{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/0db0e61d2dc1451b885d5d7d7491ed7a\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/0db0e61d2dc1451b885d5d7d7491ed7a-00001.gif","duration":300.06,"title":"Evaluation of langchain RAG using RAGAS","description":"In this walkthrough we use RAGAS to evaluate our RAG and we try out different embedding models and setup and advance retriever and compare results.   \n\nGithub Notebook: https://nbviewer.org/github/rajkstats/AIE2/blob/main/Week%204/Day%201/Evaluation_of_RAG_using_Ragas_Assignment_Notebook_RAJK.ipynb"}