
    # Initialize the Groq client with the API key
    client = Groq(api_key=api_key)
    
    # Construct the query
    query = f"Based on the user's interests in {user_interests}, skills in {user_skills}, and location of {user_location}, find scholarships, internships, online courses, and career advice suitable for them."
    
    # Request to Groq API
    response = client.chat.completions.create(
        messages=[{"role": "user", "content": query}],
        model="llama-3.3-70b-versatile",
    )
    
    return response.choices[0].message.content

# Function to translate text into the selected language (async version)
async def translate_text(text, target_language):
    translator = Translator()
    translated = await translator.translate(text, dest=target_language)
    return translated.text

# Function to get chatbot response
def get_chatbot_response(user_message):
    # Fetch the API key from the environment variable
    api_key = "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"
    
    if not api_key:
        raise ValueError("API key is missing. Make sure to set the GROQ_API_KEY environment variable.")
    
    # Initialize the Groq client with the API key
    client = Groq(api_key=api_key)
    
    # Request to Groq API for chatbot response
    response = client.chat.completions.create(
        messages=[{"role": "user", "content": user_message}],
        model="llama-3.3-70b-versatile",
    )
    
    return response.choices[0].message.content

# Gradio interface
with gr.Blocks(css="""
    .gradio-container {
        background-color: #f0f0f5;
        color: #333;
        font-family: 'Roboto', sans-serif;
        padding: 20px;
        border-radius: 10px;
        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
    }
    .gradio-container .button {
        background-color: #007bff;
        color: white;
        padding: 12px;
        font-size: 16px;
        border-radius: 10px;
        border: none;
    }
    .gradio-container .button:hover {
        background-color: #0056b3;
    }
    .gradio-container .textbox {
        font-size: 16px;
        padding: 12px;
        border-radius: 10px;
        border: 1px solid #ccc;
    }
""") as demo:
    gr.Markdown("""
        <h1 style="text-align:center;">AI-Powered Opportunity Finder for Youth</h1>
        <p style="text-align:center;">Find scholarships, internships, online courses, and career advice based on your interests, skills, and location.</p>
    """)
    
    # Sidebar for input fields
    with gr.Column():
        gr.Markdown("### Provide your details to find opportunities")

        interests = gr.Textbox(label="Your Interests (e.g., AI, Robotics, Software Engineering):")
        skills = gr.Textbox(label="Your Skills (e.g., Python, Data Science, Web Development):")
        location = gr.Textbox(label="Your Location (e.g., Gujrat, Pakistan):")

        languages = gr.Dropdown(
            label="Select your preferred language:",
            choices=["English", "Spanish", "French", "German", "Italian", "Chinese", "Japanese", "Urdu"],
            value="English"
        )
        
        find_button = gr.Button("Find Opportunities")
    
    # Chatbot Section
    with gr.Column():
        gr.Markdown("### AI Chatbot")
        user_message = gr.Textbox(label="Ask anything to the chatbot:", lines=2)
        chatbot_output = gr.Textbox(label="Chatbot Response:", interactive=False)
    
    # Function to handle finding opportunities
    def find_opportunities_and_chat(interests, skills, location, language, user_message):
        # Fetch opportunities
        opportunities = get_opportunities(interests, skills, location)
        translated_opportunities = asyncio.run(translate_text(opportunities, language))
        
        # Get chatbot response
        chatbot_response = get_chatbot_response(user_message) if user_message else "Ask me anything!"
        
        return translated_opportunities, chatbot_response

    # Connect the button to the function
    find_button.click(
        find_opportunities_and_chat,
        inputs=[interests, skills, location, languages, user_message],
        outputs=[gr.Textbox(label="Recommended Opportunities"), chatbot_output]
    )

# Launch the Gradio app
if __name__ == "__main__":
    demo.launch()