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LM-Kit Blog

Welcome to the LM-Kit blog—where we make AI so easy, even your code could write this intro! Whether you’re a .NET pro or just starting out, we’re here to help you add some serious AI power to your apps with zero hassle. Let’s build something awesome (and maybe a little smarter) together!

 

🧬 Embedding Strategies in LM-Kit: Rapid Prototyping to Durable Storage

Introduction In this post, we’ll break down four vector storage patterns supported by LM-Kit. TL;DR LM-Kit simplifies the complexity of embedding storage by offering a unified, developer-friendly interface that supports both instant prototyping and scalable deployment. It supports four storage patterns, each tailored to different stages of your project: In-Memory: Ideal for fast prototyping and low-volume tasks with zero setup. Built-In Vector DB: Self-contained file-based storage for local tools or offline apps. Qdrant Vector Store: External high-performance DB for cloud

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April 24, 2025

🧠Introducing AgentMemory: Elevating Contextual Recall with Custom Filtering

Introduction In this article, we introduce AgentMemory, the first iteration of a core component within the LM-Kit framework that augments multi-turn conversations by incorporating persistent, long-term memory. Designed for engineers and researchers, AgentMemory not only captures and recalls key conversation details over time but also filters and refines information to optimize agent behavior. By ensuring that your agents retain context across interactions, we enable smarter, more personalized AI experiences. This update incorporates practical insights from customer feedback and ongoing research to enhance real-world

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March 4, 2025

👁️‍🗨️LM-Kit Goes Multimodal: Introducing Vision Support and Our 2025 Roadmap

Introduction Over the past year, we’ve been hard at work expanding LM-Kit to empower developers with cutting-edge AI capabilities. We are now excited to announce that LM-Kit has officially gone multimodal, thanks to the addition of support for Vision Language Models (VLMs). This milestone paves the way for delivering a multi-agents orchestration system, which will be one of our main focuses in the coming year. Our journey in 2024 revolved around building a state-of-the-art inference system, fully native to the

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January 15, 2025

🏷️ Introducing LM-Kit’s Keyword Extraction API

Introduction In today’s data-rich world, extracting the essence from massive amounts of text is no easy task. With mountains of documents, articles, and reports to sift through, the need for efficient and precise keyword extraction is more critical than ever. That’s where LM-Kit’s new Keyword Extraction engine steps in, bringing together on-device processing, cutting-edge algorithms, and tiny language models (LLMs) that run swiftly on standard CPUs. The result? High-performance keyword extraction that’s both resource-friendly and fast, without sacrificing accuracy. KeywordExtraction Class Documentation

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December 9, 2024

🧩 Building a Function Calling Agent with LM-Kit

Introduction Function calling, also known as tool calling, has emerged as a transformative feature in the landscape of artificial intelligence (AI), enabling language models to perform dynamic actions based on user inputs. It serves as the cornerstone for creating AI agents, autonomous systems capable of interacting with the environment, making decisions, and performing tasks without constant human guidance. With the advent of tools like LM-Kit, developers can now harness this capability with unprecedented ease and flexibility. In this article, we’ll

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October 16, 2024

😊Introducing LM-Kit’s New Multilingual Sentiment Analysis Model

Bringing Real-Time Sentiment Analysis to Any Device with Unparalleled Accuracy. Introduction We are thrilled to announce the release of our new Sentiment Analysis Model v2, a state-of-the-art tool designed to accurately analyze the sentiment of text in real-time. This model is a significant addition to the Text Analysis category within the LM-Kit framework, which empowers developers with advanced AI capabilities for .NET applications. LM-Kit.NET is a comprehensive toolkit that brings the power of Generative AI directly into your .NET projects

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October 9, 2024

⚡Introducing Dynamic Sampling in LM-Kit.NET: Up to 75% Error Reduction and 2x Faster Processing for LLMs

Introduction We are thrilled to announce a significant enhancement in our latest release of LM-Kit.NET: the introduction of a new parameter  that allows you to activate or deactivate our Dynamic Sampling technology. This isn’t just a simple toggle, it’s a gateway to making Large Language Models (LLMs) faster and smarter, enabling them to better serve various industry use cases. Dynamic Sampling is deeply embedded at the core of LM-Kit.NET, utilized extensively across both internal mechanisms and public API layers. Our engineering team is committed to iterative

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October 2, 2024

🤖Hello World!

It’s been an exciting week for us here at LM-Kit. After months of hard work, passion, and innovation, we are beyond thrilled to introduce our company to the world and officially launch our first product: LM-Kit.NET! 🚀 Who Are We? LM-Kit is a young, dynamic startup founded in 2024 in the heart of Toulouse, France. But while our company is fresh on the scene, our roots run deep. With over 20 years of experience in SDK development and critical business

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September 8, 2024

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