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学习、联系、构建

Microsoft Reactor

加入 Microsoft Reactor 并实时与开发人员互动

准备好开始使用 AI 和最新技术了吗？ Microsoft Reactor 提供活动、培训和社区资源，帮助开发人员、企业家和初创公司利用 AI 技术等。快加入我们吧！

Python + Agents: Adding context and memory to agents

25 二月, 2026 | 6:30 下午 - 7:30 下午 (UTC) 协调世界时

形式:
直播

主题: 代理

语言: 英语

In the second session of our Python + Agents series, we’ll extend agents built with the Microsoft Agent Framework by adding two essential capabilities: context and memory.

We’ll begin with context, commonly known as Retrieval‑Augmented Generation (RAG), and show how agents can ground their responses using knowledge retrieved from local data sources such as SQLite or PostgreSQL.

This enables agents to provide accurate, domain‑specific answers based on real information rather than model hallucination. Next, we’ll explore memory—both short‑term, thread‑level context and long‑term, persistent memory.

You’ll see how agents can store and recall information using solutions like Redis or open‑source libraries such as Mem0, enabling them to remember previous interactions, user preferences, and evolving tasks across sessions.

By the end, you’ll understand how to build agents that are not only capable but context‑aware and memory‑efficient, resulting in richer, more personalized user experiences.

先决条件

To follow along with the live examples, sign up for a free GitHub account. If you are brand new to generative AI with Python, start with our our 9-part Python + AI series, which covers LLMs, embedding models, RAG, tool calling, MCP, and more.

主讲人