Using Qdrant, Fastembed, Google Cloud, OpenAI to build a Question Answer Cloud Based RAG System
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Updated
Mar 28, 2024 - Jupyter Notebook
Using Qdrant, Fastembed, Google Cloud, OpenAI to build a Question Answer Cloud Based RAG System
RAG (Retrieval Augmented Generation) and vector search to translate natural language into SQL queries for PostgreSQL databases.
findthatbit.com + findthatbit.info
Youtube GPT
Chatbot that provides information to tourists using GenAI
We are going to showcase how to build a superhero character AI - where users can chat with their favourite superheroes.
The objective of this project is to create a chatbot that can be used to communicate with users to provide answers to their health issues. This is a RAG implementation using open source stack.
This app allows users to search for products by either entering text or uploading an image, and retrieves relevant products from a database
Parsing PDF, PPT, and Txt documents using LlamaParse, Qdrant, and the Groq model
News Observatory
This project transform the Bug Frameworks papers into embeddings
Tutorials and references to get started with Qdrant vector databases
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