.Net: docs: fix dead links after planner removal and MEVD code migration

dotnet/samples/Concepts/README.md

@@ -63,7 +63,7 @@ dotnet test -l "console;verbosity=detailed" --filter "FullyQualifiedName=ChatCom
 - [Connectors_WithMultipleLLMs](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Connectors_WithMultipleLLMs.cs)
 - [Google_GeminiChatCompletion](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiChatCompletion.cs)
 - [Google_GeminiChatCompletionStreaming](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiChatCompletionStreaming.cs)
-- [Google_GeminiChatCompletionWithThinkingBudget](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiChatCompletionWithThinkingBudget.cs)
+- [Google_GeminiChatCompletionWithThinking](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiChatCompletionWithThinking.cs)
 - [Google_GeminiChatCompletionWithFile.cs](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiChatCompletionWithFile.cs)
 - [Google_GeminiGetModelResult](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiGetModelResult.cs)
 - [Google_GeminiStructuredOutputs](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/ChatCompletion/Google_GeminiStructuredOutputs.cs)
@@ -143,7 +143,6 @@ dotnet test -l "console;verbosity=detailed" --filter "FullyQualifiedName=ChatCom
 - [TextChunkingAndEmbedding](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/TextChunkingAndEmbedding.cs)
 - [VectorStore_DataIngestion_Simple: A simple example of how to do data ingestion into a vector store when getting started.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_DataIngestion_Simple.cs)
 - [VectorStore_DataIngestion_MultiStore: An example of data ingestion that uses the same code to ingest into multiple vector stores types.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_DataIngestion_MultiStore.cs)
-- [VectorStore_DataIngestion_CustomMapper: An example that shows how to use a custom mapper for when your data model and storage model doesn't match.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_DataIngestion_CustomMapper.cs)
 - [VectorStore_VectorSearch_Simple: A simple example of how to do data ingestion into a vector store and then doing a vector similarity search over the data.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_VectorSearch_Simple.cs)
 - [VectorStore_VectorSearch_Paging: An example showing how to do vector search with paging.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_VectorSearch_Paging.cs)
 - [VectorStore_VectorSearch_MultiVector: An example showing how to pick a target vector when doing vector search on a record that contains multiple vectors.](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Memory/VectorStore_VectorSearch_MultiVector.cs)
@@ -160,12 +159,6 @@ dotnet test -l "console;verbosity=detailed" --filter "FullyQualifiedName=ChatCom
 - [FrugalGPTWithFilters](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Optimization/FrugalGPTWithFilters.cs)
 - [PluginSelectionWithFilters](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Optimization/PluginSelectionWithFilters.cs)
 
-### Planners - Examples on using `Planners`
-
-- [AutoFunctionCallingPlanning](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Planners/AutoFunctionCallingPlanning.cs)
-- [FunctionCallStepwisePlanning](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Planners/FunctionCallStepwisePlanning.cs)
-- [HandlebarsPlanning](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Planners/HandlebarsPlanning.cs)
-
 ### Plugins - Different ways of creating and using [`Plugins`](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Abstractions/Functions/KernelPlugin.cs)
 
 - [ApiManifestBasedPlugins](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/ApiManifestBasedPlugins.cs)
@@ -188,9 +181,6 @@ dotnet test -l "console;verbosity=detailed" --filter "FullyQualifiedName=ChatCom
 - [ImportPluginFromGrpc](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/ImportPluginFromGrpc.cs)
 - [MsGraph_CalendarPlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/MsGraph_CalendarPlugin.cs)
 - [MsGraph_EmailPlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/MsGraph_EmailPlugin.cs)
-- [MsGraph_ContactsPlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/MsGraph_ContactsPlugin.cs)
-- [MsGraph_DrivePlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/MsGraph_DrivePlugin.cs)
-- [MsGraph_TasksPlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/MsGraph_TasksPlugin.cs)
 - [TransformPlugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/TransformPlugin.cs)
 - [CopilotAgentBasedPlugins](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/CopilotAgentBasedPlugins.cs)
 - [WebPlugins](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/Plugins/WebPlugins.cs)
@@ -213,7 +203,6 @@ dotnet test -l "console;verbosity=detailed" --filter "FullyQualifiedName=ChatCom
 
 ### RAG - Retrieval-Augmented Generation
 
-- [WithFunctionCallingStepwisePlanner](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/RAG/WithFunctionCallingStepwisePlanner.cs)
 - [WithPlugins](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/Concepts/RAG/WithPlugins.cs)
 
 ### Search - Search services information

dotnet/samples/Demos/OnnxSimpleRAG/README.md

@@ -13,7 +13,7 @@ In this example we setup two ONNX AI Services:
 
 - [Chat Completion Service](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Abstractions/AI/ChatCompletion/IChatCompletionService.cs) - Using the Chat Completion Service from [Onnx Connector](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/Connectors.Onnx/OnnxRuntimeGenAIChatCompletionService.cs) to generate responses from the Local Model.
 - [Text Embeddings Generation Service]() - Using the Text Embeddings Generation Service from [Onnx Connector](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/Connectors.Onnx/BertOnnxTextEmbeddingGenerationService.cs) to generate
-- [Vector Store](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/VectorData.Abstractions/VectorStorage/IVectorStore.cs) Using Vector Store Service with [InMemoryVectorStore](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/Connectors.Memory.InMemory/InMemoryVectorStore.cs) to store and retrieve embeddings in memory for RAG.
+- [Vector Store](https://github.com/dotnet/extensions/tree/main/src/Libraries/Microsoft.Extensions.VectorData.Abstractions) Using Vector Store Service with [InMemoryVectorStore](https://github.com/CommunityToolkit/AI/blob/main/MEVD/src/InMemory/InMemoryVectorStore.cs) to store and retrieve embeddings in memory for RAG.
 - [Semantic Text Memory](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel.Core/Memory/SemanticTextMemory.cs) to manage the embeddings in memory for RAG.
 - [Text Memory Plugin](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Plugins/Plugins.Memory/TextMemoryPlugin.cs) to enable memory retrieval functions (Recall) to be used with Prompts for RAG.
 

python/samples/concepts/README.md

@@ -225,7 +225,7 @@
 - [Simple Chatbot](./reasoning/simple_reasoning.py)
 - [Simple Function Calling](./reasoning/simple_reasoning_function_calling.py)
 
-### Search - Using [`Search`](https://github.com/microsoft/semantic-kernel/tree/main/python/semantic_kernel/connectors/search) services information
+### Search - Using [`Search`](https://github.com/microsoft/semantic-kernel/blob/main/python/semantic_kernel/connectors/search.py) services information
 
 - [Bing Text Search as Plugin](./search/bing_text_search_as_plugin.py)
 - [Brave Text Search as Plugin](./search/brave_text_search_as_plugin.py)

python/semantic_kernel/connectors/memory_stores/redis/README.md

@@ -2,7 +2,7 @@
 
 This connector uses Redis to implement Semantic Memory. It requires the [RediSearch](https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/) module to be enabled on Redis to implement vector similarity search.
 
-See the [.net README](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/Connectors/Connectors.Memory.Redis/README.md) for more information.
+See the [.net README](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/VectorData/Redis/README.md) for more information.
 
 ## Quick start