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Разработка на основе данных

  • A Python library enabling developers to build robust AI agents with state machines managing LLM-driven workflows.
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    What is Robocorp LLM State Machine?
    LLM State Machine is an open-source Python framework designed to construct AI agents using explicit state machines. Developers define states as discrete steps—each invoking a large language model or custom logic—and transitions based on outputs. This approach provides clarity, maintainability, and robust error handling for multi-step, LLM-powered workflows, such as document processing, conversational bots, or automation pipelines.
  • Supercharge your AI interactions by capturing project structures effortlessly.
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    What is Struct2AI?
    StructAI transforms the way developers engage with AI by enabling instant structure capture of projects and selected file contents. This facilitates an AI-ready output that can be pasted directly into your preferred AI tools. With features such as smart file selection and GitHub integration, StructAI ensures that you have the relevant data at your fingertips. Forget about tedious manual structuring; experience a lightning-fast and efficient way to enhance your AI-driven projects.
  • AI-powered feedback collection and prioritization technology for building customer-centric products.
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    What is Visionari?
    Visionari leverages advanced AI technology to streamline the feedback collection and prioritization process for businesses. By gathering user feedback from various channels, analyzing insights with AI, and automating the creation of roadmaps and changelogs, Visionari ensures that companies can efficiently prioritize and implement the most impactful features. This results in increased customer satisfaction and engagement, reducing manual work and enabling a more focused, data-driven approach to product development.
  • QueryCraft is a toolkit for designing, debugging, and optimizing AI agent prompts, with evaluation and cost analysis capabilities.
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    What is QueryCraft?
    QueryCraft is a Python-based prompt engineering toolkit designed to streamline the development of AI agents. It enables users to define structured prompts through a modular pipeline, connect seamlessly to multiple LLM APIs, and conduct automated evaluations against custom metrics. With built-in logging of token usage and costs, developers can measure performance, compare prompt variations, and identify inefficiencies. QueryCraft also includes debugging tools to inspect model outputs, visualize workflow steps, and benchmark across different models. Its CLI and SDK interfaces allow integration into CI/CD pipelines, supporting rapid iteration and collaboration. By providing a comprehensive environment for prompt design, testing, and optimization, QueryCraft helps teams deliver more accurate, efficient, and cost-effective AI agent solutions.
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