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| license: other | |
| title: CareerBoost | |
| sdk: streamlit | |
| emoji: 📈 | |
| colorFrom: blue | |
| colorTo: purple | |
| pinned: true | |
| short_description: AI-powered, futuristic, and career-accelerating | |
| # CareerBoost: Your Job Search & Prep Companion | |
| **Empowering Your Career Journey with AI-Driven Tools** | |
| **Creator**: Musabbir KM | |
| --- | |
| ## Overview | |
| CareerBoost is an AI-powered web application designed to assist job seekers in finding job opportunities, preparing for interviews, and creating professional CVs. Built with a focus on usability and efficiency, it leverages advanced AI agents to deliver tailored results for users worldwide, with a special emphasis on the Indian job market. | |
| --- | |
| ## Features | |
| CareerBoost offers four core functionalities, each powered by specialized AI agents: | |
| 1. **Job Finding Agent**: | |
| - Scrapes job listings from major job boards like Naukri.com, Shine.com, LinkedIn, and Indeed | |
| - Supports location-based searches (e.g., "data science in Kochi") | |
| - Displays detailed job information: title, company, location, salary range, and application link | |
| - Intelligent fallback to web search when direct scraping fails | |
| - Real-time alerts for new postings matching your profile | |
| - Fetches structured job listings using the RapidAPI JSearch endpoint | |
| 2. **Interview Preparation**: | |
| - Generates 10 tailored interview questions and answers (4 technical, 3 behavioral, 3 situational) | |
| - Incorporates latest trends (2022–2025) covering emerging skills like: | |
| - Machine Learning Ops (MLOps) | |
| - Ethical AI frameworks | |
| - Cloud-native technologies | |
| - Data visualization tools (Tableau, PowerBI) | |
| - Includes company-specific question banks for top employers | |
| - Provides sample answers with STAR (Situation-Task-Action-Result) format | |
| - Delivers plain-text output for easy review and practice | |
| 3. **CV Creator**: | |
| - Builds ATS-friendly CVs optimized for applicant tracking systems | |
| - Custom templates for different experience levels (Entry, Mid, Senior) | |
| - Includes smart sections: | |
| - Professional Summary with keywords | |
| - Skills Matrix with proficiency levels | |
| - Experience with measurable achievements | |
| - Education with relevant coursework | |
| - Auto-formatting for consistent styling | |
| - Export options (PDF, DOCX, plain text) | |
| 4. **Career Insights**: | |
| - Daily curated feed of job market trends and tech news | |
| - Company watchlists with hiring alerts | |
| - Salary benchmarking by role and location | |
| - Emerging technology spotlights (AI, Blockchain, IoT) | |
| - Industry-specific reports (IT, Healthcare, Finance) | |
| - Local job market heatmaps | |
| - Skill gap analysis with learning recommendations | |
| - Networking event calendars | |
| --- | |
| ## Technologies Used | |
| CareerBoost is built with a robust tech stack to ensure performance and scalability: | |
| - **Frontend**: | |
| - [Streamlit](https://streamlit.io/) (v1.29.0): For the interactive web interface. | |
| - Custom CSS: For enhanced UI styling (tabs, cards, logo display). | |
| - **Backend & AI**: | |
| - [LangChain](https://python.langchain.com/) (v0.2.16): For agent orchestration and tool integration. | |
| - [Google Gemini LLM](https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini) (via langchain-google-genai v1.0.8): Powers natural language processing and generation. | |
| - [DuckDuckGo Search](https://github.com/deedy5/duckduckgo_search) (v6.2.11): For fallback web searches. | |
| - [RapidAPI JSearch](https://rapidapi.com/letscrape-6bRBaM6guO5/api/jsearch): For structured job data. | |
| - [aiohttp](https://docs.aiohttp.org/) (v3.10.5): For asynchronous web scraping. | |
| - [Selectolax](https://github.com/rushter/selectolax) (v0.3.21): For efficient HTML parsing. | |
| - [Tenacity](https://github.com/jd/tenacity) (v8.5.0): For retry logic in scraping. | |
| - [python-dotenv](https://github.com/theskumar/python-dotenv) (v1.0.1): For environment variable management. | |
| --- | |
| ## Agent Info | |
| CareerBoost leverages four specialized AI agents, each designed for a specific task: | |
| - **Job Finding Agent**: | |
| - Uses a ReAct (Reasoning + Acting) framework to scrape job boards asynchronously. | |
| - Handles errors like rate limits and timeouts with retries and randomized delays. | |
| - Formats output as a numbered list for clarity. | |
| - **RapidAPI Job Search Agent**: | |
| - Queries the JSearch API for structured job data. | |
| - Processes results into a consistent format (title, company, location, link, source). | |
| - **Interview Preparation Agent**: | |
| - Generates 10 questions and answers using the Google Gemini LLM. | |
| - Integrates web search insights to reflect recent trends (e.g., cloud computing, ethical AI). | |
| - Fixed to prevent iteration limit errors by enforcing strict tool usage. | |
| - **CV Creator Agent**: | |
| - Generates ATS-friendly CVs with a single LLM call. | |
| - Customizes content based on user input, ensuring relevance to the job field. | |
| --- | |
| ## Get In Touch | |
| - We’d love to hear from you! Whether you have questions, feedback, or just want to chat, reach out to us anytime. | |
| - 📧 **Email**: [musabbirmushu@gmail.com](mailto:musabbirmushu@gmail.com) | |
| - 💼 **LinkedIn**: [CareerBoost LinkedIn](https://www.linkedin.com/in/muhammed-musabbir-km-0302b8212utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_appt) | |
| - 🌐 **Website**: [www.careerboost.ai](https://omnicipher.onrender.com) | |
| - ⌨️ **GitHub**: [CareerBoost GitHub](https://github.com/musabbirkm) | |