Comprehensive прототипирование чат-ботов Tools for Every Need

Get access to прототипирование чат-ботов solutions that address multiple requirements. One-stop resources for streamlined workflows.

прототипирование чат-ботов

  • A Python library enabling real-time streaming AI chat agents using OpenAI API for interactive user experiences.
    0
    0
    What is ChatStreamAiAgent?
    ChatStreamAiAgent provides developers with a lightweight Python toolkit to implement AI chat agents that stream token outputs as they are generated. It supports multiple LLM providers, asynchronous event hooks, and easy integration into web or console applications. With built-in context management and prompt templating, teams can rapidly prototype conversational assistants, customer support bots, or interactive tutorials while delivering low-latency, real-time responses.
  • A minimal Python-based AI agent demo showcasing GPT conversational models with memory and tool integration.
    0
    0
    What is DemoGPT?
    DemoGPT is an open-source Python project designed to demonstrate the core concepts of AI agents using OpenAI's GPT models. It implements a conversational interface with persistent memory saved in JSON files, enabling context-aware interactions across sessions. The framework supports dynamic tool execution, such as web search, calculations, and custom extensions, through a plugin-style architecture. By simply configuring your OpenAI API key and installing dependencies, users can run DemoGPT locally to prototype chatbots, explore multi-turn dialogue flows, and test agent-driven workflows. This comprehensive demo offers developers and researchers a practical foundation for building, customizing, and experimenting with GPT-powered agents in real-world scenarios.
  • Wizard Language is a declarative TypeScript DSL to define multi-step AI agents with prompt orchestration and tool integration.
    0
    0
    What is Wizard Language?
    Wizard Language is a declarative domain-specific language built on TypeScript for authoring AI assistants as wizards. Developers define intent-driven steps, prompts, tool invocations, memory stores, and branching logic in a concise DSL. Under the hood, Wizard Language compiles these definitions into orchestrated LLM calls, managing context, asynchronous flows, and error handling. It accelerates prototyping of chatbots, data retrieval assistants, and automated workflows by abstracting prompt engineering and state management into reusable components.
Featured