Prompt Engineering - E.36 | Prompt Engineering using LangChain 🦜️🔗 | RAG Documents Embedding and Indexing | Ch.9 2/3

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6 hours of video
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Summary

Keywords

langchiain openai chatgpt prompt engineering vectors embeddings rag qna شرح كورس

Full Transcript

In this video, we will write the codes for the second step of building an open QnA system which is document embedding and indexing. Join us to learn all about developing Questioning and Answering and Retrieval Augmented Generation (RAG) apps using LLMs and LangChain Notebook: https://colab.research.google.com/drive/1mHTius2J-xi_P_3U9d82gfPp7SpQF5fV?usp=sharing 💡 - OpenAI Embedding 💡 - Cohere Embedding 💡 - HuggingFace Embedding 💡 - Indexing using FAISS 💡 - Indexing using ChromaDB

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