diff --git a/App/kernel-memory/README.md b/App/kernel-memory/README.md index 51ed37cc..103e0d86 100644 --- a/App/kernel-memory/README.md +++ b/App/kernel-memory/README.md @@ -41,7 +41,7 @@ class instance in .NET backend/console/desktop apps in synchronous mode. This ap works as well as in ASP.NET Web APIs and Azure Functions. Each request is processed immediately, although calling clients are responsible for handling transient errors. -![image](docs/infra-sync.png) +![image](https://github.com/microsoft/kernel-memory/blob/main/docs/infra-sync.png?raw=true) > ### Importing documents into your Kernel Memory can be as simple as this: > @@ -114,7 +114,7 @@ search and retrieval through faceted navigation. Depending on your scenarios, you might want to run all the code **locally inside your process, or remotely through an asynchronous and scalable service.** -![image](docs/infra-async.png) +![image](https://github.com/microsoft/kernel-memory/blob/main/docs/infra-async.png?raw=true) If you're importing small files, and need only C# and can block the process during the import, local-in-process execution can be fine, using @@ -252,7 +252,7 @@ on macOS/Linux: > } > ``` -You can find a [full example here](examples/001-dotnet-WebClient/README.md). +You can find a [full example here](https://github.com/microsoft/kernel-memory/blob/main/examples/001-dotnet-WebClient/README.md). # Custom memory ingestion pipelines @@ -289,34 +289,34 @@ running the service locally with OpenAPI enabled. ## Examples -1. [Collection of Jupyter notebooks with various scenarios](examples/000-notebooks) -2. [Using Kernel Memory web service to upload documents and answer questions](examples/001-dotnet-WebClient) -3. [Importing files and asking question without running the service (serverless mode)](examples/002-dotnet-Serverless) -4. [Using KM Plugin for Semantic Kernel](examples/003-dotnet-SemanticKernel-plugin) -5. [Processing files with custom logic (custom handlers) in serverless mode](examples/004-dotnet-serverless-custom-pipeline) -6. [Processing files with custom logic (custom handlers) in asynchronous mode](examples/005-dotnet-AsyncMemoryCustomPipeline) -7. [Upload files and ask questions from command line using curl](examples/006-curl-calling-webservice) -8. [Customizing RAG and summarization prompts](examples/101-dotnet-custom-Prompts) -9. [Custom partitioning/text chunking options](examples/102-dotnet-custom-partitioning-options) -10. [Using a custom embedding/vector generator](examples/103-dotnet-custom-EmbeddingGenerator) -11. [Using custom LLMs](examples/104-dotnet-custom-LLM) -12. [Using LLama](examples/105-dotnet-serverless-llamasharp) -13. [Summarizing documents, using synthetic memories](examples/106-dotnet-retrieve-synthetics) -14. [Using Semantic Kernel LLM connectors](examples/107-dotnet-SemanticKernel-TextCompletion) -15. [Using custom content decoders](examples/108-dotnet-custom-content-decoders) -16. [Using a custom web scraper to fetch web pages](examples/109-dotnet-custom-webscraper) -17. [Generating answers with Anthropic LLMs](examples/110-dotnet-anthropic) -18. [Hybrid Search with Azure AI Search](examples/111-dotnet-azure-ai-hybrid-search) -19. [Writing and using a custom ingestion handler](examples/201-dotnet-serverless-custom-handler) -20. [Running a single asynchronous pipeline handler as a standalone service](examples/202-dotnet-custom-handler-as-a-service) -21. [Test project using KM package from nuget.org](examples/203-dotnet-using-core-nuget) -22. [Integrating Memory with ASP.NET applications and controllers](examples/204-dotnet-ASP.NET-MVC-integration) -23. [Sample code showing how to extract text from files](examples/205-dotnet-extract-text-from-docs) -24. [.NET configuration and logging](examples/206-dotnet-configuration-and-logging) -25. [Expanding chunks retrieving adjacent partitions](examples/207-dotnet-expanding-chunks-on-retrieval) -26. [Using local models via LM Studio](examples/208-dotnet-lmstudio) -27. [Using Context Parameters to customize