AI Smart Study Planner

An AI-powered study planning application built with Streamlit and Ollama that generates personalized study roadmaps, learning strategies, resource recommendations, and curated YouTube course suggestions based on a user's goals and available study time.

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Project Structure

study_planner/
│
├── app.py
│
├── assets/
│   └── styles.py
│
├── prompts/
│   └── study_prompt.py
│
├── services/
│   └── ollama_service.py
│
├── utils/
│   ├── parser.py
│   ├── youtube_utils.py
│   └── calculations.py
│
├── ui/
│   ├── sidebar.py
│   ├── home.py
│   ├── dashboard.py
│   └── tabs.py
│
├── requirements.txt
│
└── README.md

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Tech Stack

Frontend

• Streamlit

AI Models

• Ollama
• Llama 3
• Qwen 3
• Mistral
• Gemma
• Any locally installed Ollama model

Backend

• Python

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How It Works

1. User enters:

   • Subject
   • Study Duration
   • Daily Study Hours
   • Current Knowledge Level

2. User selects an Ollama model.

3. The application dynamically generates a structured prompt.

4. The selected local LLM creates:

   • Study Timetable
   • Learning Phases
   • Success Tips
   • Resource Recommendations
   • YouTube Course Recommendations

5. The response is parsed and displayed in a structured dashboard.

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Installation

Clone the Repository

git clone https://github.com/<your-username>/study_planner.git
cd study_planner

Install Dependencies

pip install -r requirements.txt

Install Ollama

Download Ollama from:

https://ollama.com/download

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Pull a Model

Example:

ollama pull llama3

or

ollama pull qwen3

Verify installation:

ollama list

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Run the Application

streamlit run app.py

or

python -m streamlit run app.py

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