5 个仓库
Tools for defining and enforcing structured function schemas for language model tool calling.
Distinguishing note: Focuses on the schema definition and interface contract for LLM-invokable functions, distinct from general data extraction.
Explore 5 awesome GitHub repositories matching artificial intelligence & ml · Function Definitions. Refine with filters or upvote what's useful.
This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services
Extracts metadata, parameter types, and descriptions from functions to create structured tool definitions compatible with model calling.
PydanticAI is a Python framework designed for building production-grade autonomous agents. It provides a unified interface for interacting with diverse language models, enabling developers to construct agents that perform complex tasks through structured data validation, tool execution, and multi-turn conversation management. The library centers on type-safe schema enforcement, ensuring that model inputs and outputs remain consistent and reliable throughout the agent's lifecycle. The framework distinguishes itself through a robust architecture that emphasizes modularity and testability. It ut
Filters and modifies tool definitions dynamically to control model access and execution capabilities.
This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu
Defines structured function schemas that allow LLMs to invoke specific actions or fetch data.
This project serves as a comprehensive educational repository and technical reference collection, documenting a wide range of software engineering practices and modern development technologies. It provides a structured learning path for developers, curating tutorials and practical examples that cover the full lifecycle of application development, from initial project scaffolding to deployment and maintenance. The repository distinguishes itself by offering deep technical insights into complex architectural patterns, including actor-based concurrency models for managing parallel tasks and cont
Encapsulates logic into modular, reusable functions with explicit parameter and return type definitions.
Geekai 是一个多模型 AI 平台和 SaaS 框架,旨在通过统一界面部署和管理 AI 智能体及多模态模型。它作为一个多模态 AI 网关,为文本、图像、音频和视频生成提供对大语言模型和生成式工具的集中访问。 该项目作为一个 AI 智能体编排器,允许定义专门的角色并导入外部工作流和知识库。它的特色在于提供了一个完整的商业服务层,包括基于积分的计费、订阅管理,以及用于变现自定义 AI 应用程序的创作者生态系统。 该平台涵盖了广泛的能力领域,包括用于幻灯片和动作迁移视频的 AI 内容生成、具有基于角色访问控制(RBAC)的企业运营管理,以及用于跨本地和云提供商管理资产的驱动程序式存储抽象。它还集成了业务分析、API 速率限制和自动数据库迁移。 该系统支持在具有可配置 HTTPS 和 SSL 设置的自托管服务器上进行私有实例部署。
Allows registration of custom backend functions that AI models can invoke for external tasks.