import streamlit as st
import os
from dotenv import load_dotenv
from langchain_community.llms import OpenAI
from langchain_google_genai import ChatGoogleGenerativeAI

# Load environment variables
load_dotenv()









def suggest_projects(skills, roles, topics, level, difficulty,model, domain, industry):
    prompt = f"""
    Based on the following information, suggest relevant projects:
    - Skills: {skills}
    - Roles: {roles}
    - Topics: {topics}
    - Level of Understanding: {level}
    - Difficulty: {difficulty}
    """
    if domain:
        prompt += f"\n- Domain: {domain}"
    if industry:
        prompt += f"\n- Industry: {industry}"

    prompt += "\n\nSuggested Projects:"

    if model == "Open AI":
        llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["OPENAI_API_KEY"])
        projects = llm(prompt)
        
        
    elif model == "Gemini":
        llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=st.secrets["GOOGLE_API_KEY"])
        projects = llm.invoke(prompt)
        projects = projects.content
    
    
    return projects

def app():
    st.title("Project Suggestions")





            
    if 'analysis' in st.session_state:
        analysis = st.session_state['analysis']
        st.header("Select AI:")
        model = st.radio("Model", [ "Gemini","Open AI",])
        st.write("Selected option:", model)
        st.write("Job Description Analysis:")
        st.text(analysis)
        
        # Parse the analysis (assuming it returns JSON-like structure)
        analysis_data = eval(analysis)  # Convert string to dictionary
        
        # Extract the details from analysis
        skills = analysis_data.get("Skills", "")
        roles = analysis_data.get("Roles", "")
        topics = analysis_data.get("Topics", "")
        level = analysis_data.get("Level of Understanding", "")
        difficulty = analysis_data.get("Difficulty", "")
        domain = analysis_data.get("domain", "")
        industry = analysis_data.get("industry", "")
        
        # Optional fields for domain and industry
        # domain = st.text_input("Optional: Domain")
        # industry = st.text_input("Optional: Industry")
        
        
        # Suggest projects based on analysis
        if st.button("Suggest Projects"):
            projects = suggest_projects(skills, roles, topics, level, difficulty,model, domain, industry)
            st.write("Suggested Projects:")
            st.text(projects)
            st.session_state['projects'] = projects.split('\n')
    else:
        st.error("Please go to the Job Description Analysis page first to analyze a job description.")