Merge branch 'main' into live-api-fc-0115

Author: holtskinner

.git-blame-ignore-revs

@@ -89,3 +89,4 @@ a41f948147f9c16c9b1255038929ab1d1ac07def
 076464885ddf63d57d91cac830ff83f774d5c877
 ca7ceb9f8358a5d79c31d2511f705bcc55c24232
 0538e91f7c69c34174c722ae1ed1552261c8b805
+6ba714a7cf1d8d460f5518e5bf220b76088aec09

.github/actions/spelling/allow.txt

@@ -258,6 +258,7 @@ Kylian
 L'avenir
 LCEL
 LLMs
+LLa
 LMPA
 LOOKBACK
 LRESULT
@@ -509,6 +510,7 @@ Virat
 Viru
 VirusTotal
 WAI
+WAU
 WDIR
 WFH
 WNDCLASS
@@ -759,6 +761,7 @@ funtion
 futur
 gapic
 gauff
+gbif
 gboolean
 gbq
 gce
@@ -919,6 +922,7 @@ millis
 miranda
 mmarco
 mmr
+modelfile
 morty
 moviepy
 mpe

.github/linters/.textlintrc

@@ -3,7 +3,8 @@
       "terminology": {
         "defaultTerms": true, 
         "exclude": [
-          "README" 
+          "README",
+          "VS Code"
         ]
       }
     }

README.md

@@ -3,16 +3,16 @@
 > NOTE: [Gemini 2.0 Flash](https://cloud.google.com/vertex-ai/generative-ai/docs/gemini-v2) has been released! Here are the latest notebooks and demos using the new model:
 >
 > - [Intro to Gemini 2.0 Flash](gemini/getting-started/intro_gemini_2_0_flash.ipynb)
-> - [Intro to Gemini 2.0 Flash REST API](gemini/getting-started/intro_gemini_2_0_flash_rest_api.ipynb)
-> - [Intro to Code Execution](gemini/code-execution/intro_code_execution.ipynb)
-> - [Intro to Multimodal Live API](gemini/multimodal-live-api/intro_multimodal_live_api.ipynb)
 > - [Intro to Multimodal Live API with Gen AI SDK](gemini/multimodal-live-api/intro_multimodal_live_api_genai_sdk.ipynb)
+> - [Intro to Gemini 2.0 Thinking Mode](gemini/getting-started/intro_gemini_2_0_flash_thinking_mode.ipynb)
+> - [Intro to Code Execution](gemini/code-execution/intro_code_execution.ipynb)
 > - [Multimodal Live API Demo App](gemini/multimodal-live-api/websocket-demo-app/)
 > - [Intro to Google Gen AI SDK](gemini/getting-started/intro_genai_sdk.ipynb)
 > - [Real-Time RAG with Multimodal Live API](gemini/multimodal-live-api/real_time_rag_retail_gemini_2_0.ipynb)
 > - [Creating Marketing Assets using Gemini 2.0](gemini/use-cases/marketing/creating_marketing_assets_gemini_2_0.ipynb)
 > - [Vertex AI Gemini Research Multi Agent Demo Research Agent for EV Industry](gemini/agents/research-multi-agents)
 > - [Create a Multi-Speaker Podcast with Gemini 2.0 & Text-to-Speech](audio/speech/use-cases/podcast/multi-speaker-podcast.ipynb)
+> - [Intro to Gemini 2.0 Flash REST API](gemini/getting-started/intro_gemini_2_0_flash_rest_api.ipynb)
 
 <!-- markdownlint-disable MD033 -->
 

RESOURCES.md

@@ -46,6 +46,8 @@ Please submit additional resources via a PR.
 
 ## Video Courses
 
+- [Real Terms for AI](https://goo.gle/AIwordsExplained)
+- [AI Guide for Cloud Developers](https://www.youtube.com/playlist?list=PLIivdWyY5sqJio2yeg1dlfILOUO2FoFRx)
 - [Intro to Gen AI - Playlist](https://www.youtube.com/playlist?list=PLBgogxgQVM9sl-KnKywVEhkb3QtLHU4OK)
   - [Introduction to Generative AI](https://www.youtube.com/watch?v=cZaNf2rA30k&list=PLBgogxgQVM9sl-KnKywVEhkb3QtLHU4OK&index=1&pp=iAQB)
   - [Introduction to Large Language Models](https://www.youtube.com/watch?v=RBzXsQHjptQ&list=PLBgogxgQVM9sl-KnKywVEhkb3QtLHU4OK&index=2&pp=iAQB)

embeddings/README.md

@@ -1,9 +1,22 @@
 # Embeddings
 
+<!-- markdownlint-disable MD036 -->
+
+**YouTube Video: What are text embeddings?**
+
+<!-- markdownlint-enable MD036 -->
+
+<!-- markdownlint-disable MD033 -->
+<a href="https://www.youtube.com/watch?v=vlcQV4j2kTo&list=PLIivdWyY5sqLvGdVLJZh2EMax97_T-OIB" target="_blank">
+  <img src="https://img.youtube.com/vi/vlcQV4j2kTo/maxresdefault.jpg" alt="What are text embeddings?" width="500">
+</a>
+<!-- markdownlint-enable MD033 -->
+
 This repository explores various techniques and use-cases for embedding in Machine Learning, with a particular focus on text embeddings and their applications.
 
 ## Notebooks
 
+- **[generate-embs-for-vvs.ipynb](generate-embs-for-vvs.ipynb):** Demonstrates large-scale embeddings generation for Vertex AI Vector Search.
 - **[hybrid-search.ipynb](hybrid-search.ipynb):** Demonstrates building a hybrid search system leveraging both keyword-based search and semantic similarity search with embeddings.
 - **[embedding-similarity-visualization.ipynb](embedding-similarity-visualization.ipynb):** Visualizes similarity relationships between embeddings using dimensionality reduction techniques like PCA and t-SNE.
 - **[intro-textemb-vectorsearch.ipynb](intro-textemb-vectorsearch.ipynb):** Provides an introduction to text embeddings and their application in building vector search engines.