LangChain Structured Data (Pydantic & JSON) Extraction | LlaMa-3 | Groq API

Hi, My name is Sunny Solanki, and in this video, I provide a step-by-step guide to structured data extraction with Open Source LLMs (LlaMa-3). We access LLMs through Groq API. Structured data extraction from unstructured data is one of the useful applications of LLMs. ============================================ CODE - https://github.com/sunny2309/langchain_tutorials/blob/main/Structured%20Output%20from%20LLMs.ipynb ============================================== ======================================================= SUPPORT US - https://buymeacoffee.com/coderzcolumn ======================================================= ======================================================= NEWSLETTER - http://eepurl.com/gRW2u9 ======================================================= ======================================================= WEBSITE - https://coderzcolumn.com ======================================================= Important Chapters: 0:00 - Structured Data Extraction using LlaMa-3 Intro 0:54 - Code Start 3:04 - Load LLM 4:09 - Define Structured Data Schemas 5:44 - Generate Structured (Pydantic) Output 8:32 - Generate JSON Output #python #datascience #datasciencetutorial #python #pythonprogramming #pythoncode #pythontutorial #llama3 #langchain #langchain-structured-output #langchain-llama3 #groqapi #langchain-open-source-llms #langchain-data-extraction #llama-3-data-extraction #how-to-use-langchain