Basic Langchain and RAG - AI Agent 開發特訓營:短期實現智能自動化 - Cupoy
直接進code學習 基礎 Langchain code for app llm chain : Chat models and prompts: retrievers : Build a sema...
直接進code學習 基礎 Langchain code for app llm chain : Chat models and prompts: retrievers : Build a semantic search engine over a PDF with document loaders, embedding models, and vector stores. classification : Classify text into categories or labels using chat models with structured outputs. extraction : Extract structured data from text and other unstructured media using chat models and few-shot examples. RAG : part1, PART2 code position: https://drive.google.com/drive/folders/1PTY3j1cgQ43LHTQazeMnWvKqNlgkG0lh?usp=share_link RAG from Scratch: https://drive.google.com/drive/folders/17qmUCpAj0KaBTHUT_2ZIahbbEkhRszjK?usp=share_link code RAG part1 : https://colab.research.google.com/drive/1WmsjaW0WHw8xi8GROG4EyN1GF4XQHy_b code RAG part2 : https://colab.research.google.com/drive/1wP2_p-z82DT0EijZzJYWrhJERuz4078K