Intial commit

2025-09-26 08:21:26 +03:00
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1,3 @@
 jobs.csv
 .venv
 __pycache__
--- a/ai.py
+++ b/ai.py
@@ -0,0 +1,68 @@
 # To run this code you need to install the following dependencies:
 # pip install google-genai
 import base64
 import os
 from google import genai
 from google.genai import types
 def generate(description, instruction):
    client = genai.Client(
        api_key=""
    )
    model = "gemini-2.5-flash"
    contents = [
        types.Content(
            role="user",
            parts=[
                types.Part.from_text(text=description),
            ],
        ),
    ]
    generate_content_config = types.GenerateContentConfig(
        thinking_config=types.ThinkingConfig(
            thinking_budget=0,
        ),
        response_mime_type="application/json",
        response_schema=genai.types.Schema(
            type=genai.types.Type.OBJECT,
            required=[
                "percentage",
                "why I'm I a good fit",
                "what I'm I missing",
            ],
            properties={
                "percentage": genai.types.Schema(
                    type=genai.types.Type.INTEGER,
                ),
                "why I'm I a good fit": genai.types.Schema(
                    type=genai.types.Type.STRING,
                ),
                "what I'm I missing": genai.types.Schema(
                    type=genai.types.Type.STRING,
                ),
            },
        ),
        system_instruction=[
            types.Part.from_text(text=instruction),
        ],
    )
    # for chunk in client.models.generate_content_stream(
    #     model=model,
    #     contents=contents,
    #     config=generate_content_config,
    # ):
    #     print(chunk.text, end="")
    response = client.models.generate_content(
        model=model,
        contents=contents,
        config=generate_content_config,
    )
    return response.text
 if __name__ == "__main__":
    generate()
--- a/alert.py
+++ b/alert.py
@@ -0,0 +1,48 @@
 import smtplib
 from email.mime.text import MIMEText
 from email.mime.multipart import MIMEMultipart
 def send_email(sender, receiver, password, good_fit_jobs):
    print("preparing message")
    html_body = """<html>
    <body style="font-family: Arial, sans-serif; line-height: 1.6;">
        <h2 style="color: #2c3e50;">My Job Alert</h2>
        <p><b>{count} jobs</b> have been found that match your profile:</p>
        <ul style="padding-left: 20px;">
    """.format(
        count=len(good_fit_jobs)
    )
    for job in good_fit_jobs:
        html_body += f"""
        <li style="margin-bottom: 15px;">
            <p><b>Title:</b> {job["title"]}</p>
            <p><b>URL:</b> <a href="{job["url"]}">{job["url"]}</a></p>
            <p><b>Percentage:</b> {job["percentage"]}</p>
            <p><b>Why I'm a good fit:</b> {job["why I'm I a good fit"]}</p>
            <p><b>What I'm missing:</b> {job["what I'm I missing"]}</p>
        </li>
        """
    html_body += """
        </ul>
    </body>
    </html>
    """
    message = MIMEText(html_body, "html")
    message["Subject"] = f"MY JOB ALERT: {len(good_fit_jobs)} jobs has been found"
    message["From"] = sender
    message["To"] = receiver
    print(f"Sending email with {len(good_fit_jobs)} jobs")
    with smtplib.SMTP("smtp.gmail.com", timeout=60, port=587) as connection:
        connection.starttls()
        connection.login(user=sender, password=password)
        connection.sendmail(
            from_addr=sender,
            to_addrs=receiver,
            msg=message.as_string(),
        )
        connection.close()
--- a/instruction.txt
+++ b/instruction.txt
@@ -0,0 +1,42 @@
 i will give you job descriptions and you tell me if i'm a good fit or not in a percentage, why I'm I a good fit and what I'm I missing
 this is my cv:
 Ahmed Hesham
 Ahmed.hesham.farag@gmail.com
 Cairo, Egypt
 LinkedIn:https://www.linkedin.com/in/ahmed-hesham0/ 
 GitHub:https://github.com/ahmedhesham301
 PROFILE
 DevOps Engineer with hands-on experience in automating CI/CD pipelines, containerizing
 applications, and deploying scalable infrastructure on AWS using Docker, Terraform, and
 Ansible. Skilled in backend development with Python and Go, building RESTful APIs and
 automating system workflows.
 EDUCATION
 Sadat Academy | Cairo, Egypt
 Computer science
 Predicted Grade: Very good
 Oct 2022 – June 2026
 TECHNICAL SKILLS
 -DevOps Tools: Jenkins, Docker, Ansible, Terraform.
 -Programming & Scripting: Python, GO, Bash, YAML, JSON.
 -Monitoring & Observability: Prometheus, Grafana.
 -Cloud Platforms & OS: Linux, AWS, Ubuntu.
 -Database: SQL, PostgreSQL.
 -Version control: Git, GitHub.
 Projects
 •Built CI/CD pipeline using Jenkins to test and deploy Flask app to EC2 on AWS. The
 pipeline included building a Docker image, pushing it to Docker Hub, provisioning
 infrastructure with Terraform, and configuring the server using Ansible.
