Uploaded May 2025 | Updated September 2026, 3 weeks ago
In this episode, we delve into the process of creating a knowledge base for workflow optimization using various methods such as syncing from websites, adding Notion pages, or integrating text files like research papers. Key steps include uploading documents, configuring chunking settings, and optimizing retrieval through vector or hybrid search methods. The video also explores advanced customizations like embedding models, chunk length variations, and pre-processing rules for enhanced performance. By the end, we demonstrate how these configurations can significantly impact the accuracy and relevance of answers generated by large language models (LLMs).
#DifyAI #RAG #LLM #KnowledgeBase #AIWorkflow #VectorSearch #Chunking #PromptEngineering #OpenAI #GPT4o #GPT4 #NoCodeAI #AIDevTools
In this episode, we delve into the process of creating a knowledge base for workflow optimization using various methods such as syncing from websites, adding Notion pages, or integrating text files like research papers. Key steps include uploading documents, configuring chunking settings, and optimizing retrieval through vector or hybrid search methods. The video also explores advanced customizations like embedding models, chunk length variations, and pre-processing rules for enhanced performance. By the end, we demonstrate how these configurations can significantly impact the accuracy and relevance of answers generated by large language models (LLMs).
#DifyAI #RAG #LLM #KnowledgeBase #AIWorkflow #VectorSearch #Chunking #PromptEngineering #OpenAI #GPT4o #GPT4 #NoCodeAI #AIDevTools
