https://github.com/chiragajain/placement-assistant
Vibe-Coded Flask-based web application acting as a Placement Assistant providing a comprehensive feedback based on the User's resume and the given Job description
https://github.com/chiragajain/placement-assistant
api css flask front-end-web-development gemini-pro-2-5 html placement-assistance placements python resume-analysis vibe-coded
Last synced: about 1 month ago
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Vibe-Coded Flask-based web application acting as a Placement Assistant providing a comprehensive feedback based on the User's resume and the given Job description
- Host: GitHub
- URL: https://github.com/chiragajain/placement-assistant
- Owner: ChiragAJain
- Created: 2025-07-26T15:28:25.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-09-02T02:56:03.000Z (9 months ago)
- Last Synced: 2025-09-02T04:25:51.780Z (9 months ago)
- Topics: api, css, flask, front-end-web-development, gemini-pro-2-5, html, placement-assistance, placements, python, resume-analysis, vibe-coded
- Language: HTML
- Homepage:
- Size: 41 KB
- Stars: 0
- Watchers: 0
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🤖 Personalized Placement Assistant
An intelligent web application that uses the Gemini 2.5 Pro API to analyze your resume against a job description, providing detailed feedback.
**Note: _This is built by Gemini Pro 2.5 as an experiment to test its capability to build full-fledge web application with few human tweaks for further refinement._**
## ✨ Features
* **AI-Powered Analysis:** Leverages Google's Gemini 2.5 Pro for a nuanced understanding of job roles and resumes.
* **Comprehensive Feedback:** Get a match score, interview and hiring probabilities, strength/gap analysis, and tailored advice.
* **Company Assessment:** Evaluates the company profile separately from the role match based on public knowledge.
* **Smart Caching:** Avoids redundant API calls by caching results for identical inputs, saving time and potential costs.
* **Simple Web Interface:** Easy-to-use UI for uploading documents and viewing results instantly.
## 🛠️ Tech Stack
* **Backend:** Python 3.12 with Flask
* **AI Model:** Google Gemini 2.5 Pro API
* **Frontend:** HTML, CSS, Vanilla JavaScript
## 🚀 Setup and Installation
Follow these steps to get the application running locally on your machine.
### 1. Prerequisites
* Python 3.12 or higher
* A Google Gemini API Key
### 2. Clone the Repository
```bash
git clone https://github.com/ChiragAJain/Placement-Assistant
cd Placement-Assistant
```
### 3. Set Up Environment Variables
Create a `.env` file in the project root:
```
GEMINI_API_KEY=your_gemini_api_key_here
```