Update app.py
Browse files
app.py
CHANGED
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@@ -1,7 +1,7 @@
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import streamlit as st
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import openai
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from langchain_google_genai import ChatGoogleGenerativeAI
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import
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from datetime import datetime, timedelta
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import time
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@@ -10,7 +10,7 @@ GOOGLE_API_KEY = st.secrets["GOOGLE_API_KEY"]
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OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
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GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
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# Initialize
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openai.api_key = OPENAI_API_KEY
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# In-memory storage for progress tracking
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@@ -44,7 +44,7 @@ def get_llm(model_choice):
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elif model_choice == "OpenAI":
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return None
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elif model_choice == "Groq":
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return GROQ_API_KEY
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else:
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raise ValueError("Unsupported model choice.")
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@@ -65,9 +65,9 @@ def generate_questions(model_choice, role, question_type, num_questions, difficu
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response = llm.invoke(prompt)
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return response.content.split("\n")
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elif model_choice == "Groq":
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response =
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return response.
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else:
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raise ValueError("Unsupported model choice.")
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@@ -85,9 +85,9 @@ def provide_feedback(model_choice, answer):
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response = llm.invoke(prompt)
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return response.content
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elif model_choice == "Groq":
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response =
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return response.
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else:
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raise ValueError("Unsupported model choice.")
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@@ -105,9 +105,9 @@ def get_tips(model_choice, role):
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response = llm.invoke(prompt)
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return response.content
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elif model_choice == "Groq":
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response =
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return response.
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else:
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raise ValueError("Unsupported model choice.")
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@@ -185,7 +185,6 @@ def track_progress():
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<p><strong>Mock Interviews Taken:</strong> {progress_data['mock_interviews_taken']}</p>
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<p><strong>Feedback Provided:</strong> {progress_data['feedback_provided']}</p>
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<p><strong>Tips Retrieved:</strong> {progress_data['tips_retrieved']}</p>
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<p><strong>Resources Used:</strong> {progress_data['resources_used']}</p>
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</div>
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""", unsafe_allow_html=True)
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@@ -204,41 +203,41 @@ def connect_resources():
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# Form to connect with career coaches or mentors
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with st.form("contact_form"):
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st.write("For personalized assistance, please fill out
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name = st.text_input("
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email = st.text_input("
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message = st.text_area("Message")
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submit_button = st.form_submit_button("
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if submit_button:
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if name
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st.
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progress_data["resources_used"] += 1
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else:
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st.
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return f"""
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<div class="output-container" style="border-left: 5px solid {color};">
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<h3>{title}</h3>
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</div>
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"""
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#
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st.
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<style>
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.stButton>button {
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color: white;
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border: none;
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padding: 10px 20px;
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text-align: center;
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text-decoration: none;
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display: inline-block;
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font-size: 16px;
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border-radius: 8px;
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cursor: pointer;
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}
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.stButton>button:hover {
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background-color: #45a049;
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@@ -251,7 +250,7 @@ st.markdown("""
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border: 1px solid #d0d0d0;
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}
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.sidebar {
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background-color: #ffffff;
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padding: 1em;
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}
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.footer {
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@@ -264,11 +263,10 @@ st.markdown("""
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width: 100%;
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border-top: 2px solid #ffffff;
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}
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.progress-container p {
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margin: 5px 0;
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}
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</style>
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""",
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# Show welcome message with an icon for 3-4 seconds
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welcome_message = st.empty()
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@@ -285,10 +283,10 @@ with welcome_message.container():
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<i class="fa fa-smile-o" aria-hidden="true" style="font-size: 40px;"></i> Welcome to TechPrep!
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</div>
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""", unsafe_allow_html=True)
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time.sleep(4)
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welcome_message.empty()
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# Initialize session state
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if 'questions' not in st.session_state:
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st.session_state.questions = []
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if 'answers' not in st.session_state:
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@@ -302,7 +300,7 @@ if 'show_results' not in st.session_state:
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# Sidebar Navigation
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st.sidebar.title("TechPrep Navigation")
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nav_option = st.sidebar.radio("Choose an option:",
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["Generate Questions", "Mock Interview", "Track Progress", "Connect with Resources"])
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# Handling page navigation
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@@ -313,7 +311,7 @@ if nav_option == "Generate Questions":
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role = st.selectbox("Role", ROLE_OPTIONS)
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question_type = st.selectbox("Question Type:", ["Behavioral", "Technical", "Situational", "Case Study", "Problem Solving"])
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num_questions = st.number_input("Number of Questions:", min_value=1, max_value=20, value=5)
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difficulty = st.selectbox("Difficulty Level:", ["
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if st.button("Generate Questions", key="generate_questions"):
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with st.spinner("Generating questions..."):
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import streamlit as st
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import openai
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain_groq import ChatGroqGenerativeAI # Assume this is the correct import for Groq
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from datetime import datetime, timedelta
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import time
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OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
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GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
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# Initialize APIs
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openai.api_key = OPENAI_API_KEY
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# In-memory storage for progress tracking
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elif model_choice == "OpenAI":
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return None
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elif model_choice == "Groq":
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return ChatGroqGenerativeAI(api_key=GROQ_API_KEY)
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else:
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raise ValueError("Unsupported model choice.")
