📚 AI Study Notes Assistant

Day 4 of my AI Engineering Journey — Built a personal AI that answers questions about YOUR own study notes.

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💭 The Problem I Solved

When you study, you take notes. But finding information across many notes is slow. And testing yourself on what you wrote is even harder.

This app solves both problems:

• Save your notes in one place
• Ask AI anything about YOUR notes
• AI answers ONLY from what YOU wrote

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💡 Why This Is Special

Most AI answers from its general training data. This AI answers ONLY from your personal notes.

That is the core idea behind RAG — Retrieval Augmented Generation.

This project is the simplest version of RAG possible: Your notes → injected into system prompt → AI answers from them.

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✨ Features

• 📝 Add notes — save any study topic with full content
• 📖 View all notes — see everything you have saved
• 🤖 Ask AI about all notes — get answers across all topics
• 🔍 Ask AI about one note — deep dive into a specific topic
• 🔎 Search notes — find notes by keyword instantly
• 🗑️ Delete notes — remove notes you no longer need
• 💾 Persistent storage — notes saved to JSON, survive app restarts

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🔑 The Core Concept — Context Injection

system_prompt = f"""You are a study assistant.
Answer ONLY based on these notes:

{user_notes}  # ← This is the magic
"""

By injecting the user's notes directly into the system prompt, the AI becomes an expert on exactly what YOU studied. Nothing more. Nothing less.

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🗂️ How Notes Are Stored

Notes are saved locally in notes.json:

[
    {
        "id": 1,
        "topic": "RAG Systems",
        "content": "RAG stands for Retrieval Augmented Generation...",
        "date": "2026-05-11 14:30"
    }
]

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⚙️ Tech Stack

Tool	Purpose
Python	Core programming language
Groq API	AI inference platform
LLaMA 3.3 70B	The underlying language model
JSON	Local data storage
python-dotenv	Secure API key management
Git & GitHub	Version control

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🚀 How to Run

1. Clone the repository

   git clone https://github.com/PrashikSawant/ai-study-notes.git
   cd ai-study-notes

2. Install dependencies

   pip install groq python-dotenv

3. Create a .env file

GROQ_API_KEY = "Add your API KEY here"

4. Run the app

   python main.py

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📚 What I Learned

• How to read and write JSON files in Python
• How context injection works — the foundation of RAG
• How to build a multi-feature menu driven application
• Why AI answers change completely based on what context you give it
• How persistent local storage works without a database

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🗺️ What's Next

• 🔜 Research Paper Summarizer
• 🔜 PDF Reader + Q&A with ChromaDB
• 🔜 Full RAG System with Vector Database

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👨‍💻 About Me

I am Prashik — an aspiring AI Engineer on a 4-month intensive journey to become job-ready in Generative AI Engineering.

Follow my journey → LinkedIn

See all projects → GitHub

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Day 4 of 120 | May 11, 2026 | Status: ✅ Complete