Source: Zhuanzhi
This article is a book introduction, recommended reading time 5 minutes. Learn to build complex AI applications using the latest popular frameworks in Python. This practical guide will take you from basic chatbots to advanced assistants capable of reasoning over data.
Learn to build complex AI applications using the latest popular frameworks in Python. This practical guide will take you from basic chatbots to advanced assistants capable of reasoning over data.
Step-by-step projects showcase how to create AI-driven applications using LangChain, Streamlit, and Chainlit. Master the fundamentals of prompt engineering 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 models with real-time data. Implement retrieval-augmented generation (RAG) for context-aware Q&A. Deploy your agents as web applications using Streamlit and Chainlit for easy interaction. Integration technologies: explore how to seamlessly connect with OpenAI’s large language models (LLMs) and other AI tools. Simplify advanced concepts: master the complexities of prompt templates, simple chains, sequence chains, and agents. Interactive learning: engage in practical exercises such as “chatting with documents” and adding memory to chat applications.
Whether you aim to enhance your Python skills or kickstart a new AI project, this book provides you with the knowledge to unlock all the features of LangChain. Interesting examples include a cooking assistant and a storytelling robot. Suitable for developers familiar with Python.
