LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
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OrcaRouter
OrcaRouter serves as a routing system for AI models that are compatible with OpenAI, efficiently directing prompts to the appropriate models from a wide array, including OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Kimi, and over 200 other leading and open-source models. Its design aims to maintain the high quality of responses while minimizing costs associated with AI inference by evaluating each prompt and directing complex reasoning tasks to premium models while assigning simpler tasks to more economical open-source options. The routing process is meticulously quality-graded, avoiding arbitrary swaps for cheaper models, and every request clearly indicates the difficulty rating, chosen model, provider, and associated costs, ensuring that routes remain transparent, accountable, and reproducible. Developers can easily switch models by updating the API base URL, while previously established SDKs, model names, and streaming functionalities remain operational. Additionally, OrcaRouter features seamless automatic failover capabilities, allowing for traffic rerouting without interruption should a provider experience downtime, thus preventing disruptions for users. It also offers comprehensive API key management that incorporates spending limits, model allowlists, rate restrictions, and budget compliance, among other functionalities, ensuring robust control over resource usage. This combination of features makes OrcaRouter an indispensable tool for optimizing AI model utilization in various applications.
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Gemini 3.8 Flash-Lite TTS
Gemini 3.8 Flash-Lite TTS is an expressive text-to-speech model from Google optimized for high-volume, cost-efficient speech generation. It is designed for workloads such as global dubbing, large-scale audio content production, localization, and conversational voice agents. Users can control characteristics such as tone, pacing, emphasis, and expressive nuance to shape how generated speech is delivered. Line-by-line direction allows scripts to include performance instructions and natural speech cues rather than producing uniformly spoken narration. The model supports long-form generation and is designed to preserve voice quality, natural pacing, and character consistency across extended audio. Native two-speaker staging allows developers and creators to generate multi-turn conversations while keeping speakers distinct and maintaining natural turn-taking. Scripted cues can introduce laughs, sighs, gasps, and listening responses such as “mhm” or “yeah” to make dialogue more conversational. Gemini 3.8 Flash-Lite TTS supports more than 100 languages and is designed for multilingual audio experiences at global scale, while generated Gemini Audio output includes SynthID watermarking for transparency. Developers can access the model through Google AI Studio and the Gemini API, with integration into Google Vids and planned API availability through Gemini Enterprise.
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