DA-463 Add Nvidia NIM RAG Tutorial (#31)

* add tutorial for gemini vector search chat app

* update LangChain embedding model link in PDF Chat tutorial and added images

* update git url

* Update tutorial/markdown/python/gemini-langchain-pdf-chat/gemini-langchain-pdf-chat-py.md

Co-authored-by: Nithish Raghunandanan <12782505+nithishr@users.noreply.github.com>

* update formatting issue in gemini tutorial

* add nvidia nim rag tutorial

* remove part where we talk about llm without rag

---------

Co-authored-by: Nithish Raghunandanan <12782505+nithishr@users.noreply.github.com>

Author: lokeshgoel177

test/test-markdown-frontmatter.js

@@ -6,7 +6,7 @@ const chalk = require('chalk')
 // accepted data field values
 const sdk_languages = ['nodejs', 'scala', 'python', 'swift', 'csharp', 'objective-c', 'android-java', 'any', 'java', 'kotlin', 'dart', 'golang']
 
-const tags = ['Ottoman', 'Ktor', 'REST API', 'Express', 'Flask', 'TLS', 'Configuration', 'Next.js', 'iOS', 'Xcode', '.NET', 'Xamarin', 'Authentication', 'OpenID', 'Keycloak', 'Android', 'P2P', 'UIKit', 'Installation', 'Spring Boot', 'Spring Data', 'Transactions', 'SQL++ (N1QL)', 'Optimization', 'Community Edition', 'Docker', 'Data Modeling', 'Metadata', 'Best Practices', 'Data Ingestion', 'Kafka', 'Support', 'Customer', 'Prometheus', 'Monitoring', 'Observability', 'Metrics', 'Query Workbench', 'ASP.NET', 'linq', 'DBaaS', 'App Services', 'Flutter', 'Gin Gonic', 'FastAPI', 'LangChain', "OpenAI", "Streamlit", 'Google Gemini']
+const tags = ['Ottoman', 'Ktor', 'REST API', 'Express', 'Flask', 'TLS', 'Configuration', 'Next.js', 'iOS', 'Xcode', '.NET', 'Xamarin', 'Authentication', 'OpenID', 'Keycloak', 'Android', 'P2P', 'UIKit', 'Installation', 'Spring Boot', 'Spring Data', 'Transactions', 'SQL++ (N1QL)', 'Optimization', 'Community Edition', 'Docker', 'Data Modeling', 'Metadata', 'Best Practices', 'Data Ingestion', 'Kafka', 'Support', 'Customer', 'Prometheus', 'Monitoring', 'Observability', 'Metrics', 'Query Workbench', 'ASP.NET', 'linq', 'DBaaS', 'App Services', 'Flutter', 'Gin Gonic', 'FastAPI', 'LangChain', "OpenAI", "Streamlit", 'Google Gemini', 'Nvidia NIM', 'LLama3']
 
 const technologies = ['connectors', 'kv', 'query', 'capella', 'server', 'index', 'mobile', 'fts', 'sync gateway', 'eventing', 'analytics', 'udf']
 

tutorial/markdown/python/gemini-langchain-pdf-chat/gemini-langchain-pdf-chat-py.md

@@ -1,6 +1,6 @@
 ---
 # frontmatter
-path: "/tutorial-python-langchain-pdf-chat"
+path: "/tutorial-gemini-langchain-pdf-chat"
 # title and description do not need to be added to markdown, start with H2 (##)
 title: Build PDF Chat App With Google Gemini and Couchbase Python SDK
 short_title: PDF Chat App with Gemini
@@ -100,7 +100,7 @@ You may also create a vector index using Search UI on both [Couchbase Capella](h
 
 #### Index Definition
 
-Here, we are creating the index `pdf_search` on the documents. The Vector field is set to `embedding` with 1536 dimensions and the text field set to `text`. We are also indexing and storing all the fields under `metadata` in the document as a dynamic mapping to account for varying document structures. The similarity metric is set to `dot_product`. If there is a change in these parameters, please adapt the index accordingly.
+Here, we are creating the index `pdf_search` on the documents. The Vector field is set to `embedding` with 768 dimensions and the text field set to `text`. We are also indexing and storing all the fields under `metadata` in the document as a dynamic mapping to account for varying document structures. The similarity metric is set to `dot_product`. If there is a change in these parameters, please adapt the index accordingly.
 
 ```json
 {
@@ -326,7 +326,7 @@ We will also initialize Couchbase vector store with Couchbase bucket info. First
 We will define the bucket, scope, collection and index names from [Environment Variables](#setup-environment-config).
 
 ```python
-# Use Google Generative AI Embeddings Embeddings
+# Use Google Generative AI Embeddings
 embedding = GoogleGenerativeAIEmbeddings(
     model="models/text-embedding-004",
 )