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import streamlit as st | |
from assistant import chat_with_hf_bot | |
from resume_parser import extract_text_from_pdf | |
from skill_matcher import match_skills | |
from tracker import log_question | |
from database import init_db, save_chat | |
st.set_page_config(page_title="AI Career Coach", layout="wide") | |
init_db() | |
st.title("π AI Career Coach") | |
st.subheader("Chatbot + Resume Analysis + Weekly Guidance") | |
tab1, tab2 = st.tabs(["π¬ Chatbot", "π Resume Matcher"]) | |
with tab1: | |
user_input = st.text_input("Ask career-related questions:") | |
if user_input: | |
response = chat_with_hf_bot(user_input) | |
save_chat(user_input, response) | |
log_question(user_input) | |
st.success(response) | |
with tab2: | |
uploaded_file = st.file_uploader("Upload your Resume (PDF only)", type="pdf") | |
if uploaded_file: | |
resume_text = extract_text_from_pdf(uploaded_file) | |
st.markdown("**Extracted Skills from Resume:**") | |
st.write(resume_text) | |
matched_roles = match_skills(resume_text) | |
st.markdown("**Suggested Roles based on Resume:**") | |
for role in matched_roles: | |
st.write(f"β {role}") | |