🧪 PathFinder AI: Student Career Pathway Recommender

Discover your ideal career path with the power of AI!

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🚀 Overview

PathFinder AI is an interactive, AI-powered web app that recommends career paths to students based on their interests, hobbies, and academic strengths. Built with Streamlit and Mistral LLM, it provides personalized, actionable guidance in a beautiful, modern UI.

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✨ Features

• 🧑‍🎓 Conversational career guidance
• 🎨 Modern, responsive UI (dark mode, mobile-friendly)
• 🧠 LLM-powered recommendations (Mistral)
• 🗂️ Predefined career clusters (STEM, Arts, Sports, Business, Social Sciences)
• 💬 Explanations for each recommended path
• 🔄 Reset and start over anytime
• ☁️ Easy deployment to Streamlit Cloud or Render

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🛠️ Setup

1. Clone the repository:

   git clone https://github.com/shubanborkar/PathFinder.git
   cd PathFinder

2. Install dependencies:

   pip install -r requirements.txt

3. Set your Mistral API key:

   export MISTRAL_API_KEY=your-mistral-key-here

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💻 Usage

Run the app locally:

streamlit run streamlit_app.py

• Enter your interests, hobbies, and academic strengths.
• Click Get Recommendations to see personalized career paths and explanations.
• Use Reset All in the sidebar to start over.

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🌐 Deployment

Streamlit Community Cloud (Recommended)

1. Push your code to GitHub.
2. Go to Streamlit Cloud and create a new app from your repo.
3. Set streamlit_app.py as the main file.
4. Add your MISTRAL_API_KEY as a secret in the app settings.

Render

1. Connect your GitHub repo to Render.
2. Use the following start command:

   streamlit run streamlit_app.py --server.port $PORT --server.address 0.0.0.0

3. Add your API key as an environment variable.

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📁 Project Structure

├── agent.py           # Core agent logic (LLM, mapping, explanations)
├── career_paths.py    # Career clusters and mapping logic
├── prompts.py         # Prompt templates
├── streamlit_app.py   # Main Streamlit web app
├── main.py            # CLI interface (optional)
├── requirements.txt   # Python dependencies
├── test_agent.py      # Simple test for agent logic
├── README.md          # This file

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🙏 Credits

• Developed by Shuban Borkar
• Powered by Mistral AI and Streamlit
• UI icons from Flaticon
• GitHub: shubanborkar
• Email: shubanborkar@gmail.com
• LinkedIn: shubanborkar

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📜 License

MIT