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🧠 LLM-RAG

🚀 Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs) Projects

1️⃣ LLM_1 link (Multilingual RAG Agent (English & Persian))

  • This project implements a sophisticated, multilingual Retrieval-Augmented Generation (RAG) agent that understands and responds in both English and Persian. The agent is designed to be "smart" by incorporating conversation memory and a degree of self-awareness, allowing it to provide contextually relevant and accurate answers based on a provided knowledge base. It leverages state-of-the-art Natural Language Processing (NLP) techniques, including vector embeddings for efficient document retrieval and a Large Language Model (LLM) for generating human-like responses.

2️⃣ LLM_2 link (LLM RAG Chatbot (Hybrid Retrieval & Phi-3))

  • A professional, enhanced Retrieval-Augmented Generation (RAG) chatbot built in Python. This project utilizes a sophisticated Hybrid Retrieval mechanism (BM25 + FAISS with reranking) for highly accurate context retrieval and leverages the Microsoft Phi-3-mini-4k-instruct Large Language Model for superior, contextual, and multilingual responses.

🟦 LLM_X link (etc)

  • Some examples of Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs)

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Retrieval-Augmented Generation (RAG) agent using Large Language Models (LLMs) Projects

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chatbot rag large-language-models llm large-language-model llm-agent retrieval-augmented-generation rag-chatbot

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