From 27766e15c37d0e7ab6f4232fa65a0489bdc24601 Mon Sep 17 00:00:00 2001 From: James Briggs <35938317+jamescalam@users.noreply.github.com> Date: Fri, 24 Mar 2023 23:41:58 +0700 Subject: [PATCH] add pinecone readme --- examples/vector_databases/pinecone/README.md | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 examples/vector_databases/pinecone/README.md diff --git a/examples/vector_databases/pinecone/README.md b/examples/vector_databases/pinecone/README.md new file mode 100644 index 00000000..3f65c2f4 --- /dev/null +++ b/examples/vector_databases/pinecone/README.md @@ -0,0 +1,13 @@ +# Pinecone Vector Database + +[Vector search](https://www.pinecone.io/learn/vector-search-basics/) is an innovative technology that enables developers and engineers to efficiently store, search, and recommend information by representing complex data as mathematical vectors. By comparing the similarities between these vectors, you can quickly retrieve relevant information in a seamless and intuitive manner. + +[Pinecone](https://pinecone.io/) is a [vector database](https://www.pinecone.io/learn/vector-database/) designed with developers and engineers in mind. As a managed service, it alleviates the burden of maintenance and engineering, allowing you to focus on extracting valuable insights from your data. The free tier supports up to 5 million vectors, making it an accessible and cost-effective way to experiment with vector search capabilities. With Pinecone, you'll experience impressive speed, accuracy, and scalability, as well as access to advanced features like single-stage metadata filtering and the cutting-edge sparse-dense index. + +## Examples + +This folder contains examples of using Pinecone and OpenAI together. More will be added over time so check back for updates! + +| Name | Description | lanugage | Google Colab | +| --- | --- | --- | --- | +| [Generative Question-Answering](./Gen_QA.ipynb) | A simple walkthrough demonstrating the use of Generative Question-Answering | \ No newline at end of file