Merge pull request #167 from haileytap/agentic-retrieval

Update README

Author: haileytap

README.md

@@ -11,7 +11,7 @@ If your configuration uses a search service managed identity for indexer connect
 | [Quickstart](Quickstart/README.md) | Introduces the fundamental tasks of working with a classic search index: create, load, and query. The index is modeled on a subset of the hotels dataset, which is widely used in Azure AI Search samples but reduced in this sample for readability and comprehension. |
 | [Quickstart-Agentic-Retrieval](Quickstart-Agentic-Retrieval/quickstart-agentic-retrieval.ipynb) | Create a knowledge base in Azure AI Search to integrate LLM reasoning into query planning. |
 | [Quickstart-Document-Permissions-Pull-API](Quickstart-Document-Permissions-Pull-API/document-permissions-pull-api.ipynb) | Using an indexer "pull API" approach, flow access control lists from a data source to search results and apply permission filters that restrict access to authorized content. Indexer support is limited to Azure Data Lake Storage (ADLS) Gen2 permission metadata. |
-| [Quickstart-Document-Permissions-Push-API](Quickstart-Document-Permissions-Push-API/document-permissions-push-api.ipynb) | Using the push APIs for indexing a JSON payload, flow embedded permission metadata to indexed documents, and to search results that are filtered based on user access to authorized content. |
+| [Quickstart-Document-Permissions-Push-API](Quickstart-Document-Permissions-Push-API/document-permissions-push-api.ipynb) | Using the push APIs for indexing a JSON payload, flow embedded permission metadata to indexed documents and search results that are filtered based on user access to authorized content. |
 | [Quickstart-RAG](Quickstart-RAG/quickstart-rag.ipynb) | Introduces LLM integration with a chat model, such as GPT-3.5-turbo or an equivalent model. |
 | [Quickstart-Semantic-Search](Quickstart-Semantic-Search/semantic-search-quickstart.ipynb) | Extends the quickstart through modifications that invoke semantic ranking. This notebook adds a semantic configuration to the index and semantic query options that formulate the query and response. |
 | [Quickstart-Vector-Search](Quickstart-Vector-Search/quickstart-vector-search.ipynb) | Introduces vector search in Azure AI Search. This notebook demonstrates how to create, load, and query a vector index. |