Updated JDBC driver, update to vector database page, partner highlight blog

_artifacts/opensearch-drivers/opensearch-jdbc-1.3.0.0.markdown

@@ -0,0 +1,12 @@
+---
+role: driver
+artifact_id: opensearch-sql-jdbc
+version: 1.3.0.0
+platform: java
+architecture: jvm
+artifact_url: https://artifacts.opensearch.org/opensearch-clients/jdbc/opensearch-sql-jdbc-1.3.0.0-shadow.jar
+slug: opensearch-sql-jdbc-1.3.0.0
+category: opensearch
+type: jar
+jarsigner: true
+---

_layouts/versions.html

@@ -249,6 +249,13 @@ <h4 class="instruction-label">
               {% endcapture %}
               {% assign artifact_extras = artifact_extras | append: artifact_extra %}
             {% endif %}
+            {% if details.jarsigner %}
+              {% capture artifact_extra %}
+                <div class="extra_links extra_{{artifact_id}}">
+                <a href="/verify-signatures.html#JarSigner">Signature verification how to</a></div>
+              {% endcapture %}
+              {% assign artifact_extras = artifact_extras | append: artifact_extra %}
+            {% endif %}
             {% assign artifact_extra = nil %}
           {% endfor %}
         {%endfor%}

_posts/2023-06-26-exploring-opensearch-vector-database-capabilities.md

@@ -0,0 +1,16 @@
+---
+layout: post
+title:  "Partner highlight: Exploring OpenSearch’s vector database capabilities"
+authors:
+- jhmcintyre
+date: 2023-06-29
+categories:
+ - partner-highlight
+meta_keywords: vector database, opensearch, semantic search, retrieval augmented generation, large language model, LLM, AI
+meta_description: Learn about the vector database capabilities built into OpenSearch and explore how Amazon OpenSearch Service can be used to implement semantic search, recommendation engines, and more.
+
+---
+
+Many organizations are turning to machine learning (ML) tools to enhance their search applications. Among those tools are ML embedding models, which can encode the meaning and context of documents, images, and audio into vectors. Those vectors can be stored and indexed within a [vector database](https://opensearch.org/platform/search/vector-database.html), then searched to identify similarities. Ultimately, this functionality can be used to augment search with artificial intelligence.
+
+ In a [recent blog post](https://aws.amazon.com/blogs/big-data/amazon-opensearch-services-vector-database-capabilities-explained/), OpenSearch partner and contributor [Amazon Web Services](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/gsg.html) takes an in-depth look at the vector database capabilities built into OpenSearch and explores how Amazon OpenSearch Service can be used to implement semantic search, Retrieval Augmented Generation (RAG) with large language models (LLMs), recommendation engines, and search rich media. [Take a look](https://aws.amazon.com/blogs/big-data/amazon-opensearch-services-vector-database-capabilities-explained/).

_versions/2023-06-06-opensearch-2.8.0.markdown

@@ -34,7 +34,7 @@ components:
     version: 1.1.0.1
   - role: drivers
     artifact: opensearch-sql-jdbc
-    version: 1.1.0.1
+    version: 1.3.0.0
 sections:
   docker-compose:
     explanation: "downloads/opensearch-docker.markdown"

platform/search/vector-database.html

@@ -105,7 +105,8 @@ <h3>Blog Posts</h3>
             <ul>
                 <li><a href="https://medium.com/@shankar.arunp/augmenting-large-language-models-with-verified-information-sources-leveraging-aws-sagemaker-and-f6be17fb10a8" target="_blank">Augmenting Large Language Models with Verified Information Sources</a></li>
                 <li><a href="/blog/semantic-science-benchmarks/">The ABCs of semantic search in OpenSearch</a></li>
-                <li><a href="https://www.stratusgrid.com/open-space/augmenting-chatgpt-with-amazon-opensearch?locale=en" target="_blank">Augmenting ChatGPT with Amazon OpenSearch</a></li> 
+                <li><a href="https://www.stratusgrid.com/open-space/augmenting-chatgpt-with-amazon-opensearch?locale=en" target="_blank">Augmenting ChatGPT with Amazon OpenSearch</a></li>
+                <li><a href="https://aws.amazon.com/blogs/big-data/amazon-opensearch-services-vector-database-capabilities-explained/?locale=en" target="_blank">Amazon OpenSearch Service’s vector database capabilities explained</a></li>
                 <li><a href="https://aws.amazon.com/blogs/machine-learning/build-a-powerful-question-answering-bot-with-amazon-sagemaker-amazon-opensearch-service-streamlit-and-langchain/" target="_blank">Build a powerful question answering bot</a></li>
                 <li><a href="https://aws.amazon.com/blogs/machine-learning/implement-unified-text-and-image-search-with-a-clip-model-using-amazon-sagemaker-and-amazon-opensearch-service/" target="_blank">Implement unified text and image search with a CLIP model</a></li>
                 <li><a href="https://aws.amazon.com/blogs/machine-learning/building-an-nlu-powered-search-application-with-amazon-sagemaker-and-the-amazon-es-knn-feature/" target="_blank">Building an NLU-powered search application with Amazon SageMaker and the Amazon OpenSearch Service</a></li>

verify-signatures.markdown

@@ -6,6 +6,7 @@ title: How to verify signatures
 
 ## How to verify signatures for downloadable artifacts
 
+### PGP
 Download our PGP key using the link below and import it. 
 
 If you’re using gpg, you just need to run: 
@@ -28,6 +29,13 @@ Our current PGP key fingerprint is `C5B7 4989 65EF D1C2 924B  A9D5 39D3 1987 931
 
 *Note: If you see "gpg: Note: This key has expired!" as originally noted in [Issue 2040](https://github.com/opensearch-project/opensearch-build/issues/2040){:target="_blank"}, please download the newest key. See change log for dates.*
 
+### <a name="JarSigner">JarSigner</a>
+Only the JDBC driver is signed with JarSigner.
+To verify signature run in the terminal:
+```
+jarsigner -verify -verbose <path_to_jar>
+```
+
 ## Change Log ##
 
 <div class="table-styler"></div>
@@ -36,5 +44,6 @@ Our current PGP key fingerprint is `C5B7 4989 65EF D1C2 924B  A9D5 39D3 1987 931
 |:-------------|:-------|:----------------|:----------------|
 | 2022-05-11  | [Issue 2040](https://github.com/opensearch-project/opensearch-build/issues/2040){:target="_blank"}  | 2022-05-12 | 2023-05-12 |
 | 2023-05-04  | [Issue 2136](https://github.com/opensearch-project/opensearch-build/issues/2136){:target="_blank"}  | 2023-05-03 | 2024-05-12 |
+| 2023-06-21  | [Issue 97](https://github.com/opensearch-project/sql-jdbc/issues/97){:target="_blank"}  | 2023-04-13 | 2031-11-09 |
 
 <br>