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openai-cookbook/examples/vector_databases/weaviate
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colin-openai 497c145cc0 Splitting Vector Databases into individual cookbooks (#529) 
* Initial commit of vector database cookbooks split out individually

* Moved notebooks to each provider's named folder and updated the README

* Removed vector DB overall cookbook in favour of individual directories
2023-06-28 01:37:01 -07:00
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docker-compose.yml Merging Weaviate notebooks to main (#122) 2023-02-13 10:33:00 -08:00
generative-search-with-weaviate-and-openai.ipynb Add Generative Search to Weaviate examples + fix authentication examples (#398) 2023-05-22 16:02:28 -07:00
getting-started-with-weaviate-and-openai.ipynb Add Generative Search to Weaviate examples + fix authentication examples (#398) 2023-05-22 16:02:28 -07:00
hybrid-search-with-weaviate-and-openai.ipynb Add Generative Search to Weaviate examples + fix authentication examples (#398) 2023-05-22 16:02:28 -07:00
question-answering-with-weaviate-and-openai.ipynb Add Generative Search to Weaviate examples + fix authentication examples (#398) 2023-05-22 16:02:28 -07:00
README.md Merging Weaviate notebooks to main (#122) 2023-02-13 10:33:00 -08:00
Using_Weaviate_for_embeddings_search.ipynb Splitting Vector Databases into individual cookbooks (#529) 2023-06-28 01:37:01 -07:00

README.md

Weaviate <> OpenAI

​Weaviate is an open-source vector search engine (docs - Github) that can store and search through OpenAI embeddings and data objects. The database allows you to do similarity search, hybrid search (the combining of multiple search techniques, such as keyword-based and vector search), and generative search (like Q&A). Weaviate also supports a wide variety of OpenAI-based modules (e.g., text2vec-openai, qna-openai), allowing you to vectorize and query data fast and efficiently.

You can run Weaviate (including the OpenAI modules if desired) in three ways:

  1. Open source inside a Docker-container (example)
  2. Using the Weaviate Cloud Service (get started)
  3. In a Kubernetes cluster (learn more)

Examples

This folder contains a variety of Weaviate and OpenAI examples.

Name Description lanugage Google Colab
Getting Started with Weaviate and OpenAI A simple getting started for semantic vector search using the OpenAI vectorization module in Weaviate (text2vec-openai) Python Notebook link
Hybrid Search with Weaviate and OpenAI A simple getting started for hybrid search using the OpenAI vectorization module in Weaviate (text2vec-openai) Python Notebook link
Question Answering with Weaviate and OpenAI A simple getting started for question answering (Q&A) using the OpenAI Q&A module in Weaviate (qna-openai) Python Notebook link
Docker-compose example A Docker-compose file with all OpenAI modules enabled Docker