This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!
Interactive notes (Jupyter Notebooks) for building AI-powered applications
A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.
Jupyeter Notebooks that demo Generative AI concepts
Perform RAG (Retrieval-Augmented Generation) from your PDFs using this Colab notebook! Powered by Llama 2
Question-Answering with RAG and local LLMs over your Jupyter Notebooks
In this notebook combines LangChain and weaviate Database to ask questions related to your document. Powered by OpenAI's GPT-3.
Collection of Jupyter Notebooks related to Generative AI.
Notebooks supporting the activities for generative AI 102 Startup loft.
Machine Learning, LLM and other Jupyter Notebooks and resources
This notebook showcases a prototype for a retrieval-augmented generation approach in question-answering. The implementation includes demonstrations using an offline language model (LLM) from Hugging Face and the OpenAI GPT-3.5 API.
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