Comprehensive 빠른 프로토타입 개발 Tools for Every Need

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빠른 프로토타입 개발

  • HyperChat enables multi-model AI chat with memory management, streaming responses, function calling, and plugin integration in applications.
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    What is HyperChat?
    HyperChat is a developer-centric AI agent framework that simplifies embedding conversational AI into applications. It unifies connections to various LLM providers, handles session context and memory persistence, and delivers streamed partial replies for responsive UIs. Built-in function calling and plugin support enable executing external APIs, enriching conversations with real-world data and actions. Its modular architecture and UI toolkit allow rapid prototyping and production-grade deployments across web, Electron, and Node.js environments.
  • A no-code web platform for building custom AI copilots with prompt editing and tool integration.
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    What is Copilot Studio?
    Copilot Studio is an AI platform & framework enabling rapid creation of domain-specific copilots. Through its drag-and-drop interface, users design prompt templates, set up tool integrations (e.g., APIs, databases), manage model selection, and orchestrate deployment. It supports version control, testing consoles, and multi-model routing, abstracting infrastructure complexity. Teams can prototype, iterate, and launch intelligent agents for customer service, developer assistance, or personal productivity in minutes.
  • Dive is an open-source Python framework for building autonomous AI agents with pluggable tools and workflows.
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    What is Dive?
    Dive is a Python-based open-source framework designed for creating and running autonomous AI agents that can perform multi-step tasks with minimal manual intervention. By defining agent profiles in simple YAML configuration files, developers can specify APIs, tools, and memory modules for tasks such as data retrieval, analysis, and pipeline orchestration. Dive manages context, state, and prompt engineering, allowing flexible workflows with built-in error handling and logging. Its pluggable architecture supports a wide range of language models and retrieval systems, making it easy to assemble agents for customer service automation, content generation, and DevOps processes. The framework scales from prototype to production, offering CLI commands and API endpoints to integrate agents seamlessly into existing systems.
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