2024 is here so join us at our next one in San Francisco is on Jan 16, 2024. Please register early because they fill up fast! There are already 245 people registered! We will be joined by
- Christy Bergman, Developer Advocate, Zilliz, Vector Search in the Age of OpenAI Assistants using Milvus
- George Williams, Organizer, Big-ANN NeurIPS 2023, Are CPUs Enough? A Review Of Vector Search Running On Novel Hardware
- 3rd speaker to be announced next week
Open Source Advent d(⌒ー⌒)
We wrapped up the Open Source Advent by showcasing different open source projects in December. People got a chance to check out the projects and earned points for a chance to win an exclusive swag pack from Zilliz and the participating projects! We will be announcing the winners next week! I created 2 blogs that list out all the projects here (First 15 and Final).
ARTICLES To check out ໒(＾ᴥ＾)७
- OpenAI RAG vs. Your Customized RAG: Which One Is Better?
- Optimizing RAG Applications: A Guide to Methodologies, Metrics, and Evaluation Tools for Enhanced Reliability
Vector Search & NLP
Getting Started with a Milvus Connection
Milvus has four SDKs: Go, Java, Python, React, and Ruby. In this blog, we’ll show steps for Python.
Building an Open Source Chatbot Using LangChain and Milvus in Under 5 Minutes
This tutorial uses a completely open-source RAG (Retrieval Augmented Generation) stack with LangChain to answer questions about Milvus using our product documentation web pages.
Metadata Filtering with Zilliz Cloud Pipelines
This tutorial discuss scalar or metadata filtering and how you can perform metadata filtering in Zilliz Cloud. This blog continues on the previous blog on Getting started with RAG in just 5 minutes. You can find its code in this notebook and scroll down to Cell #27.
- Evaluation Builds Better Retrieval Augmented Generation Applications
- Effective RAG: Generate and Evaluate High-Quality Content for Your LLMs
- RAG Evals: Statistical Analysis of Retrieval Strategies with Arize
GITHUB REPOS ᕙ(‾̀◡‾́)ᕗ
Milvus Vector Database. Milvus is an open source vector database used to store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models.
Akcio: Enhancing LLM-Powered ChatBot with CVP Stack A full chatbot app all open-source for you to try out for your self!
GPT Cache. GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.
VectorDBBench. VectorDBBench is an open-source benchmarking tool to help you evaluate the performance of mainstream vector databases and cloud services with yoru specific use case.