app.py

import streamlit as st
import random
import time

# --- Mock AI for CV Generation ---
# In a real application, this function would call a generative AI model API
# (e.g., Google's Gemini API, OpenAI's GPT) to create the CV content.
def generate_cv(data):
    """
    Generates a CV in Markdown format based on user input data.
    This is a mock function that simulates a generative AI response.
    """
    st.info("Generating your CV... Please wait.")
    
    # Simulate an API call delay
    with st.spinner('Thinking...'):
        time.sleep(random.uniform(2, 5))

    cv_text = f"""
# {data['name']}

**Contact:** {data['contact']}

---

### Professional Summary

{data['summary']}

---

### Skills

{data['skills']}

---

### Work Experience

"""
    for exp in data['experience']:
        cv_text += f"""
**{exp['title']}** at *{exp['company']}* ({exp['dates']})
- {exp['description']}

"""

    cv_text += f"""
---

### Education

**{data['education']['degree']}** in {data['education']['field']}
{data['education']['school']} ({data['education']['year']})

"""
    return cv_text

# --- Streamlit UI ---
st.set_page_config(
    page_title="Generative CV Maker",
    layout="wide",
    initial_sidebar_state="expanded",
)

st.title("📄 AI-Powered CV Maker")
st.markdown("Enter your details and let our AI assistant generate a professional CV for you.")

# --- User Input Form (in sidebar) ---
st.sidebar.header("Your Information")
with st.sidebar.form("cv_form"):
    name = st.text_input("Full Name", "John Doe")
    contact = st.text_input("Contact Info", "john.doe@email.com | +1234567890")
    summary = st.text_area("Professional Summary", "A highly motivated and results-oriented professional with a strong background in...")

    st.subheader("Skills")
    skills = st.text_area("List your skills (comma-separated)", "Python, Data Analysis, Machine Learning, Streamlit, Git")

    st.subheader("Work Experience")
    num_experience = st.number_input("Number of experiences", min_value=1, max_value=5, value=1)
    experiences = []
    for i in range(num_experience):
        st.markdown(f"**Experience {i+1}**")
        exp_title = st.text_input(f"Job Title ({i+1})", "Data Scientist")
        exp_company = st.text_input(f"Company ({i+1})", "Tech Solutions Inc.")
        exp_dates = st.text_input(f"Dates ({i+1})", "Jan 2020 - Present")
        exp_description = st.text_area(f"Description ({i+1})", "• Performed data analysis using Python and Pandas.\n• Built and deployed machine learning models to solve business problems.")
        experiences.append({
            "title": exp_title,
            "company": exp_company,
            "dates": exp_dates,
            "description": exp_description,
        })

    st.subheader("Education")
    edu_degree = st.text_input("Degree", "Master of Science")
    edu_field = st.text_input("Field of Study", "Computer Science")
    edu_school = st.text_input("University/College", "State University")
    edu_year = st.text_input("Year of Graduation", "2019")
    education = {
        "degree": edu_degree,
        "field": edu_field,
        "school": edu_school,
        "year": edu_year,
    }

    # Every form must have a submit button.
    submitted = st.form_submit_button("Generate CV")

# --- Display Generated CV ---
if submitted:
    user_data = {
        "name": name,
        "contact": contact,
        "summary": summary,
        "skills": skills,
        "experience": experiences,
        "education": education,
    }
    
    cv_content = generate_cv(user_data)
    
    st.header("✨ Your AI-Generated CV")
    st.markdown("---")
    st.markdown(cv_content)
    
    st.download_button(
        label="Download CV",
        data=cv_content,
        file_name="my_generated_cv.md",
        mime="text/markdown",
    )