app.py

import gradio as gr
import requests
import os
import subprocess
import threading

# API credentials for job search
API_KEY = "c1b9b6be0amsh11316ef9a922bdbp1789f5jsn18a0023eef11"
API_HOST = "jsearch.p.rapidapi.com"

# Securely set Groq API key (for Career Counselor)
GROQ_API_KEY = "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"
os.environ["GROQ_API_KEY"] = GROQ_API_KEY

# Function to fetch job openings
def get_job_openings(job_title, location, location_type, employment_type, salary_min, salary_max):
    url = "https://jsearch.p.rapidapi.com/search"
    querystring = {
        "query": f"{job_title} in {location}",
        "page": "1",
        "num_pages": "1",
        "remote_jobs_only": "true" if location_type == "REMOTE" else "false",
        "employment_types": employment_type,
        "salary_min": salary_min,
        "salary_max": salary_max
    }
    headers = {
        "x-rapidapi-key": API_KEY,
        "x-rapidapi-host": API_HOST
    }
    response = requests.get(url, headers=headers, params=querystring)
    return response.json().get('data', []) if response.status_code == 200 else f"Error {response.status_code}: {response.text}"

# Function for job search UI
def search_jobs(job_title, location, location_type, employment_type, salary_min, salary_max):
    jobs = get_job_openings(job_title, location, location_type, employment_type, salary_min, salary_max)
    if isinstance(jobs, str):
        return jobs
    if not jobs:
        return "No job openings found. Please try different inputs."
    return "\n\n".join(
        f"{idx}. {job.get('job_title', 'No Title')}\n"
        f"Company: {job.get('employer_name', 'Unknown')}\n"
        f"Location: {job.get('job_city', 'Unknown')}, {job.get('job_country', '')}\n"
        f"Type: {job.get('job_employment_type', 'N/A')}\n"
        f"Salary: {job.get('job_salary_currency', '')} {job.get('job_salary_min', 'N/A')} - {job.get('job_salary_max', 'N/A')}\n"
        f"Posted On: {job.get('job_posted_at_datetime_utc', 'N/A')}\n"
        f"Deadline: {job.get('job_offer_expiration_datetime_utc', 'N/A')}\n"
        f"[View Job Posting]({job.get('job_apply_link', '#')})"
        for idx, job in enumerate(jobs, start=1)
    )

# Function to launch Career Counselor App in a separate thread
def launch_career_counselor():
    def run_streamlit():
        # Write the Streamlit app code to career_counselor.py
        with open("career_counselor.py", "w") as f:
            f.write("""
import os
import streamlit as st
from groq import Groq

GROQ_API_KEY = os.getenv("GROQ_API_KEY")
client = Groq(api_key=GROQ_API_KEY)

st.title("Career Counselor App")
st.write("Get career guidance based on your skills, interests, and experience.")

st.header("Tell us about yourself")
skills = st.text_area("List your skills (e.g., Python, teamwork, CAD):")
interests = st.text_area("What areas of interest do you have? (e.g., AI, design, civil engineering):")
experience = st.text_area("Describe your experience (if any):")

def suggest_careers_groq(skills, interests, experience):
    try:
        prompt = f"Suggest careers based on Skills: {skills}, Interests: {interests}, Experience: {experience}"
        chat_completion = client.chat.completions.create(
            messages=[{"role": "user", "content": prompt}],
            model="llama-3.3-70b-versatile",
            stream=False,
        )
        return chat_completion.choices[0].message.content
    except Exception as e:
        st.error(f"Error: {e}")
        return None

if st.button("Get Career Advice"):
    if not skills or not interests:
        st.error("Please provide skills and interests for better suggestions.")
    else:
        st.subheader("Career Recommendations")
        response = suggest_careers_groq(skills, interests, experience)
        st.write(response if response else "No recommendations available.")

st.markdown("---")
st.markdown("<p style='text-align: center;'>Designed by Career Expert</p>", unsafe_allow_html=True)
""")
        # Use a clean environment and launch via the Python module to avoid extra flags.
        env = os.environ.copy()
        subprocess.Popen(
            ["python", "-m", "streamlit", "run", "career_counselor.py"],
            stdout=subprocess.DEVNULL,
            stderr=subprocess.DEVNULL,
            env=env
        )
    threading.Thread(target=run_streamlit, daemon=True).start()

# Function to handle option selection
def main(option):
    if option == "Career Connect (Job Search)":
        return gr.update(visible=True), gr.update(visible=False), ""
    elif option == "Career Counselor App":
        launch_career_counselor()
        return gr.update(visible=False), gr.update(visible=True), "🚀 Career Counselor App is launching..."

# Gradio Interface
with gr.Blocks() as iface:
    gr.Markdown("# 🌟 Career Guidance & Job Search")
    gr.Markdown("Choose between job searching or AI-powered career guidance.")
    option = gr.Radio(["Career Connect (Job Search)", "Career Counselor App"], label="Select an Option")
    
    # Job search UI
    job_search_interface = gr.Interface(
        fn=search_jobs,
        inputs=[
            gr.Textbox(label="Enter Job Title", placeholder="e.g., Node.js Developer"),
            gr.Textbox(label="Enter Location", placeholder="e.g., New York"),
            gr.Radio(["ANY", "ON_SITE", "REMOTE", "HYBRID"], label="Location Type"),
            gr.CheckboxGroup(["FULLTIME", "PARTTIME", "INTERN", "CONTRACTOR"],
                             label="Select Employment Type", value=["FULLTIME", "INTERN"]),
            gr.Number(label="Minimum Salary ($)", value=0, minimum=0),
            gr.Number(label="Maximum Salary ($)", value=100000, minimum=0)
        ],
        outputs=gr.Textbox(label="Job Openings"),
        visible=False
    )
    
    counselor_status = gr.Markdown("", visible=False)
    
    option.change(main, inputs=option, outputs=[job_search_interface, counselor_status, gr.Textbox(label="Status")])

iface.launch()