#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
#DIA/USDT analysis :
#DIA is in an uptrend, forming higher highs (HHs) and higher lows (HLs). The price has retraced and tested the support zone, rebounding from that level. It is expected that the price will continue its bullish momentum from the current level and test the previous highs.
TF : 1W
Entry : $0.5230
Target : $1.2800
SL : $0.3480