Published on: 2024-11-27 02:28:13
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Build Chat Applications with OpenAI and LangChain, In this Build Chat Applications with OpenAI and LangChain course, we’ll explore the increasingly popular LangChain Python library to develop engaging chatbot applications. With detailed, step-by-step guidance, you will use OpenAI’s API key to access their powerful large language models (LLMs). Once we have access to foundational models, we’ll utilize LangChain and its integrations to create compelling prompts, add memory, input external data, and link it to third-party tools. LangChain’s integration with third-party tools distinguishes it by enabling connections to various language models and loading documents in multiple formats. It also allows for selecting suitable embedding models, storing embeddings in a vector store, and linking to search engines, code interpreters, and tools like Wikipedia, GitHub, Gmail, and more.
None of this would be possible without mastering the LangChain Expression Language (LCEL)—essential for developing stateful, context-aware reasoning chatbots. These chatbots remember past conversations, answer questions about unseen data, and tackle more complex problems. Additionally, we’ll spend much of our time discussing the state-of-the-art Retrieval Augmented Generation (RAG), both theoretically and practically. This technique allows LLM-powered applications to analyze and answer questions about information outside their training data. Ultimately, we’ll create a chatbot that answers students’ questions on courses from the 365 library.
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Subtitle : English
Quality: 1080p
The 2024/9 version has an increase of 105 lessons and 29 minutes in duration compared to 2024/8. Subtitles have also been added.
3.2 GB
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