Integrations

Still do not know how to integrate great open-source and third-party services with Zilliz Cloud? Use these guides to start with.

With OpenAI [READ MORE]

This page discusses integrating vector databases with OpenAI's embedding API.

With HuggingFace [READ MORE]

This page illustrates how to build a question-answering system using Zilliz Cloud as the vector database and Hugging Face as the embedding system.

With Cohere [READ MORE]

This page illustrates how to create a question-answering system based on the SQuAD dataset using Zilliz Cloud as the vector database and Cohere as the embedding system.

With LangChain [READ MORE]

This guide demonstrates how to build an LLM-driven question-answering application using Zilliz Cloud and LangChain.

With PyTorch [READ MORE]

On this page, we are going to go over a simple image search example using Zilliz Cloud. The dataset we are searching through is the Impressionist-Classifier Dataset found on Kaggle. For this example, we have re-hosted the data in a public google drive.

With LlamaIndex [READ MORE]

This guide demonstrates how to build a Retrieval-Augmented Generation (RAG) system using LlamaIndex and Milvus.

With SentenceTransformers [READ MORE]

In this example, we are going to go over a Wikipedia article search using Zilliz Cloud and the SentenceTransformers library. The dataset we will search through is the Wikipedia-Movie-Plots Dataset found on Kaggle. For this example, we have re-hosted the data in a public Google drive.