LSTM-AIChatPersian: A Persian RAG Chatbot This repository contains the development of a Persian Retrieval-Augmented Generation (RAG) chatbot. The project aims to create an intelligent conversational AI capable of understanding and responding effectively in the Persian language.

Key Features Advanced Deep Learning Techniques: Utilizes LSTM (Long Short-Term Memory) with attention mechanisms for robust language processing.

Self-Supervised Learning: Incorporates self-supervised learning to enhance the model's ability to learn from large datasets.

Embedding and Tokenization: Employs advanced embedding and tokenization techniques tailored for the Persian language.

Google API Integration: Integrates with Google API for expanded functionality and improved conversational capabilities.

Redis for Efficient Recall: Leverages Redis for efficient storage and retrieval of information, enabling quick and accurate responses.

Optimized Performance: Optimized using various techniques, including Adam and RMSprop optimizers, L1 and L2 regularization methods, and data augmentation to improve robustness and accuracy.

Rigorous Evaluation: The chatbot's performance is rigorously evaluated using standard natural language processing metrics such as BLEU, ROUGE, and METEOR.

License This project is licensed under the Apache-2.0 License, promoting open-source collaboration and widespread use.