Getting Started with GPT4 API, GPT4 RAG, OpenAI GPT4 Assistant, OpenAI Models
-
Updated
May 16, 2024 - Jupyter Notebook
Getting Started with GPT4 API, GPT4 RAG, OpenAI GPT4 Assistant, OpenAI Models
Chainlit app for RAG chat with documents Parsing PDF documents using LlamaParse, Qdrant, and the Groq model
User-friendly interface for creating effective Retrieval Augmented Generation (RAGs)
This project aims to build a chatbot for Amazon sellers, addressing various issues related to selling on Amazon such as logistics, marketing, and more. This is an educational study for experimental purposes and not a fully-fledged chatbot solution. We used Llama-Parse, GPT3.5Turbo and Streamlit..
Parsing PDF, PPT, and Txt documents using LlamaParse, Qdrant, and the Groq model
using Llama Parse to read pdf and convert into mark down or text
RAG application to track and analyze Safaricom Mpesa transactions from using LLMs.
Add a description, image, and links to the llamaparse topic page so that developers can more easily learn about it.
To associate your repository with the llamaparse topic, visit your repo's landing page and select "manage topics."