Comprehensive Kettendenken Tools for Every Need

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  • A Go-based framework enabling developers to build, test and run AI agents with in-process chain-of-thought and customizable tools.
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    What is Goated Agents?
    Goated Agents simplifies building sophisticated AI-driven autonomous systems in Go. By embedding chain-of-thought processing directly in the language runtime, developers can implement multi-step reasoning with transparent intermediate reasoning logs. The library offers a tool definition API, allowing agents to call external services, databases, or custom code modules. Memory management support enables persistent context across interactions. Plugin architecture facilitates extending core capabilities such as tool wrappers, logging, and monitoring. Goated Agents leverages Go’s performance and static typing to deliver efficient, reliable agent execution. Whether constructing chatbots, automation pipelines, or research prototypes, Goated Agents provides the building blocks to orchestrate complex reasoning flows and integrate LLM-driven intelligence seamlessly into Go applications.
    Goated Agents Core Features
    • In-process chain-of-thought reasoning
    • Customizable tool definition API
    • Memory management for context persistence
    • Plugin architecture for extensions
    • Multi-step reasoning with transparent logs
    • LLM integration support
    • Type-safe Go implementation
    • Agent orchestration and execution
  • Wumpus is an open-source framework that enables creation of Socratic LLM agents with integrated tool invocation and reasoning.
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    What is Wumpus LLM Agent?
    Wumpus LLM Agent is designed to simplify development of advanced Socratic AI agents by providing prebuilt orchestration utilities, structured prompting templates, and seamless tool integration. Users define agent personas, tool sets, and conversation flows, then leverage built-in chain-of-thought management for transparent reasoning. The framework handles context switching, error recovery, and memory storage, enabling multi-step decision processes. It includes a plugin interface for APIs, databases, and custom functions, allowing agents to browse the web, query knowledge bases, or execute code. With comprehensive logging and debugging, developers can trace each reasoning step, fine-tune agent behavior, and deploy on any platform that supports Python 3.7+.
  • AgentX is an open-source framework enabling developers to build customizable AI agents with memory, tool integration, and LLM reasoning.
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    What is AgentX?
    AgentX provides an extensible architecture for building AI-driven agents that leverage large language models, tool and API integrations, and memory modules to perform complex tasks autonomously. It features a plugin system for custom tools, support for vector-based retrieval, chain-of-thought reasoning, and detailed execution logs. Users define agents through flexible configuration files or code, specifying tools, memory backends like Chroma DB, and reasoning pipelines. AgentX manages context across sessions, enables retrieval-augmented generation, and facilitates multiturn conversations. Its modular components allow developers to orchestrate workflows, customize agent behaviors, and integrate external services for automation, research assistance, customer support, and data analysis.
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