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modelos de prompts personalizados

  • A .NET sample demonstrating building a conversational AI Copilot with Semantic Kernel, combining LLM chains, memory, and plugins.
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    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.
    Semantic Kernel Copilot Demo Core Features
    • LLM Prompt Chaining
    • Contextual Memory Storage
    • Plugin-based Skill Architecture
    • Azure or OpenAI Model Integration
    • Custom Prompt Template Management
    • Conversational Task Orchestration
  • ThreeAgents is a Python framework that orchestrates interactions among system, assistant, and user AI agents via OpenAI.
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    What is ThreeAgents?
    ThreeAgents is built in Python, leveraging OpenAI's chat completions API to instantiate multiple AI agents with distinct roles (system, assistant, user). It provides abstractions for agent prompting, role-based message handling, and context memory management. Developers can define custom prompt templates, configure agent personalities, and chain interactions to simulate realistic dialogues or task-oriented workflows. The framework handles message passing, context window management, and logging, enabling experiments in collaborative decision-making or hierarchical task decomposition. With support for environment variables and modular agents, ThreeAgents allows seamless swapping between OpenAI and local LLM backends, facilitating rapid prototyping of multi-agent AI systems. It ships with example scripts and Docker support for quick setup.
  • A Python library enabling real-time streaming AI chat agents using OpenAI API for interactive user experiences.
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    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.
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