SWOT Analyzer Powered by DeepSeek R1

Project Overview

This project leverages the advanced capabilities of DeepSeek R1, an AI model renowned for its exceptional reasoning performance, to deliver personalized SWOT Analyses (Strengths, Weaknesses, Opportunities, and Threats) by analyzing CVs and Job Descriptions.

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Ideal For

• Job Seekers: Align your skills with market demands.

• Recruiters: Precisely identify and bridge talent gaps.

Key Features

• Advanced Reasoning: Utilizes DeepSeek R1's state-of-the-art reasoning capabilities for in-depth analysis.

• Actionable Insights: Provides strategic recommendations for growth and improvement.

• Efficiency & Precision: Streamlines decision-making, saving time and reducing bias.

Technical architecture

The system is built using Streamlit as the user interface, where users upload a resume file( pdf or doc format) and manually input the job description.

Once the input is received, the system parses the resume file using MarkItDown (a Python tool from Microsoft for converting files and office documents to Markdown) for structured extraction.

The parsed information, along with the job description, is then passed to the deepseek-r1-distill-qwen-32b model from groqcloud, which acts as the reasoning engine to analyze the content and generate a SWOT analysis. The model identifies:

• Strengths based on skills and experience
• Weaknesses in missing qualifications
• Opportunities in aligning competencies with job trends
• Threats in skill gaps or competition

The results are then processed and displayed back in the Streamlit app, providing users with actionable insights to improve their resume alignment with job requirements.

This system seamlessly integrates resume parsing, job description analysis, and AI-driven reasoning to offer a comprehensive SWOT evaluation for career enhancement.

How It Works

1. Upload: Submit your CV and Job Description.

2. Analyze: Our advanced AI compares your skills and experience with job requirements.

3. Result: A comprehensive SWOT Analysis pinpointing key strengths and areas for improvement.

Getting Started

Prerequisites

• Python 3.11 or above 🐍
• Groq API for inference, which is currently available for free in its beta version with rate limits. You can obtain your API key here after creating an account: Groq API.

💻 Local Deployment

1. Clone the Repository

git clone https://github.com/Mouez-Yazidi/SWOT-Analyzer-Powered-by-DeepSeek-R1.git
cd SWOT-Analyzer-Powered-by-DeepSeek-R1

2. Add Environment Variables

• Create a .env file and add the following variables according to the credentials you obtained from the required platforms:

  GROQ_KEY=
  

3. Install Dependencies

Navigate to the local directory and install the necessary dependencies:

pip install -r requirements.txt

4. Running the App Locally

To run the app locally, execute the following command:

streamlit run main.py --environment local

You should now be able to access the app at http://localhost:8501 🌐.

☁️ Streamlit Cloud Deployment

1. Prepare Your Repository

Ensure that your code is pushed to a GitHub repository 📂.

2. Link with Streamlit Cloud

• Visit Streamlit Cloud and sign in.
• Connect your GitHub repository 🔗.
• Choose your repository and branch.

3. Environment Variables

• Go to the "Advanced settings" section of your app.
• In the "Secrets" section, input any sensitive information, such as API keys or other credentials.
• Make sure to add this variables according to the credentials you obtained from the required platforms.

GROQ_KEY=""

Streamlit Cloud will:

• Install dependencies from requirements.txt 📦

🎉 You’re all set! Your app will now be live on Streamlit Cloud!

✨ Show Your Support!

If you appreciate this project, I would be grateful if you could give it a star on GitHub. Your support motivates us to enhance and expand our work!

License

This project is licensed under the MIT License.