add cloud gen ai examples (#67)

modules/genai-ecosystem/nav.adoc

@@ -1,4 +1,8 @@
 ** xref:index.adoc[GenAI Ecosystem]
+*** Cloud Examples
+**** xref:aws-demo.adoc[AWS Demo]
+**** xref:microsoft-azure-demo.adoc[Microsoft Azure Demo]
+**** xref:google-cloud-demo.adoc[Google Cloud Demo]
 *** Example Projects
 **** xref:rag-demo.adoc[GraphRAG Demo]
 **** xref:genai-stack.adoc[GenAI Stack]

modules/genai-ecosystem/pages/aws-demo.adoc

@@ -0,0 +1,38 @@
+= AWS Demo
+include::_graphacademy_llm.adoc[]
+:slug: aws-demo
+:author: Ben Lackey
+:category: genai-ecosystem
+:tags: rag, demo, retrieval augmented generation, chatbot, edgar, sec filings, aws, bedrock
+:neo4j-versions: 5.x
+:page-pagination:
+:page-product: aws-demo
+
+This is a sample notebook and web application which shows how Amazon Bedrock and Titan can be used with Neo4j. It shows how to leverage generative AI to build and consume a knowledge graph in Neo4j.
+
+The dataset we're using is from the SEC's EDGAR system.
+
+The dataflow in this demo consists of two parts:
+
+* Ingestion - we read the EDGAR files with Bedrock, extracting entities and relationships from them which is then ingested into a Neo4j database deployed from AWS Marketplace.
+* Consumption - A user inputs natural language into a chat UI. Bedrock converts that to Neo4j Cypher which is run against the database. This flow allows non technical users to query the database.
+
+== Installation
+
+The Demo is available on GitHub: https://github.com/neo4j-partners/neo4j-generative-ai-aws
+
+== Relevant Links
+[cols="1,4"]
+|===
+| icon:github[] Code Repository | https://github.com/neo4j-partners/neo4j-generative-ai-aws[GitHub]
+| APN Blog Post | https://aws.amazon.com/blogs/apn/leveraging-neo4j-and-amazon-bedrock-for-an-explainable-secure-and-connected-generative-ai-solution[Link]
+| Demo Video | https://www.youtube.com/watch?v=nV3-KKEZnD4&list=PLG3nTnYVz3nya8Me9-Xj9vEuLYIOk03ba&index=11&t=14s[Link]
+| Press Release | https://neo4j.com/press-releases/neo4j-aws-bedrock-integration[Link]
+| Slides | https://docs.google.com/presentation/d/1pnJn1GV7tm6Gr-K-0bEB5TlkPRoDbqLTKkKjWdr3eZs/edit?usp=sharing[Link]
+|===
+
+== Videos & Tutorials
+
+++++
+<iframe width="640" height="480" src="https://www.youtube.com/embed/nV3-KKEZnD4" frameborder="0" allow="accelerometer; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+++++

modules/genai-ecosystem/pages/google-cloud-demo.adoc

@@ -0,0 +1,34 @@
+= Google Cloud Demo
+include::_graphacademy_llm.adoc[]
+:slug: google-cloud-demo
+:author: Ben Lackey
+:category: genai-ecosystem
+:tags: rag, demo, retrieval augmented generation, chatbot, google, vertexai
+:neo4j-versions: 5.x
+:page-pagination:
+:page-product: google-cloud-demo
+
+This example consists of two sample applications that show how to use Neo4j with the generative AI capabilities in Google Cloud Vertex AI. We explore how to leverage Google generative AI to build and consume a knowledge graph in Neo4j.
+
+* assetmanager - Parses data from the SEC containing quarterly filings of asset managers. We build a graph containing assets managers and the securities they hold. A chatbot that queries the knowledge graph is included as well.
+* resume - Extracts entities like jobs and skills from a collection of resumes, then builds a graphs showing what talents individuals share. A chatbot that queries the knowledge graph is included as well.
+
+== Installation
+
+The Demo is available on GitHub: https://github.com/neo4j-partners/neo4j-generative-ai-google-cloud
+
+== Relevant Links
+[cols="1,4"]
+|===
+| icon:github[] Code Repository | https://github.com/neo4j-partners/neo4j-generative-ai-google-cloud[GitHub]
+| Blog Post | https://cloud.google.com/blog/topics/partners/build-intelligent-apps-with-neo4j-and-google-generative-ai[Link]
+| Demo Video | https://www.youtube.com/watch?v=UGWVMfo5Pew[Link]
+| Slides | https://docs.google.com/presentation/d/1vIXaZCWX5fN5m6y50Z7nM6RlTSJR7vErUrfXlWR0BLY/edit?usp=sharing[Link]
+| Press Release | https://neo4j.com/press-releases/neo4j-google-cloud-vertex-ai[Link]
+|===
+
+== Videos & Tutorials
+
+++++
+<iframe width="640" height="480" src="https://www.youtube.com/embed/UGWVMfo5Pew" frameborder="0" allow="accelerometer; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+++++

modules/genai-ecosystem/pages/index.adoc

@@ -29,6 +29,12 @@ image::https://cdn.graphacademy.neo4j.com/assets/img/courses/banners/llm-fundame
 
 == GenAI Ecosystem
 
+=== Cloud Examples
+
+* xref:aws-demo.adoc[AWS Demo]
+* xref:microsoft-azure-demo.adoc[Microsoft Azure Demo]
+* xref:google-cloud-demo.adoc[Google Cloud Demo]
+
 === Example Projects
 
 * xref:rag-demo.adoc[RAG (Retrieval Augmented Generation) Demo]

modules/genai-ecosystem/pages/microsoft-azure-demo.adoc

@@ -0,0 +1,33 @@
+= Microsoft Azure Demo
+include::_graphacademy_llm.adoc[]
+:slug: microsoft-azure-demo
+:author: Ben Lackey
+:category: genai-ecosystem
+:tags: rag, demo, retrieval augmented generation, chatbot, edgar, sec filings, azure, openai
+:neo4j-versions: 5.x
+:page-pagination:
+:page-product: microsoft-azure-demo
+
+This is a sample notebook and web application which shows how Azure OpenAI can be used with Neo4j. We will explore how to leverage Azure OpenAI LLMs to build and consume a knowledge graph in Neo4j.
+
+This notebook parses data from a public corpus of Medical Case Sheet using Azure OpenAI's gpt-4-32k model. The model is prompted to recognise and extract entities and relationships.
+
+We then use the gpt-4-32k model and prompt it to convert questions in English to Cypher - Neo4j's query language for data retrieval.
+
+== Installation
+
+The Demo is available on GitHub: https://github.com/neo4j-partners/neo4j-generative-ai-azure
+
+== Relevant Links
+[cols="1,4"]
+|===
+| icon:github[] Code Repository | https://github.com/neo4j-partners/neo4j-generative-ai-azure[GitHub]
+| Demo Video | https://www.youtube.com/watch?v=3PO-erAP6R4&list=PLG3nTnYVz3nya8Me9-Xj9vEuLYIOk03ba[Link]
+| Slides | https://docs.google.com/presentation/d/16KtVfpRoQWoUTY9UAK7fDBm-ZTCG7NrT0VCSa5brmLY/edit?usp=sharing[Link]
+|===
+
+== Videos & Tutorials
+
+++++
+<iframe width="640" height="480" src="https://www.youtube.com/embed/3PO-erAP6R4" frameborder="0" allow="accelerometer; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+++++