Milvus Adventures
Tags: opensource, vectordatabase, rust, milvus
Published: 2023-10-21 01:29:40

#October 20, 2023

##HACKTOBERFEST
[Hacktoberfest](https://zilliz.com/hacktoberfest) is still happening and we recently added a few more [first issues](https://github.com/milvus-io/milvus/issues?q=is%3Aopen+is%3Aissue+label%3AHacktoberfest) for anyone from the Rust community!

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

* October 24 — [San Francisco Unstructured Meetup](https://lu.ma/b3rhkle8)
* October 25 - [SF AI For Developers Meetup](https://www.meetup.com/ai-user-group/events/295810042/)
* November 7 - Seattle Unstructure Meetup
* November 14 — [San Francisco Unstructured Meetup](https://lu.ma/nmqqrpbx)

Build something cool with Milvus at one of these Hackathons we are supporting!

* [CalHacks](https://www.calhacks.io/) 🐻🧸— October 27-29
* [HackNC](https://hacknc.com/) 👻 — October 28-29

##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)

##ARTICLES
**LangChain & Milvus**

* [Using LangChain to Self-Query a Vector Database](https://zilliz.com/blog/using-langchain-to-self-query-vector-database)
* [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
**LangChain & Milvus**

* [Memory for LLM applications: Different retrieval techniques for getting the most relevant context](https://zilliz.com/event/memory-for-llm-applications-webinar)
* [How to Add Conversational Memory to an LLM Using LangChain
](https://www.youtube.com/watch?v=m3WwttSBDvo)* [Debugging your RAG apps with LangSmith
](https://zilliz.com/event/llm-app-building-langchain)

**LlamaIndex & Milvus**

* [Persistent Vector Storage with LlamaIndex](https://www.youtube.com/watch?v=S4GmdrlqVKc)
* [Jerry Liu, CEO LlamaIndex tells you how to Boost your LLM with Private Data using LlamaIndex](https://zilliz.com/event/boost-your-llm-with-private-data-using-llamaindex)

##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.