Milvus Adventures Nov 3, 2023
Tags: opensource, openai, tutorial, ai
Published: 2023-11-04 00:56:45

#November 3, 2023

##HACKTOBERFEST
[Hacktoberfest](https://zilliz.com/hacktoberfest) is now over for the year! Thank you so much to everyone who participated!

##COMMUNITY
Join us at one of our Unstructured Data Meetups!

* November 7 - [Seattle Unstructured Meetup](https://www.meetup.com/aittg-seattle/events/296838610/)
* November 14 — [San Francisco Unstructured Meetup](https://lu.ma/nmqqrpbx)

Missed one of our community events? No worries!

* [SF Unstructured Data Meetup](https://www.youtube.com/watch?v=yqaG2XSv89I&list=PLPg7_faNDlT7SC3HxWShxKT-t-u7uKr--) - watch the video
	* Jon Bennion, Logical Fallacies in LLM output
	* Filip Haltmayer, Kafka integration with Zilliz  
	* Rob and Kasia, Pair Programming with GitHub Copilot
	 
* [CalHacks](https://www.calhacks.io/) 🐻🧸— October 27-29 - read the [recap](https://zilliz.com/blog/zilliz-at-calhacks-2023)

##GETTING STARTED WITH VECTOR SEARCH
* [What Is Semantic Search?](https://zilliz.com/glossary/semantic-search)
* [Vector Distance](https://zilliz.com/glossary/vector-distance)
* [What Are AI Hallucinations?](https://zilliz.com/glossary/ai-hallucination)
* [Vector Database 101: Everything You Need to Know](https://zilliz.com/learn/introduction-to-unstructured-data)

##ARTICLES
**LangChain & Milvus**

* NEW [Retrieval Augmented Generation on Notion Docs via LangChain](https://zilliz.com/blog/retrieval-augmented-generation-on-notion-docs-via-langchain)
* [Ultimate Guide to Getting Started with LangChain](https://zilliz.com/blog/langchain-ultimate-guide-getting-started)
* [Question Answering over Documents with Zilliz Cloud and LangChain](https://docs.zilliz.com/docs/question-answering-over-documents-with-zilliz-cloud-and-langchain)

**LlamaIndex & Milvus**

* [Getting Started with LlamaIndex](https://zilliz.com/blog/getting-started-with-llamaindex)
* [Documentation QA using Zilliz Cloud and LlamaIndex ](https://docs.zilliz.com/docs/documentation-qa-using-zilliz-cloud-and-llamaindex)
* [Building a Chatbot with Zilliz Cloud, LlamaIndex and LangChain Part I](https://zilliz.com/blog/chat-towards-data-science-building-chatbot-with-zilliz-cloud)

##TUTORIAL
**Using AI to Find Your Celebrity Stylist**. In this tutorial, you will learn how to utilize a fine-tuned model to segment clothing in images. You will then crop out each labeled article and resize the images to the same size. Finally, store the embeddings generated from those images in Milvus, an open-source vector database.
* [Part ONE](https://zilliz.com/blog/using-ai-to-find-your-celebrity-stylist)
* [Part TWO](https://zilliz.com/blog/use-ai-find-your-celebrity-style-two)

**Build Semantic Search on your ZenDesk tickets.** In this tutorial, you will learn hot to conduct Semantic Search on ZenDesk tickets with Airbyte, Streamlit, and of course Milvus as our vector store. [Start Now.](https://zilliz.com/blog/use-milvus-and-airbyte-for-similarity-search-on-all-your-data)

##VIDEOS
**Vector Database Fundamentalss**

* [ANNOY Vector Index](https://www.youtube.com/watch?v=fhzDrXCpIRQ&list=PLPg7_faNDlT6wXMi2vfG0zJ6pK-gq6KE8)
* [HNSW Vector Index ](https://www.youtube.com/watch?v=v1AiTcwZaRY&list=PLPg7_faNDlT6wXMi2vfG0zJ6pK-gq6KE8&index=2) 
* [IVF Vector Index](https://www.youtube.com/watch?v=VOerTAir9SU&list=PLPg7_faNDlT6wXMi2vfG0zJ6pK-gq6KE8&index=3)


##GITHUB REPOS
**[Milvus Vector Database](https://github.com/milvus-io/milvus)**. 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.

**[GPT Cache.](https://github.com/zilliztech/GPTCache)** 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](https://github.com/zilliztech/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.