#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
#FIO/USDT analysis :
#FIO is in an uptrend, forming higher highs (HHs) and higher lows (HLs) while trading above the 200 EMA. The price has broken out and retested the previous swing high resistance levels. It is expected to bounce back from this point and continue its bullish momentum to test the recent swing high.
TF : 1D
Entry : $0.0305
Target : $0.0417
SL : $0.0270
#FIO/USDT analysis :
#FIO is currently in an uptrend, forming higher highs (HHs) and higher lows (HLs), while finding support above the trendline. The price is anticipated to rebound from the current level to sustain its bullish momentum and test new highs.
TF : 4h
Entry : $0.0259
Target : $0.0300
SL : $0.0238
#FIO/USDT analysis :
#FIO is currently experiencing a decline from the resistance zone following rejections in that region. It is anticipated to maintain its downward momentum and possibly test previous lows.
TF : 4H
Entry : $0.0198
Target : $0.0162
SL : $0.0210