removed runs-on

.github/workflows/Docker Build & Push.yml

@@ -2,7 +2,9 @@ name: Docker Image CI
 
 on:
   push:
-    branches: [ "main" ]
+    paths: 
+      - '**'
+      - '!.github/workflows/**'
   pull_request:
     branches: [ "main" ]
 
@@ -10,7 +12,6 @@ jobs:
 
   build:
 
-    runs-on: ubuntu-latest
 
     steps:
     - name: checkout code

.github/workflows/run-container.yml

@@ -7,14 +7,14 @@ on:
 
 jobs:
   run-docker:
-    runs-on: ubuntu-latest
-
     steps:
-      - name: Run container
+      - name: pull image
+        run: docker pull ahmedhesham301/jobfit-ai:latest
+      - name: Create .env file
         run: |
-          docker run \
+          echo "smtp_email=${{ secrets.SMTP_EMAIL }}" >> .env
-            -e smtp_email=${{ secrets.SMTP_EMAIL }} \
+          echo "smtp_password=${{ secrets.SMTP_PASSWORD }}" >> .env
-            -e smtp_password=${{ secrets.SMTP_PASSWORD }} \
+          echo "receiver_email=${{ secrets.RECEIVER_EMAIL }}" >> .env
-            -e receiver_email=${{ secrets.RECEIVER_EMAIL }} \
+          echo "api_keys=${{ secrets.API_KEYS }}" >> .env
-            -e api_keys=${{ secrets.API_KEYS }} \
+      - name: Run container
-            ahmedhesham301/jobfit-ai:latest
+        run: docker run --env-file .env ahmedhesham301/jobfit-ai:latest

filter.py

@@ -12,6 +12,7 @@ total_fail_empty_response = 0
 
 
 def filter_jobs(jobs, cv, api_keys, good_fit_jobs):
+    global total_fail,total_overload,total_fail_overload,total_empty_response,total_fail_empty_response
     key_number = 0
 
     for i, job in jobs.iterrows():
@@ -72,7 +73,7 @@ def filter_jobs(jobs, cv, api_keys, good_fit_jobs):
             logging.critical("All attempts failed")
             continue
 
-        if ai_response_dict["percentage"] > 50:
+        if ai_response_dict["percentage"] > 70:
             good_fit_jobs.append(
                 {
                     "title": job["title"],
@@ -90,4 +91,4 @@ def print_stats():
     stats = f"""total fail: {total_fail}
 total empty responses: {total_empty_response} fail: {total_fail_empty_response}
 Total overloads:       {total_overload}       fail: {total_fail_overload}"""
-    print(stats)
+    logging.warning(stats)

instruction.txt

@@ -1,42 +1,60 @@
 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
+DevOps Engineer
-Cairo, Egypt
+ahmed.hesham.farag@gmail.com
-LinkedIn:https://www.linkedin.com/in/ahmed-hesham0/ 
+linkedin:https://www.linkedin.com/in/ahmed-hesham0/
-GitHub:https://github.com/ahmedhesham301
+Cairo,Egypt
-PROFILE
+website:ahmeddev.net
-DevOps Engineer with hands-on experience in automating CI/CD pipelines, containerizing
+github:https://github.com/ahmedhesham301
-applications, and deploying scalable infrastructure on AWS using Docker, Terraform, and
+SUMMARY:
-Ansible. Skilled in backend development with Python and Go, building RESTful APIs and
+Aspiring DevOps engineer with a strong drive to learn and grow. Currently focused on building a solid
-automating system workflows.
+foundation through consistent learning and hands-on practice. Always curious and ready to face challenges as
-EDUCATION
+part of the learning journey. Looking for an internship opportunity where I can contribute, learn from
-Sadat Academy | Cairo, Egypt
+experienced professionals, and take meaningful steps toward becoming a skilled engineer.
-Computer science
+EDUCATION:
-Predicted Grade: Very good
+Bachelor of Computer Science
-Oct 2022 – June 2026
+Sadat Academy
-TECHNICAL SKILLS
+Sep 2022 – Jun 2026
--DevOps Tools: Jenkins, Docker, Ansible, Terraform.
+EXPERIENCE:
--Programming & Scripting: Python, GO, Bash, YAML, JSON.
+DevOps Intern | GhaymahSep 2025 – Present
--Monitoring & Observability: Prometheus, Grafana.
+DevOps Intern | Orange Digital Centre, Cairo, EgyptJan 2025 – Feb 2025
--Cloud Platforms & OS: Linux, AWS, Ubuntu.
+SKILLS:
--Database: SQL, PostgreSQL.
+Containerization & Orchestration: Docker
--Version control: Git, GitHub.
+Cloud Provider: AWS
-Projects
+CI/CD: Jenkins & Github Actions
-•Built CI/CD pipeline using Jenkins to test and deploy Flask app to EC2 on AWS. The
+Monitoring & Observability: Prometheus & Grafana
-pipeline included building a Docker image, pushing it to Docker Hub, provisioning
+Configuration Management & IaC: Ansible & Terraform
-infrastructure with Terraform, and configuring the server using Ansible.
+Version Control: Git & GitHub
-GitHub Repo: weather-app
+Programming & Scripting: Python, Bash, Golang
-•A Docker image for a Minecraft server that allows you to specify the desired version as
+Database: Postgresql & SQL
-an argument. The image automatically downloads the specified version from Mojang's
+
-website and launches the server with a single command. GitHub repo
+PROJECTS:
-•An Amazon price tracker that monitors the price of a specified item. It scrapes the current
+-weather-app
-price and sends you an email notification whenever the price drops below your desired
+Automated application deployment using Docker containers for consistent environments.
-price.
+Implemented CI/CD pipelines with Jenkins to streamline build, test, and deployment processes.
-EXPERIENCE
+Provisioned and managed cloud infrastructure using Terraform for scalable and secure resources.
-Orange Digital Centre
+Configured server environments and orchestration with Ansible for efficient configuration management.
-Jan 2025 – Feb 2025
+Applied best practices in infrastructure as code, automation, and cloud resource optimization.
-DevOps internship
+
-Gained hands-on experience in CI/CD pipelines using Jenkins, Ansible, and Terraform.
+-containerizing Minecraft server
-ADDITIONAL SKILLS
+Designed and implemented automated scripts for building, deploying, and running a Minecraft server
-Languages: Arabic (Native), English (Fluent)Microsoft Office: Proficient in Word and PowerPoint
+using Bash and Docker.
+Developed Dockerfile and shell scripts to streamline server setup, configuration, and lifecycle management.
+Containerized the server for consistent, reproducible deployments across environments.
+Automated build and deployment processes to minimize manual intervention and improve reliability.
+Documented setup and usage instructions for ease of onboarding and maintenance.
+
+-go url shortener
+Developed a full-stack URL shortening service using Go (backend) and JavaScript/HTML (frontend).
+Implemented RESTful APIs for creating, retrieving, and redirecting shortened URLs.
+Integrated PostgreSQL for persistent storage and efficient URL management.
+Added monitoring and metrics collection with Prometheus.
+Containerized the application using Docker and managed multi-service deployment with Docker Compose.
+Applied middleware for request monitoring.
+Wrote modular, maintainable code following best practices.
+
+-JobFit AI
+A Python-based application that leverages Google Gemini AI to analyze job descriptions and candidate
+profiles, search for relevant jobs, and generate a fit percentage. The system highlights strengths, identifies
+skill gaps, and automatically sends emails with high-fit job matches to users.

