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https://github.com/lm-kit/lm-kit-net-samples

.NET samples for LM-Kit.NET
https://github.com/lm-kit/lm-kit-net-samples

ai dotnet genai gpt llama llm lm-kit nlp

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.NET samples for LM-Kit.NET

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README 

          
# 🎉 Claim Your Free Community License!



Get started with the **LM-Kit Community Edition** today and gain access to powerful AI tools for free. Whether you're a hobbyist, startup, or open-source developer, the Community Edition is here to help you innovate and experiment without limitations.



👉 [Claim Your Free License Now!](https://lm-kit.com/products/community-edition/)



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# 🚀 **What's New**



*Listed from most recent to oldest*



- 🔧 [Tool Calling for Local Agents](https://lm-kit.com/blog/tool-calling-for-local-agents/) - Build AI agents with state-of-the-art tool calling. Supports all modes (simple, multiple, parallel) with structured JSON schemas, safety policies, and human-in-the-loop controls.

- 🎙️ [Speech-to-Text Support](https://lm-kit.com/solutions/language-processing/speech-to-text/) - Convert spoken audio into highly accurate text transcripts, supporting 100 languages.

- 🛡️ [Multimodal PII Extraction](https://lm-kit.com/solutions/content-analysis/#pii-extraction) - Identify and extract personally identifiable information from text and images for compliance.

- 🏷️ [Multimodal Named Entity Recognition](https://lm-kit.com/solutions/content-analysis/#ner) - Detect and classify entities (people, organizations, locations, etc.) across text and images.

- 🌐 Multimodal RAG with Reranking Support - Improve accuracy with multimodal retrieval-augmented generation and reranking.

- 🧬 [New Built-in Vector Database Engine](https://lm-kit.com/blog/lmkit-made-embedding-storage-effortless/) - Store and Retrieve Embeddings at Any Scale.

- 🔗 [New Vector Database Connector (Open Source, Qdrant Support)](https://github.com/LM-Kit/lm-kit-net-data-connectors) - Easily integrate semantic search and hybrid RAG pipelines.

- 🧠 [Semantic Kernel Integration (Open Source)](https://github.com/LM-Kit/lm-kit-net-semantic-kernel) - Build intelligent workflows with Microsoft's Semantic Kernel + LM-Kit.NET.

- 👁️ [LM-Kit Goes Multimodal: Introducing Vision Support](https://lm-kit.com/blog/lmkit-goes-multimodal/) - Image understanding now available.

- 🎮 Vulkan Backend - Accelerated multi-GPU support for AMD, Intel, and NVIDIA.

- 🧩 Function Calling Support - Dynamically invoke functions directly from model outputs.

- ✨ [Dynamic Sampling – Up to 75% Error Reduction and 2x Faster Processing for LLMs](https://lm-kit.com/blog/introducing-dynamic-sampling/)

  

👉 [See full changelog](https://docs.lm-kit.com/lm-kit-net/guides/changelog.html)



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# Enterprise-Grade .NET SDK for Integrating Generative AI Capabilities | Demo Repository



> **With LM-Kit.NET, integrating or building AI is no longer complex.**



**LM-Kit.NET** is a **cross-platform SDK** that brings together **LLMs (Large Language Models)** and **SLMs (Small Language Models)** for an extensive range of AI functionalities. It enables **Quick-Start AI Agents**, supports **multi-agent orchestration**, and offers a consistent API for C# and VB.NET. Whether you want to customize existing AI agents or build new ones, LM-Kit.NET provides a robust and streamlined approach to modern AI development.



**AI Agent Runtime for .NET**  



### **Product Overview & API Reference**

LM-Kit.NET delivers **Multimodal Generative AI** solutions for .NET, facilitating the creation and customization of AI Agents as well as comprehensive multi-agent coordination. Its capabilities, ranging from data processing, text analysis, and translation to text generation and model optimization—integrate smoothly into your .NET projects. By leveraging cutting-edge AI techniques, LM-Kit.NET empowers developers to build advanced solutions with minimal complexity.



👉 Find additional documentation and detailed guides in the **LM-Kit Docs**:  [https://docs.lm-kit.com](https://docs.lm-kit.com)



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## **Extensive Feature Set**



LM-Kit.NET offers a wide array of advanced AI features that can be seamlessly integrated into your .NET applications:



- **Interactive Question & Answering**  

  Deliver concise responses to user queries, handling both single-turn and multi-turn interactions.



- **Automated Text Generation**  

  Dynamically create context-appropriate content tailored to your needs.



- **Structured Text Creation**  

  Enforce output formats using JSON schemas, grammar constraints, templates, or other structural rules.



- **Grammar & Spelling Correction**  

  Automatically enhance content quality by fixing errors in spelling and syntax.



- **Style-Specific Rewriting**  

  Adjust the tone or style of text to align with specific communication goals.



- **Seamless Language Translations**  

  Convert text between different languages without compromising context or accuracy.



- **Speech-to-Text**  

  Convert spoken audio into highly accurate text transcripts, supporting 100+ languages.