RAG prompt during a request](examples/209-dotnet-using-context-overrides) -28. [Creating a Memory instance without KernelMemoryBuilder](examples/210-KM-without-builder) +1. [Collection of Jupyter notebooks with various scenarios](https://github.com/microsoft/kernel-memory/tree/main/examples/000-notebooks) +2. [Using Kernel Memory web service to upload documents and answer questions](https://github.com/microsoft/kernel-memory/tree/main/examples/001-dotnet-WebClient) +3. [Importing files and asking question without running the service (serverless mode)](https://github.com/microsoft/kernel-memory/tree/main/examples/002-dotnet-Serverless) +4. [Using KM Plugin for Semantic Kernel](https://github.com/microsoft/kernel-memory/tree/main/examples/003-dotnet-SemanticKernel-plugin) +5. [Processing files with custom logic (custom handlers) in serverless mode](https://github.com/microsoft/kernel-memory/tree/main/examples/004-dotnet-serverless-custom-pipeline) +6. [Processing files with custom logic (custom handlers) in asynchronous mode](https://github.com/microsoft/kernel-memory/tree/main/examples/005-dotnet-async-memory-custom-pipeline) +7. [Upload files and ask questions from command line using curl](https://github.com/microsoft/kernel-memory/tree/main/examples/006-curl-calling-webservice) +8. [Customizing RAG and summarization prompts](https://github.com/microsoft/kernel-memory/tree/main/examples/101-dotnet-custom-Prompts) +9. [Custom partitioning/text chunking options](https://github.com/microsoft/kernel-memory/tree/main/examples/102-dotnet-custom-partitioning-options) +10. [Using a custom embedding/vector generator](https://github.com/microsoft/kernel-memory/tree/main/examples/103-dotnet-custom-EmbeddingGenerator) +11. [Using custom LLMs](https://github.com/microsoft/kernel-memory/tree/main/examples/104-dotnet-custom-LLM) +12. [Using LLama](https://github.com/microsoft/kernel-memory/tree/main/examples/105-dotnet-serverless-llamasharp) +13. [Summarizing documents, using synthetic memories](https://github.com/microsoft/kernel-memory/tree/main/examples/106-dotnet-retrieve-synthetics) +14. [Using Semantic Kernel LLM connectors](https://github.com/microsoft/kernel-memory/tree/main/examples/107-dotnet-SemanticKernel-TextCompletion) +15. [Using custom content decoders](https://github.com/microsoft/kernel-memory/tree/main/examples/108-dotnet-custom-content-decoders) +16. [Using a custom web scraper to fetch web pages](https://github.com/microsoft/kernel-memory/tree/main/examples/109-dotnet-custom-webscraper) +17. [Generating answers with Anthropic LLMs](https://github.com/microsoft/kernel-memory/tree/main/examples/110-dotnet-anthropic) +18. [Hybrid Search with Azure AI Search](https://github.com/microsoft/kernel-memory/tree/main/examples/111-dotnet-azure-ai-hybrid-search) +19. [Writing and using a custom ingestion handler](https://github.com/microsoft/kernel-memory/tree/main/examples/201-dotnet-serverless-custom-handler) +20. [Running a single asynchronous pipeline handler as a standalone service](https://github.com/microsoft/kernel-memory/tree/main/examples/202-dotnet-custom-handler-as-a-service) +21. [Test project using KM package from nuget.org](https://github.com/microsoft/kernel-memory/tree/main/examples/203-dotnet-using-KM-nuget) +22. [Integrating Memory with ASP.NET applications and controllers](https://github.com/microsoft/kernel-memory/tree/main/examples/204-dotnet-ASP.NET-MVC-integration) +23. [Sample code showing how to extract text from files](https://github.com/microsoft/kernel-memory/tree/main/examples/205-dotnet-extract-text-from-docs) +24. [.NET configuration and logging](https://github.com/microsoft/kernel-memory/tree/main/examples/206-dotnet-configuration-and-logging) +25. [Expanding chunks retrieving adjacent partitions](https://github.com/microsoft/kernel-memory/tree/main/examples/207-dotnet-expanding-chunks-on-retrieval) +26. [Using local models via LM Studio](https://github.com/microsoft/kernel-memory/tree/main/examples/208-dotnet-lmstudio) +27. [Using