jobs.py

@@ -1,28 +1,37 @@
 from jobspy import scrape_jobs
 import logging
 
-def getJobs(jobTitle, results_wanted, hours_old):
+
+def getJobs(
+    jobTitle,
+    results_wanted,
+    hours_old,
+    country,
+    location,
+    is_remote,
+):
     jobs = scrape_jobs(
         site_name=[
             "indeed",
             "linkedin",
             # "zip_recruiter",
-            "google",
+            # "google",
             # "glassdoor",
             # "bayt",
             # "naukri",
             # "bdjobs",
         ],
         search_term=jobTitle,
-        location="Cairo",
+        location=location,
         results_wanted=results_wanted,
-        google_search_term=f"{jobTitle} jobs near Cairo since {hours_old} hours",
+        # google_search_term=f"{jobTitle} jobs near Cairo since {hours_old} hours",
         hours_old=hours_old,
-        country_indeed="Egypt",
+        country_indeed=country,
+        is_remote=is_remote,
         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"],
     )
-    logging.warning(f"Found {len(jobs)} {jobTitle} jobs")
+    logging.warning(f"Found {len(jobs)} {jobTitle} jobs in {country},{location}")
     # print(jobs)
     return jobs
     # jobs.to_csv(

main.py

@@ -23,20 +23,23 @@ with open("instruction.txt", "r") as f:
     CV = f.read()
 
 
-def get_jobs(job_title, results_wanted, hours_old):
+def get_jobs(job_title, results_wanted, hours_old, country, location, is_remote):
     global all_jobs
-    jobs = getJobs(job_title, results_wanted, hours_old)
+    jobs = getJobs(job_title, results_wanted, hours_old, country, location, is_remote=False)
     all_jobs = pd.concat([all_jobs, jobs], ignore_index=True)
 
 
 if __name__ == "__main__":
-    get_jobs("devops", results_wanted=30, hours_old=2)
+    get_jobs("devops", results_wanted=30, hours_old=2, country="egypt", location="cairo")
-    get_jobs("backend", results_wanted=30, hours_old=2)
+    get_jobs("backend", results_wanted=30, hours_old=2, country="egypt", location="cairo")
-    get_jobs("software engineer", results_wanted=30, hours_old=2)
+    get_jobs("software engineer",results_wanted=30,hours_old=2,country="egypt",location="cairo",)
-    get_jobs("cloud", results_wanted=30, hours_old=2)
+    get_jobs("cloud", results_wanted=30, hours_old=2, country="egypt", location="cairo")
-    get_jobs("sre", results_wanted=30, hours_old=2)
+    get_jobs("site reliability engineer",results_wanted=30,hours_old=2,country="egypt",location="cairo")
-    get_jobs("intern", results_wanted=30, hours_old=2)
+    get_jobs("sre", results_wanted=30, hours_old=2, country="egypt", location="cairo")
+    get_jobs("intern", results_wanted=30, hours_old=2, country="egypt", location="cairo")
+    # get_jobs("devops",results_wanted=200,hours_old=2,country="worldwide",location="",is_remote=True)
     all_jobs.drop_duplicates(inplace=True, ignore_index=True)
+    logging.warning(f"Total jobs no duplicates: {len(all_jobs)}")
     filter_jobs(all_jobs, CV, api_keys, good_fit_jobs)
     if len(good_fit_jobs) > 0:
         send_email(SENDER, RECEIVER, PASSWORD, good_fit_jobs)