- 理解Python编程
- 熟悉大型语言模型和提示工程
- 具备API和自动化工作流程的经验
目标受众
- AI工程师
- ML开发者
- 自动化架构师
使用AutoGen構建LLM代理系統是一門實作課程，專注於利用Microsoft的AutoGen框架開發多代理系統，適用於大型語言模型（LLMs）。
這項由講師主導的培訓（線上或線下）針對中級AI與自動化專業人士，旨在幫助他們設計、實現並協調使用AutoGen與Python及LLMs的多代理系統。
培訓結束後，參與者將能夠：
- 使用AutoGen框架設計多代理架構。
- 配置代理角色、能力與協調行為。
- 使用函數調用與記憶處理進行代理互動。
- 構建並測試基於Python的LLM代理工作流程，適用於實際案例。
課程形式
- 互動式講座與討論。
- 大量練習與實踐。
- 在實作實驗室環境中進行動手操作。
課程定制選項
- 如需為本課程定制培訓，請聯繫我們安排。
LLM Agent Systems 簡介
- LLM agents 和多代理架構概念
- AutoGen 框架和生態系統概述
- 代理角色：用戶代理、助理、函數調用者等
安裝與配置 AutoGen
- 設置 Python 環境和依賴項
- AutoGen 配置文件基礎
- 連接 LLM 提供商（OpenAI、Azure、本地模型）
代理設計與角色分配
- 了解代理類型和對話模式
- 定義代理目標、提示和指令
- 基於角色的任務委派和控制流程
函數調用與工具集成
- 註冊供代理使用的函數
- 自主和協作函數執行
- 將外部 API 和 Python 腳本連接到代理
對話 Management 與記憶
- 會話跟踪和持久記憶
- 代理間消息傳遞和令牌處理
- 管理對話上下文和歷史記錄
端到端代理工作流程
- 構建多步驟協作任務（例如文檔分析、代碼審查）
- 模擬用戶代理對話和決策鏈
- 調試和優化代理性能
Use Case 與部署
- 內部自動化代理：研究、報告、腳本
- 外部機器人：聊天助理、語音集成
- 在生產環境中打包和部署代理系統
總結與下一步
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