GenerativeCS: A Unified Generative AI Development Library for .NET Developers

GenerativeCS, launched by ChatAIze, is a feature-rich .NET generative AI library that supports four major mainstream APIs: OpenAI, xAI Grok, Anthropic Claude, and Google Gemini. It provides complete functions including chat completion, function calling, speech synthesis, and semantic embedding, and deeply integrates .NET programming paradigms (such as dependency injection and asynchronous programming). By enabling native C# function calls via reflection, it helps .NET developers flexibly integrate multiple AI capabilities without changing their tech stack, keeping code concise and maintainable.

GenerativeCS was born out of the urgent need for native generative AI support in the .NET ecosystem. While Python dominates the AI field, .NET has a large user base in enterprise application development, and many enterprises want to integrate AI capabilities without changing their tech stack. This library supports .NET 9.0 and above, can be quickly integrated via NuGet, is open-source under the MIT license, with code hosted on GitHub. The community is highly active, and it continuously follows up on the latest API updates from various AI providers.

GenerativeCS covers mainstream generative AI application scenarios:

• Text Generation: Supports chat completion, streaming responses, multi-turn conversation management, with built-in message history to maintain context;
• Function Calling: Automatically discovers local functions via C# reflection, no need to manually write function descriptions or parameter parsing;
• Speech Processing: Supports Text-to-Speech (TTS), Speech-to-Text (STT), and speech translation, compatible with multiple audio formats;
• Other Functions: Provides advanced capabilities such as text embedding generation, content moderation, and image generation, forming a complete AI matrix.

The unified API abstraction layer of GenerativeCS is one of its core values:

• Defines four client classes: OpenAIClient, GrokClient, ClaudeClient, and GeminiClient, all implementing a unified interface contract with consistent asynchronous method signatures;
• Supports switching AI providers at runtime without rewriting business logic;
• Each client offers fine-grained configurations (model selection, temperature, maximum tokens, retry strategy, etc.), which can be initialized as default or temporarily overridden for a single request.

GenerativeCS has a unique design in function calling:

• Automatically analyzes C# method parameters and return values via reflection to generate function definitions that comply with the OpenAI Function Calling specification;
• When the AI model decides to call a function, it automatically parses parameters, executes the local method, and returns the result with a transparent process;
• Supports features like time awareness (obtaining current time) and message pinning (keeping key instructions in context), simplifying AI Agent development.

GenerativeCS is suitable for various .NET scenarios:

• Enterprise Chatbots: As a backend engine, it works with Blazor/WPF to build intelligent customer service;
• Content Generation Tools: Streaming responses provide real-time text generation experiences;
• Voice Interaction Applications: Integrates TTS/STT to build full-duplex voice conversation systems;
• RAG Applications: Seamlessly connects to vector databases via embedding vector generation, enabling semantic search and knowledge Q&A;
• AI Agents: Encapsulates enterprise internal APIs, database queries, etc., into tool functions, allowing AI to have business operation capabilities.

GenerativeCS provides .NET developers with a comprehensive, elegantly designed generative AI development tool, breaking language ecosystem barriers and allowing .NET applications to access advanced AI capabilities on an equal footing. Its unified multi-provider support, native .NET integration, and powerful function calling capabilities form a production-ready framework. It will continue to iterate in the future, adding support for new models and features, making it an excellent open-source project for .NET teams to introduce AI capabilities.