app.py

import streamlit as st
from langchain_google_genai import ChatGoogleGenerativeAI
from datetime import datetime

# Custom CSS for styling
st.markdown("""
    <style>
    /* Style the title */
    .stApp {
        background-color: #8182ae ;
        font-family: 'Arial', sans-serif;
    }
    .stTitle {
        color: #2c3e50;
        font-size: 32px;
        font-weight: bold;
        text-align: center;
        margin-bottom: 20px;
    }
    /* Style the buttons and forms */
    .stButton > button {
        background-color: #d91515 ;
        color: white;
        padding: 10px 20px;
        border-radius: 5px;
        border: none;
        font-weight: bold;
    }
    .stForm {
        background-color: #ecf0f1;
    }
    /* Style the sidebar */
    .stSidebar > div {
        background-color: #8182ae;
        padding: 15px;
        border-radius: 10px;
    }
    .stSidebar > div > h1 {
        color: #2c3e50;
    }
    </style>
    """, unsafe_allow_html=True)

st.markdown("<h1 class='stTitle'>Prepare Smarter, Ace the Interview!</h1>", unsafe_allow_html=True)

# Function to generate interview questions
def generate_questions(role, topic, difficulty, num_questions):
    prompt = (
        f"Generate {num_questions} {difficulty} interview questions for a {role} role "
        f"focused on {topic}."
    )
    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
    answers = llm.invoke(prompt)
    return answers.content if answers else "No questions generated."

# Function to analyze responses and give feedback
def analyze_responses(response):
    prompt = (
        f"Provide constructive feedback on the following interview response:\n\n{response}"
    )
    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
    feedback = llm.invoke(prompt)
    return feedback.content if feedback else "No feedback available."

# Function to provide general and specific interview tips
def provide_tips(role=None):
    prompt = "Share general interview tips."
    if role:
        prompt += f" Provide specific tips for a {role} role."
    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
    tips = llm.invoke(prompt)
    return tips.content if tips else "No tips available."

# Interface for generating questions
with st.form('question_form', clear_on_submit=True):
    st.markdown("<div class='stForm'>", unsafe_allow_html=True)
    role = st.selectbox('Select Role', ['Software Developer', 'Data Analyst', 'Marketing Manager'])
    topic = st.selectbox('Select Topic', ['Behavioral', 'Technical', 'Situational'])
    difficulty = st.selectbox('Select Difficulty Level', ['Easy', 'Medium', 'Hard'])
    num_questions = st.slider('Number of Questions', 1, 10, 5)
    question_submitted = st.form_submit_button('Generate Questions')

    if question_submitted:
        questions = generate_questions(role, topic, difficulty, num_questions)
        st.info(questions)
    st.markdown("</div>", unsafe_allow_html=True)

# Interface for feedback on responses
with st.form('feedback_form', clear_on_submit=True):
    st.markdown("<div class='stForm'>", unsafe_allow_html=True)
    response = st.text_area('Type your interview response')
    feedback_submitted = st.form_submit_button('Get Feedback')

    if feedback_submitted and response:
        feedback = analyze_responses(response)
        st.info(feedback)
    st.markdown("</div>", unsafe_allow_html=True)

# Interface for interview tips
with st.form('tips_form', clear_on_submit=True):
    st.markdown("<div class='stForm'>", unsafe_allow_html=True)
    role_for_tips = st.selectbox('Select Role for Tips', ['', 'Software Developer', 'Data Analyst', 'Marketing Manager'])
    tips_submitted = st.form_submit_button('Get Tips')

    if tips_submitted:
        tips = provide_tips(role_for_tips if role_for_tips else None)
        st.info(tips)
    st.markdown("</div>", unsafe_allow_html=True)

# Sidebar for mock interview scheduling and resources
st.sidebar.header(" Book Your Interview Slot")
st.sidebar.write("Book a Practice Interview with the Bot")
mock_date = st.sidebar.date_input("Select Date", datetime.now())
mock_time = st.sidebar.time_input("Select Time", datetime.now().time())
st.sidebar.button("Schedule Interview", on_click=lambda: st.sidebar.write("Interview is Booked!"))

st.sidebar.header("Engagement Metrics and Resources")
st.sidebar.write("Track your progress over time and connect with resources.")