AI-Powered Learning Path Generator

# PathAI - Installation Instructions

**Step-by-step guide to set up and run the project**

---

## Prerequisites

Before you begin, ensure you have the following installed:

- **Python 3.8 or higher** - Download from [python.org](https://www.python.org/downloads/)

- **pip** (comes with Python)

- A **Google Cloud account** (for OAuth setup)

---

## Installation Steps

### 1. Clone the Repository

**Using Git:**

```bash

git clone https://github.com/AP24110011751/Path-AI-AI-PoweredLearning-path-generator-.git

cd "Path-AI-AI-PoweredLearning-path-generator-"

```

**Or download as ZIP:**

1. Visit: https://github.com/AP24110011751/Path-AI-AI-PoweredLearning-path-generator-

2. Click green **"Code"** button

3. Click **"Download ZIP"**

4. Extract and open the folder

---

### 2. Install Dependencies

Run the following command to install all required Python packages:

```bash

pip install -r requirements.txt

```

**Packages installed:**

- Flask (web framework)

- google-genai (AI API)

- google-auth (authentication)

- python-dotenv (environment variables)

- PyPDF2, python-docx (document processing)

- requests (HTTP client)

- openai (additional AI support)

---

### 3. Configure Environment Variables

Create a `.env` file in the project root directory with these values:

```env

GEMINI_API_KEY=your_google_gemini_api_key

GOOGLE_CLIENT_ID=your_google_oauth_client_id

FLASK_SECRET_KEY=your_random_secret_key

```

#### Getting Your API Keys:

**Google Client ID (OAuth):**

1. Go to [Google Cloud Console](https://console.cloud.google.com)

2. Create a new project or select existing one

3. Go to APIs & Services → Credentials

4. Click "Create Credentials" → OAuth 2.0 Client ID

5. Choose "Web application" as type

6. Add authorized JavaScript origins:

   - `http://localhost:5000`

   - `http://127.0.0.1:5000`

7. Copy the Client ID value

**Gemini API Key:**

1. Visit [Google AI Studio](https://aistudio.google.com)

2. Click "Get API Key"

3. Create a new API key

4. Copy the key value

**Flask Secret Key:**

- Any random string, e.g., `dev-secret-key-@#$%^&*`

---

### 4. Run the Application

```bash

python app.py

```

You should see:

```

==================================================

  AI Learning Path Generator

  Open: http://localhost:5000

==================================================

 * Running on http://localhost:5000

 * Debug mode: on

```

---

### 5. Access the Application

Open your browser and navigate to:

```

http://localhost:5000

```

---

## Verify Installation

Test that everything works:

- ✓ Landing page loads

- ✓ "Sign in with Google" button appears

- ✓ Click to sign in (should authenticate)

- ✓ Skill selection displays

- ✓ Career goal selection works

- ✓ Roadmap generates successfully

---

## Troubleshooting

| Problem | Solution |

|---------|----------|

| **Google sign-in fails** | Ensure `http://localhost:5000` is in Google Cloud Credentials → Authorized JavaScript origins |

| **ModuleNotFoundError** | Run `pip install -r requirements.txt` again |

| **Port 5000 in use** | Change port in app.py last line: `app.run(debug=True, port=8000)` |

| **API keys not working** | Verify .env file exists in project root and variables are correct |

| **Database errors** | Delete `pathai.db` and restart - it will be recreated |

---

## Project Structure

```

AI path generator/

├── app.py                 # Main Flask application

├── ai_engine.py          # AI generation logic

├── db.py                 # Database functions

├── requirements.txt      # Dependencies

├── .env                  # Environment variables (create this)

├── static/

│   ├── css/style.css

│   └── js/app.js

├── templates/

│   ├── index.html

│   └── admin.html

└── pathai.db            # SQLite database

```

---

## Next Steps

1. **Create your first roadmap** - Sign in and select skills/goals

2. **Track progress** - Mark completed skills and build streaks

3. **Use AI chatbot** - Get help on learning topics

4. **Admin panel** - Visit `/admin` for management tools

---

## Production Deployment

For deploying to production:

- Use Gunicorn: `pip install gunicorn && gunicorn app:app`

- Migrate SQLite to PostgreSQL

- Enable HTTPS

- Set environment variables on your hosting platform

---

## Support

- Full documentation: See `PROJECT_DOCUMENTATION.docx`

- Technical report: See `PROJECT_REPORT.docx`

- Issues? Check the troubleshooting section above

---

**Questions?** Refer to the DOCUMENTATION.md file in the project root.

Enjoy learning with PathAI! 🚀

• First time setup steps
• Dashboard navigation
• Progress tracking
• How to use chatbot
• Resume analysis instructions
• Admin panel access
• Key features table
• Important notes & warnings

• Operating system requirements
• Software prerequisites
• Browser compatibility
• Hardware minimums
• Internet connectivity note