Advanced Modèles OpenAI Tools for Professionals

Discover cutting-edge Modèles OpenAI tools built for intricate workflows. Perfect for experienced users and complex projects.

Modèles OpenAI

  • Refined chat interface supporting multiple AI models, voice input, and text-to-speech.
    0
    0
    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 .NET sample demonstrating building a conversational AI Copilot with Semantic Kernel, combining LLM chains, memory, and plugins.
    0
    0
    What is Semantic Kernel Copilot Demo?
    Semantic Kernel Copilot Demo is an end-to-end reference application illustrating how to build advanced AI agents with Microsoft’s Semantic Kernel framework. The demo features prompt chaining for multi-step reasoning, memory management to recall context across sessions, and a plugin-based skill architecture enabling integration with external APIs or services. Developers can configure connectors for Azure OpenAI or OpenAI models, define custom prompt templates, and implement domain-specific skills such as calendar access, file operations, or data retrieval. The sample shows how to orchestrate these components to create a conversational Copilot capable of understanding user intents, executing tasks, and maintaining context over time, fostering rapid development of personalized AI assistants.
  • Open-source Python framework enabling creation of custom AI Agents integrating web search, memory, and tools.
    0
    0
    What is AI-Agents by GURPREETKAURJETHRA?
    AI-Agents offers a modular architecture for defining AI-driven agents using Python and OpenAI models. It incorporates pluggable tools—including web search, calculators, Wikipedia lookup, and custom functions—allowing agents to perform complex, multi-step reasoning. Built-in memory components enable context retention across sessions. Developers can clone the repository, configure API keys, and extend or swap tools quickly. With clear examples and documentation, AI-Agents streamlines the workflow from concept to deployment of tailored conversational or task-focused AI solutions.
Featured