- **Accurate Language Identification**  

  Determine the original language of any given text with high precision.



- **Concise Text Summaries**  

  Produce clear, focused summaries from extensive documents for faster comprehension.



- **Quality Assessment**  

  Evaluate text quality using various metrics, ensuring relevance and clarity.



- **RAG-Enhanced Generation**  

  Elevate text output by retrieving pertinent information from external repositories.



- **Dynamic Function Invocation**  

  Invoke specialized functions in your application on-demand to handle diverse tasks.



- **Semantic Embeddings**  

  Transform textual or image data into meaningful numeric representations for improved retrieval and analysis.



- **Customizable Data Extraction**  

  Extract and organize information from diverse sources using flexible schemas.



- **Tailored Classification**  

  Assign text to predefined categories, streamlining workflows and content management.



- **Sentiment & Emotion Analysis**  

  Detect the emotional stance of text and pinpoint specific feelings.



- **Sarcasm Detection**  

  Recognize ironic or sarcastic nuances in written material.



- **Keyword Mining**  

  Isolate critical terms and phrases from large datasets with ease.



- **Code Processing**  

  Analyze and transform programming code for enhanced development efficiency.



- **Image Analysis (Vision Support)**  

  Extend AI capabilities to interpret and evaluate images.



- **Multimodal Named Entity Recognition**  

  Detect and classify entities (people, organizations, locations, etc.) across text and images.



- **Multimodal PII Extraction**  

  Identify and extract personally identifiable information from text and images for compliance.



- **Model Quantization & Optimization**  

  Streamline both LLMs and SLMs for faster inference and lower computational overhead.



- **Fine-Tuning & LoRA Integration**  

  Adapt base models to meet domain-specific needs, incorporating Low-Rank Adaptation (LoRA) for efficient training.



- **And More…**  

  Explore additional features to supercharge your AI-driven solutions.



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## **Run Local LLMs and SLMs on Any Device**



LM-Kit.NET is powered by [llama.cpp](https://github.com/ggerganov/llama.cpp), ensuring best-in-class performance across a variety of hardware setups with minimal configuration and zero external dependencies.  

All processing happens **on-device** (edge computing), giving you full control and tunability for inference. Additionally, LM-Kit.NET supports an expanding list of model architectures, including **GPT-OSS**, **Qwen**, **Gemma**, **DeepSeek**, **Granite**, **Llama**, **Phi**, and more.



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## **Maximized Performance**



### 1. 🚀 Optimized for a Variety of GPUs and CPUs

Leverage **CUDA** on NVIDIA GPUs, **Metal** on Apple devices, and **Vulkan** for multi-GPU setups (AMD, Intel, NVIDIA), ensuring top-tier performance regardless of your hardware.



### 2. ⚙️ Advanced Architectural Foundations

Enjoy a core system optimized for diverse scenarios, with advanced caching and resource recycling that enables consistent high performance in single or multi-instance environments.



### 3. 🌟 Unmatched Performance

Experience up to **5x faster** inference speeds, backed by continuous refinements and rigorous benchmarking to keep you ahead of the competition.



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## **Retain Complete Control Over Your Data**



All inference is performed locally, meaning **no data ever leaves your device**. This ensures:



1. **Enhanced Privacy**  

   Eliminates the need to send sensitive data to external servers.



2. **Increased Security**  

   Minimizes risks of interception or unauthorized access.



3. **Faster Response Times**  

   Reduces latency by avoiding remote server round trips.



4. **Lower Bandwidth Usage**  

   Cuts down on internet data transfer, ideal for limited connectivity.



5. **Regulatory Compliance**  

   Helps satisfy GDPR, HIPAA, and other data protection requirements by keeping data on-premises.



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## **Easy Integration and Simple Deployment**



LM-Kit.NET is distributed as a single **NuGet** package, making it incredibly easy to include in your .NET applications:



1. **Streamlined Integration**  

   No need for containers or complex setup—just a few clicks in Visual Studio or your preferred .NET IDE.



2. **Direct In-Process Execution**  

   Avoid the overhead of additional services or containers, reducing latency and simplifying deployments.



3. **Efficient Resource Management**  

   Operates within your existing .NET process, making it suitable for resource-constrained environments.



4. **Enhanced Reliability**  

   By steering clear of external dependencies, LM-Kit.NET offers stable and predictable performance.



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## **Supported Operating Systems**



- **Windows**: From Windows 7 to the latest release  

- **macOS**: macOS 11 and above  

- **Linux**: Distributions with glibc 2.27 or newer  



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## **Supported .NET Frameworks**



- **.NET 4.6.2** through **.NET 9**



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## **Model Catalog**



Browse the [LM-Kit Model Catalog](https://docs.lm-kit.com/lm-kit-net/guides/getting-started/model-catalog.html) for a comprehensive list of **quantized models** tested and optimized for LM-Kit.NET. You can also seamlessly load models from Hugging Face repositories using the Hugging Face API, simplifying model discovery and deployment.