File size: 3,320 Bytes
cdafb57 addc2a2 cdafb57 dfa2f71 b351531 dfa2f71 b351531 dfa2f71 b351531 dfa2f71 b351531 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 |
---
license: mit
base_model:
- meta-llama/Llama-3.2-3B-Instruct
pipeline_tag: text-generation
library_name: adapter-transformers
tags:
- langgraph
- educational
- tutor
- ai-tutor
- adaptive-learning
- text-generation
- llama3.2
---
# π€ Enhanced AI Tutor System using LLaMA-3 and LangGraph
[](LICENSE)
[](https://python.langgraph.dev/)
[](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
An **adaptive, feedback-based AI tutor system** built using:
- π§ Meta's [LLaMA-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
- π [LangGraph](https://github.com/langchain-ai/langgraph) for multi-agent workflow
- β‘ Hugging Face Transformers (4-bit quantization for efficiency)
- β
PyTorch, BitsandBytes, Accelerate for seamless GPU usage
---
## π What It Does
This notebook walks you through a **complete interactive tutor session** that:
1. π Asks a question from a topic you choose
2. π Evaluates your answer and gives structured feedback
3. π§ͺ Generates a new practice question
4. π Tracks your progress and adapts difficulty
It's like having your own AI teacher, personalized to your learning!
---
## π View Notebook in Colab
[](https://colab.research.google.com/drive/1X4QwSB48fddXATlJBYtab16l7TM72KZk?usp=sharing)
You can explore the full .ipynb notebook on Google Colab using the button above.
---
## π Project Structure
```
βββ EnhancedTutorSystem.ipynb
βββ README.md
βββ requirements.txt
```
---
## π§ Model Info
This project uses (but does not rehost) Meta's official instruction-tuned model:
[](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
The model is loaded via transformers using 4-bit quantization (BitsAndBytes)
**Note:** You must agree to Meta's license to access the model.
---
## π― Features
- βοΈ Adaptive questions across difficulty levels
- π Real-time performance tracking
- π€ Intelligent feedback on every answer
- π‘ LangGraph-powered multi-agent workflow
- π§΅ Fully reproducible session history
---
## π Coming Soon
- π A Hugging Face Space with a user-friendly UI
- π Student progress export to PDF
- π― Topic-based quiz sessions
- π§ͺ Integration with LangChain for evaluation metrics
---
## π License
This project is released under the MIT License.
---
## π Acknowledgments
- π§ Meta AI for LLaMA-3
- π LangGraph by LangChain
- π€ Hugging Face for open infrastructure
---
## π¬ Contact / Feedback
[](https://github.com/Mrigank005)
[](https://www.linkedin.com/in/mrigank005)
Feel free to raise issues or suggestions on GitHub
Or connect via Hugging Face community tab!
**Happy learning!** π‘
---
|