import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI  
from langchain.tools import Tool
from langchain_community.tools.google_search import GoogleSearchResults
import json

# Get API key for Gemini
GEMINI_API_KEY = userdata.get("gemini_api")

# Configure LangChain LLM with Gemini 2.0
llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-exp", google_api_key=os.getenv("gemini_api"))

# Google Search Tool (does not require API key)
google_search = GoogleSearchResults()
search_tool = Tool(
    name="Google Search",
    func=google_search.run,
    description="Search the web for information.",
)

def azure_cert_bot(cert_name):
    query = f"Microsoft Azure {cert_name} certification curriculum site:microsoft.com"
    
    # Perform Google Search
    search_results = search_tool.run(query)
    
    # Generate Q&A using Gemini
    prompt = (
        f"Based on the following curriculum details, generate key questions and answers in markdown format for the {cert_name} certification exam:\n\n{search_results}"
    )
    response = llm.invoke(prompt)
    
    try:
        response_text = response.get("content", "No response generated.") if isinstance(response, dict) else response
    except Exception as e:
        response_text = f"Error processing response: {str(e)}"
    
    return search_results, response_text

# Streamlit UI Enhancements
st.set_page_config(page_title="Azure Certification Prep Assistant", layout="wide")

# Custom Styling
st.markdown("""
    <style>
    body {
        font-family: 'Arial', sans-serif;
    }
    .stApp {
        background-color: #f5f7fa;
    }
    .title {
        text-align: center;
        color: #1f77b4;
        font-size: 36px;
        font-weight: bold;
    }
    .subheader {
        color: #ff5733;
        font-size: 24px;
        font-weight: bold;
    }
    .markdown-text-container {
        background-color: white;
        padding: 15px;
        border-radius: 10px;
        box-shadow: 2px 2px 10px rgba(0,0,0,0.1);
    }
    </style>
""", unsafe_allow_html=True)

st.markdown("<div class='title'>Azure Certification Prep Assistant</div>", unsafe_allow_html=True)

cert_name = st.text_input("Enter Azure Certification Name (e.g., AZ-900)", "")
if st.button("Get Certification Details"):
    if cert_name:
        links, qa_content = azure_cert_bot(cert_name)
        
        st.markdown("<div class='subheader'>Certification Links & Curriculum</div>", unsafe_allow_html=True)
        st.markdown(f"<div class='markdown-text-container'>{links}</div>", unsafe_allow_html=True)
        
        st.markdown("<div class='subheader'>Exam Questions & Answers</div>", unsafe_allow_html=True)
        st.markdown(f"<div class='markdown-text-container'>{qa_content}</div>", unsafe_allow_html=True)
    else:
        st.warning("Please enter a certification name.")