 GitHub Repo: weather-app
 •A Docker image for a Minecraft server that allows you to specify the desired version as
 an argument. The image automatically downloads the specified version from Mojang's
 website and launches the server with a single command. GitHub repo
 •An Amazon price tracker that monitors the price of a specified item. It scrapes the current
 price and sends you an email notification whenever the price drops below your desired
 price.
 EXPERIENCE
 Orange Digital Centre
 Jan 2025 – Feb 2025
 DevOps internship
 Gained hands-on experience in CI/CD pipelines using Jenkins, Ansible, and Terraform.
 ADDITIONAL SKILLS
 Languages: Arabic (Native), English (Fluent)Microsoft Office: Proficient in Word and PowerPoint
--- a/jobs.py
+++ b/jobs.py
@@ -0,0 +1,30 @@
 from jobspy import scrape_jobs
 def getJobs(jobTitle, results_wanted, hours_old):
    jobs = scrape_jobs(
        site_name=[
            "indeed",
            "linkedin",
            # "zip_recruiter",
            "google",
            # "glassdoor",
            # "bayt",
            # "naukri",
            # "bdjobs",
        ],
        search_term=jobTitle,
        location="Egypt",
        results_wanted=results_wanted,
        google_search_term=f"{jobTitle} jobs near Cairo since {hours_old} hours",
        hours_old=hours_old,
        country_indeed="Egypt",
        linkedin_fetch_description=True,  # gets more info such as description, direct job url (slower)
        # proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
    )
    print(f"Found {len(jobs)} jobs")
    # print(jobs)
    return jobs
    # jobs.to_csv(
    #     "jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False
    # )  # to_excel
--- a/main.py
+++ b/main.py
@@ -0,0 +1,68 @@
 from jobs import getJobs
 from ai import generate
 from alert import send_email
 import json
 import time
 import logging
 SENDER = ""
 PASSWORD = ""
 RECEIVER = ""
 good_fit_jobs = []
 with open("instruction.txt", "r") as f:
    CV = f.read()
 def get_jobs(job_title, cv, results_wanted, hours_old):
    jobs = getJobs(job_title, results_wanted, hours_old)
    for i, job in jobs.iterrows():
        # print(job["description"])
        # print("_______________")
        print("index is :", i)
        if (i + 1) % 10 == 0 and i != 0:
            print("Sleeping to avoid API rate limits")
            time.sleep(60)
        try_count = 3
        while try_count > 0:
                try:
                    cleaned_description = "\n".join(
                        [line for line in job["description"].splitlines() if line.strip()]
                    )
                    ai_response = generate(cleaned_description, cv)
                    ai_response_dict = json.loads(ai_response)
                    break
                except json.JSONDecodeError as e:
                    try_count -= 1
                    print("_______________")
                    print(cleaned_description)
                    print("_______________")
                    print(ai_response)
                    print(e)
                    print("Sleeping after fail to avoid API rate limits")
                    time.sleep(6)
        else:
            print("All attempts failed.")
            continue
        # print(ai_response_dict)
        if ai_response_dict["percentage"] > 0:
            # print("adding job to good_fit_jobs")
            good_fit_jobs.append(
                {
                    "title": job["title"],
                    "url": job["job_url"],
                    "percentage": ai_response_dict["percentage"],
                    "why I'm I a good fit": ai_response_dict["why I'm I a good fit"],
                    "what I'm I missing": ai_response_dict["what I'm I missing"],
                }
            )
 if __name__ == "__main__":
    get_jobs("devops", CV, results_wanted=2, hours_old=4)
    # get_jobs("backend", CV, results_wanted=30, hours_old=2)
    if len(good_fit_jobs) > 0:
        send_email(SENDER, RECEIVER, PASSWORD, good_fit_jobs)
--- a/requirements.txt
+++ b/requirements.txt
@@ -0,0 +1,35 @@
 annotated-types==0.7.0
 anyio==4.11.0
 beautifulsoup4==4.13.5
 cachetools==5.5.2
 certifi==2025.8.3
 charset-normalizer==3.4.3
 google-auth==2.40.3
 google-genai==1.38.0
 h11==0.16.0
 httpcore==1.0.9
 httpx==0.28.1
 idna==3.10
 markdownify==0.13.1
 numpy==1.26.3
 pandas==2.3.2
 pyasn1==0.6.1
 pyasn1_modules==0.4.2
 pydantic==2.11.9
 pydantic_core==2.33.2
 python-dateutil==2.9.0.post0
 python-jobspy==1.1.82
 pytz==2025.2
 regex==2024.11.6
 requests==2.32.5
 rsa==4.9.1
 six==1.17.0
 sniffio==1.3.1
 soupsieve==2.8
 tenacity==9.1.2
 tls-client==1.0.1
 typing-inspection==0.4.1
 typing_extensions==4.15.0
 tzdata==2025.2
 urllib3==2.5.0
 websockets==15.0.1