move to 3p integrations

.github/scripts/spellcheck_conf/wordlist.txt

@@ -1451,3 +1451,8 @@ openhathi
 sarvam
 subtask
 acc
+CrowdStrike
+builtins
+cybersecurity
+wordlwide
+builtins

recipes/use_cases/README.md

@@ -17,7 +17,4 @@ This step-by-step tutorial shows how to use the [Messenger Platform](https://dev
 A complete example of how to build a Llama 3 chatbot hosted on your browser that can answer questions based on your own data using retrieval augmented generation (RAG). You can run Llama2 locally if you have a good enough GPU or on OctoAI if you follow the note [here](../README.md#octoai_note).
 
 ## [Sales Bot](./customerservice_chatbots/ai_agent_chatbot/SalesBot.ipynb): Sales Bot with Llama3 - A Summarization and RAG Use Case
-An summarization + RAG use case built around the Amazon product review Kaggle dataset to build a helpful Music Store Sales Bot. The summarization and RAG are built on top of Llama models hosted on OctoAI, and the vector database is hosted on Weaviate Cloud Services.
-
-## [Llama3.1 Built-in Tool Calling](./tool_calling/builtins/llama31_tools.ipynb): Use Llama3.1 to invoke Brave Search, Code Interpreter or Wolfram Alpha
-An example that showcases how Llama3.1 can invoke built-in tools to excel at tasks that require complex mathematical reasoning, or need additional context that can be retrieved via a web search.
+An summarization + RAG use case built around the Amazon product review Kaggle dataset to build a helpful Music Store Sales Bot. The summarization and RAG are built on top of Llama models hosted on OctoAI, and the vector database is hosted on Weaviate Cloud Services.