Advanced 대화형 채팅 도구 Tools for Professionals

Discover cutting-edge 대화형 채팅 도구 tools built for intricate workflows. Perfect for experienced users and complex projects.

대화형 채팅 도구

  • Refined chat interface supporting multiple AI models, voice input, and text-to-speech.
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    What is ChatKit?
    ChatKit is a sophisticated application designed to refine your ChatGPT experience. It supports various AI models, including OpenAI, Gemini, and Azure models. With features such as prompt templates, chat bookmarks, text-to-speech, and voice input, ChatKit aims to create a seamless and efficient chat experience. Users have the flexibility to use their API keys or ChatKit credits, incorporating advanced functionalities like URL context, full-text search in chat history, and real-time chat capabilities.
    ChatKit Core Features
    • Support for multiple AI models
    • Prompt templates
    • Chat bookmarks
    • Text-to-speech
    • Voice input
    • Full-text search in chat history
    ChatKit Pro & Cons

    The Cons

    No open-source code availability
    No mobile app links or extensions found
    Limited pricing options detail beyond the website

    The Pros

    Supports multiple AI models including OpenAI, Gemini, Azure, and custom models
    Offers advanced prompt engineering tools and templates
    Includes text-to-speech and voice input features
    Enables saving and sharing of prompt templates
    One-time payment available
  • A Streamlit-based UI showcasing AIFoundry AgentService for creating, configuring, and interacting with AI agents via API.
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    What is AIFoundry AgentService Streamlit?
    AIFoundry-AgentService-Streamlit is an open-source demo application built with Streamlit that lets users quickly spin up AI agents via AIFoundry’s AgentService API. The interface includes options to select agent profiles, adjust conversational parameters like temperature and max tokens, and display conversation history. It supports streaming responses, multiple agent environments, and logs requests and responses for debugging. Written in Python, it simplifies testing and validating different agent configurations, accelerating the prototyping cycle and reducing integration overhead before production deployment.
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