LLM-Product-Assistant

Overview

The LLM-Product-Assistant is an interactive Q&A system designed to help users to better understand and navigate the functionalities of a particular product. For this specific project, we focused on troubleshooting issues users might have with Amazon VPC.

Table of Contents

1. Technologies Deployed
2. Installation & Setup
3. Contributors

Technologies Deployed

• LangChain: html loader, text summarization and chunking, wrappers for OpenAI and Pinecone
• OpenAI API: embeddings generation, retrieval
• Pinecone: embeddings storage and indexing, similairty search for top_k
• PEFT: LLaMa fine-tunning

Installation & Setup

Prerequisites

• Python version: 3.10.7
• Obtain the required API keys from a team member.

Steps

1. Clone the Repository:

   git clone <repository-link>
   cd LLM-Product-Assistant

2. Navigate to the Main Folder:

   cd path/to/main/folder

3. Build the Docker Image:

   docker build -t chatbot -f 07_Docker/Dockerfile .

4. Run the Docker Container:

   docker run -p 5000:5000 chatbot

5. Access the Application: Click on the link that appears in the console to start interacting with the chatbot.

Contributors

• Sam Swain: Project Lead
• Zhengyuan (Donald) Li: Generative AI Engineer
• Brian Hong: Generative AI Engineer
• Wencheng Zhang: Generative AI Engineer