Llama2-RAG-XAI-Expert-Model

Pre-Trained Llama2 Embedding RAG Explainable Expert AI LLM Model

Project Description

This project has been developed using the Llama2 Large Language Model specialized in Explainable AI (XAI). The project embeds the Llama2 model with PDF datasets to allow users to ask questions and receive answers along with source documents.

Project Workflow

Project Web Interface

Technologies and Libraries Used

• Llama2 Model: Large Language Model (LLM)
• LangServe APIs: APIs for language services
• FastAPI: Fast and modern API development tool
• Ngrok: Tool for exposing local servers to the internet
• Pinecone: Cloud service used for vector database
• Langchain: Library for natural language processing and data preparation
• RAG: RAG, or Retrieval-Augmented Generation, is a hybrid approach that combines retrieval-based and generation-based methods for natural language processing tasks.
• HTML, CSS, JavaScript: Technologies used for web interface development

Project Structure and Installation

1. Requirements: Dependencies and requirements to run the project
2. Installation: Steps and commands to install the project

   git clone https://github.com/user/project.git
   cd project

3. Configuration: Configuration steps and files required
4. Running: Steps to run and test the project

Usage

1. Starting the API Server: Steps to start the API server using FastAPI
2. Using the Web Interface: Guidelines for users to interact with the system through the web interface

• Developer: Mehmet Emin Ak & Elif Beyza Tok

Project Thesis

🔗To learn more details about this project read Thesis.pdf