Add elasticsearch examples to vector databases folder (#622)

* Add Elasticsearch to vector databases, add notebooks

* Update prompt

* Make intro verbiage more neutral

* Add semantic search notebook outputs

* Add RAG notebook output

* Update query

* Remove unreadable vector output

examples/vector_databases/README.md

@@ -1,6 +1,6 @@
 # Vector Databases
 
-This section of the OpenAI Cookbook showcases many of the vector databases available to support your semantic search use cases. 
+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.
 
@@ -9,6 +9,7 @@ Each provider has their own named directory, with a standard notebook to introdu
 ## Guides & deep dives
 - [AnalyticDB](https://www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/get-started-with-analyticdb-for-postgresql)
 - [Chroma](https://docs.trychroma.com/getting-started)
+- [Elasticsearch](https://www.elastic.co/guide/en/elasticsearch/reference/current/knn-search.html)
 - [Hologres](https://www.alibabacloud.com/help/en/hologres/latest/procedure-to-use-hologres)
 - [Kusto](https://learn.microsoft.com/en-us/azure/data-explorer/web-query-data)
 - [Milvus](https://milvus.io/docs/example_code.md)

examples/vector_databases/elasticsearch/README.md

@@ -0,0 +1,31 @@
+# Elasticsearch
+
+Elasticsearch is a popular search/analytics engine and [vector database](https://www.elastic.co/elasticsearch/vector-database).
+Elasticsearch offers an efficient way to create, store, and search vector embeddings at scale.
+
+For technical details, refer to the [Elasticsearch documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/knn-search.html).
+
+The [`elasticsearch-labs`](https://github.com/elastic/elasticsearch-labs) repo contains executable Python notebooks, sample apps, and resources for testing out the Elastic platform.
+
+## OpenAI cookbook notebooks 📒
+
+Check out our notebooks in this repo for working with OpenAI, using Elasticsearch as your vector database.
+
+### [Semantic search](https://github.com/openai/openai-cookbook/blob/main/examples/vector_databases/elasticsearch/elasticsearch-semantic-search.ipynb)
+
+In this notebook you'll learn how to:
+
+ - Index the OpenAI Wikipedia embeddings dataset into Elasticsearch
+ - Encode a question with the `openai ada-02` model
+ - Perform a semantic search
+
+<hr>
+
+
+### [Retrieval augmented generation](https://github.com/openai/openai-cookbook/blob/main/examples/vector_databases/elasticsearch/elasticsearch-retrieval-augmented-generation.ipynb)
+
+This notebooks builds on the semantic search notebook by:
+
+- Selecting the top hit from a semantic search
+- Sending that result to the OpenAI [Chat Completions](https://platform.openai.com/docs/guides/gpt/chat-completions-api) API endpoint for retrieval augmented generation (RAG)
+