Context Parameters to customize RAG prompt during a request](https://github.com/microsoft/kernel-memory/tree/main/examples/209-dotnet-using-context-overrides) +28. [Creating a Memory instance without KernelMemoryBuilder](https://github.com/microsoft/kernel-memory/tree/main/examples/210-KM-without-builder) ## Tools @@ -336,24 +336,24 @@ running the service locally with OpenAPI enabled. - **Microsoft.KernelMemory.WebClient:** .NET web client to call a running instance of Kernel Memory web service. [![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.KernelMemory.WebClient)](https://www.nuget.org/packages/Microsoft.KernelMemory.WebClient/) - [![Example code](https://img.shields.io/badge/example-code-blue)](examples/001-dotnet-WebClient) + [![Example code](https://img.shields.io/badge/example-code-blue)](https://github.com/microsoft/kernel-memory/tree/main/examples/001-dotnet-WebClient) - **Microsoft.KernelMemory.Core:** Kernel Memory core library including all extensions, can be used to build custom pipelines and handlers, contains also the serverless client to use memory in a synchronous way without the web service. [![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.KernelMemory.Core)](https://www.nuget.org/packages/Microsoft.KernelMemory.Core/) - [![Example code](https://img.shields.io/badge/example-code-blue)](examples/002-dotnet-Serverless) + [![Example code](https://img.shields.io/badge/example-code-blue)](https://github.com/microsoft/kernel-memory/tree/main/examples/002-dotnet-Serverless) - **Microsoft.KernelMemory.Service.AspNetCore:** an extension to load Kernel Memory into your ASP.NET apps. [![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.KernelMemory.Service.AspNetCore)](https://www.nuget.org/packages/Microsoft.KernelMemory.Service.AspNetCore/) - [![Example code](https://img.shields.io/badge/example-code-blue)](examples/204-dotnet-ASP.NET-MVC-integration) + [![Example code](https://img.shields.io/badge/example-code-blue)](https://github.com/microsoft/kernel-memory/tree/main/examples/204-dotnet-ASP.NET-MVC-integration) - **Microsoft.KernelMemory.SemanticKernelPlugin:** a Memory plugin for Semantic Kernel, replacing the original Semantic Memory available in SK. [![Nuget package](https://img.shields.io/nuget/vpre/Microsoft.KernelMemory.SemanticKernelPlugin)](https://www.nuget.org/packages/Microsoft.KernelMemory.SemanticKernelPlugin/) - [![Example code](https://img.shields.io/badge/example-code-blue)](examples/003-dotnet-SemanticKernel-plugin) + [![Example code](https://img.shields.io/badge/example-code-blue)](https://github.com/microsoft/kernel-memory/tree/main/examples/003-dotnet-SemanticKernel-plugin) ### Packages for Python, Java and other languages diff --git a/App/kernel-memory/extensions/LlamaSharp/README.md b/App/kernel-memory/extensions/LlamaSharp/README.md index cb0738d9..78c018e3 100644 --- a/App/kernel-memory/extensions/LlamaSharp/README.md +++ b/App/kernel-memory/extensions/LlamaSharp/README.md @@ -7,6 +7,6 @@ This project contains the [LLama](https://ai.meta.com/blog/large-language-model-llama-meta-ai/) LLM connector to access to LLama LLM models and generate text, leveraging the -[LLamaSharp]((https://scisharp.github.io/LLamaSharp)) project. +[LLamaSharp](https://scisharp.github.io/LLamaSharp) project. diff --git a/App/kernel-memory/infra/README.md b/App/kernel-memory/infra/README.md index ff9034ee..0df750b2 100644 --- a/App/kernel-memory/infra/README.md +++ b/App/kernel-memory/infra/README.md @@ -59,5 +59,5 @@ var memory = new MemoryWebClient( apiKey: "...your WebServiceAuthorizationKey1..."); ``` -We recommend reviewing the [examples](../examples/) included in the repository, e.g. starting from -[001-dotnet-WebClient](../examples/001-dotnet-WebClient). +We recommend reviewing the [examples](https://github.com/microsoft/kernel-memory/tree/main/examples) included in the repository, e.g. starting from +[001-dotnet-WebClient](https://github.com/microsoft/kernel-memory/tree/main/examples/001-dotnet-WebClient).