商品描述
Learn to build sophisticated AI apps with Python's hottest new framework. This hands-on guide takes you from basic chatbots to advanced assistants that can reason about data.
- Step-by-step projects show you how to create AI-powered apps with LangChain, Streamlit, and Chainlit
- Master prompt engineering fundamentals to elicit accurate responses from large language models
- Build conversational agents that can use calculators, Wikipedia, weather data, and custom tools
- Integrate external APIs to connect your models with real-time data
- Implement retrieval augmented generation (RAG) for context-aware question answering
- Deploy your agents as web apps with Streamlit and Chainlit for easy interaction
- Integration Techniques: Explore how to seamlessly connect with OpenAI's Large Language Models (LLMs) and other AI tools.
- Advanced Concepts Made Simple: Grasp the intricacies of Prompt Templates, Simple Chains, Sequential Chains, and Agents.
- Interactive Learning: Engage in practical exercises like 'Chat with a Document' and adding memory to chat applications.
Whether you're looking to level up your Python skills or launch a new AI project, this book equips you with the knowledge to unlock the full capabilities of LangChain. Fun examples feature cooking assistants and storytelling bots. Ideal for developers familiar with Python.
商品描述(中文翻譯)
學習使用Python最熱門的新框架來建立複雜的人工智慧應用程式。這本實作指南將帶領你從基本的聊天機器人到可以推理數據的高級助手。
逐步專案示範如何使用LangChain、Streamlit和Chainlit創建AI應用程式。
掌握提示工程基礎，以從大型語言模型中獲得準確的回應。
建立可以使用計算機、維基百科、天氣數據和自定義工具的對話代理。
整合外部API，將模型與實時數據連接。
實施擴充式生成（RAG）以進行上下文感知的問答。
使用Streamlit和Chainlit將代理部署為Web應用程式，以便進行簡單的互動。
整合技術：探索如何與OpenAI的大型語言模型（LLM）和其他人工智慧工具無縫連接。
深入理解高級概念：掌握提示模板、簡單鏈、順序鏈和代理的細節。
互動學習：參與實際練習，如“與文件聊天”和為聊天應用程式添加記憶功能。
無論你是想提升Python技能還是啟動一個新的人工智慧項目，這本書將為你提供解鎖LangChain全部功能的知識。有趣的例子包括烹飪助手和故事機器人。適合熟悉Python的開發人員。
