openai-cookbook/examples/vector_databases
2023-10-02 11:20:03 -07:00
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analyticdb Fix typo in QA_with_Langchain_AnalyticDB_and_OpenAI.ipynb (#582) 2023-07-12 12:28:14 -07:00
azuresearch Minor change to use SearchIndexingBufferedSender to support optimized batch indexing (#712) 2023-09-26 16:43:05 -07:00
cassandra_astradb new cassIO connect experience with the newest cassio.init (#745) 2023-09-28 18:00:04 -07:00
chroma Update notebooks (#598) 2023-07-24 15:59:33 -07:00
deeplake Add Deep Lake vector database example (#455) 2023-10-02 11:20:03 -07:00
elasticsearch [elasticsearch] fix typo in signup url (#726) 2023-09-27 16:02:50 -07:00
hologres Add Hologres as a vector database with python notebook example (#404) 2023-05-19 11:16:27 -07:00
kusto kusto vector sample added 2023-05-11 11:06:34 +08:00
milvus Zilliz integration and Milvus bugfixes (#259) 2023-03-28 15:36:24 -07:00
myscale Splitting Vector Databases into individual cookbooks (#529) 2023-06-28 01:37:01 -07:00
neon Update Neon cookbook README.md (#747) 2023-09-29 18:22:39 -07:00
pinecone consolidate Embedding.create calls into one (#543) 2023-07-20 20:20:04 -07:00
PolarDB Add getting started with PolarDB vector database and OpenAI example. (#489) 2023-07-11 17:13:26 -07:00
qdrant Refactor Qdrant notebooks (#556) 2023-06-29 07:47:18 -07:00
redis Fix typo in redis-hybrid-query-examples.ipynb (#642) 2023-08-17 03:21:48 -07:00
SingleStoreDB Adding SingleStoreDB as a vector database with Python notebook (#402) 2023-05-22 16:05:50 -07:00
tair Add Tair to examples of vector database (#609) 2023-09-11 15:16:00 -07:00
typesense Splitting Vector Databases into individual cookbooks (#529) 2023-06-28 01:37:01 -07:00
weaviate Splitting Vector Databases into individual cookbooks (#529) 2023-06-28 01:37:01 -07:00
zilliz update to token for zilliz (#552) 2023-06-27 12:53:26 -07:00
README.md Add Neon Postgres to the list of vector databases in the README (#746) 2023-09-29 18:23:01 -07:00

Vector Databases

This section of the OpenAI Cookbook showcases many of the vector databases available to support your semantic search use cases.

Vector databases can be a great accompaniment for knowledge retrieval applications, which reduce hallucinations by providing the LLM with the relevant context to answer questions.

Each provider has their own named directory, with a standard notebook to introduce you to using our API with their product, and any supplementary notebooks they choose to add to showcase their functionality.

Guides & deep dives