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response = llm.invoke(prompt)
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return response.content.split("\n")
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elif model_choice == "Groq":
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llm = get_llm(model_choice)
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response = llm.invoke(prompt)
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return response.content.split("\n")
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else:
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raise ValueError("Unsupported model choice.")
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response = llm.invoke(prompt)
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return response.content
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elif model_choice == "Groq":
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llm = get_llm(model_choice)
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response = llm.invoke(prompt)
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return response.content
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else:
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raise ValueError("Unsupported model choice.")
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response = llm.invoke(prompt)
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return response.content
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elif model_choice == "Groq":
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llm = get_llm(model_choice)
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response = llm.invoke(prompt)
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return response.content
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else:
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raise ValueError("Unsupported model choice.")
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<p><strong>Mock Interviews Taken:</strong> {progress_data['mock_interviews_taken']}</p>
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<p><strong>Feedback Provided:</strong> {progress_data['feedback_provided']}</p>
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<p><strong>Tips Retrieved:</strong> {progress_data['tips_retrieved']}</p>
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</div>
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""", unsafe_allow_html=True)
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# Form to connect with career coaches or mentors
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with st.form("contact_form"):
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st.write("For personalized assistance, please fill out this form:")
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name = st.text_input("Name")
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email = st.text_input("Email")
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message = st.text_area("Message")
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submit_button = st.form_submit_button("Submit")
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if submit_button:
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if not name or not email or not message:
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st.error("Please fill out all fields.")
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else:
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st.success("Thank you for contacting us! We will get back to you soon.")
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progress_data["resources_used"] += 1
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def style_output(text, color):
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return f'<div class="output-container"><span style="color: {color}; font-weight: bold;">{text}</span></div>'
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# Streamlit app layout
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st.set_page_config(page_title="TechPrep", layout="wide")
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st.markdown(
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"""
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<style>
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body {
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background-color: #e0f7fa; /* Light cyan background color */
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font-family: Arial, sans-serif;
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}
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.stButton>button {
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width: 100%;
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height: 3em;
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font-size: 1.2em;
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color: white;
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background-color: #4CAF50;
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border: none;
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border-radius: 8px;
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cursor: pointer;
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transition: background-color 0.3s ease;
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}
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.stButton>button:hover {
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background-color: #45a049;
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border: 1px solid #d0d0d0;
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}
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.sidebar {
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background-color: #ffffff; /* Sidebar background color */
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padding: 1em;
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}
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.footer {
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width: 100%;
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border-top: 2px solid #ffffff;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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# Show welcome message with an icon for 3-4 seconds
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welcome_message = st.empty()
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<i class="fa fa-smile-o" aria-hidden="true" style="font-size: 40px;"></i> Welcome to TechPrep!
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</div>
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""", unsafe_allow_html=True)
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time.sleep(4) # Wait for 4 seconds
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welcome_message.empty() # Remove the welcome message
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# Initialize session state for questions, answers, and current index
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if 'questions' not in st.session_state:
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st.session_state.questions = []
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if 'answers' not in st.session_state:
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# Sidebar Navigation
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st.sidebar.title("TechPrep Navigation")
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nav_option = st.sidebar.radio("Choose an option:",
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["Generate Questions", "Mock Interview", "Track Progress", "Connect with Resources"])
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# Handling page navigation
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role = st.selectbox("Role", ROLE_OPTIONS)
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question_type = st.selectbox("Question Type:", ["Behavioral", "Technical", "Situational", "Case Study", "Problem Solving"])
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num_questions = st.number_input("Number of Questions:", min_value=1, max_value=20, value=5)
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difficulty = st.selectbox("Difficulty Level:", ["Basic", "Medium", "Complex"])
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if st.button("Generate Questions", key="generate_questions"):
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with st.spinner("Generating questions..."):
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