#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
#ALPINE/USDT analysis :
#ALPINE is currently in a downtrend, trading below the 200 Exponential Moving Average (EMA) and making new lows. The price is expected to continue its bearish momentum and test lower levels. For a short entry, wait for the price to test the zone and resume its bearish momentum.
TF : 4H
Entry : $0.923
Target : $0.819
SL : $0.991
#ALPINE/USDT analysis :
#ALPINE is in a downtrend, trading below the 200 EMA. The price is currently facing rejection from the resistance zone and is expected to continue its downward movement. look for retracement to enter short positions.
TF : 4H
Entry : $1.094
Target : $0.917
SL : $1.202
#ALPINE/USDT analysis -
#ALPINE is in a downtrend. It is currently experiencing a pullback while finding support over the trendline. Wait for the price to break the trendline for a short entry as the price is expected to face resistance from the 200 EMA and continue its bearish momentum.
TF : 1H
Entry : $1.055
Target : $0.927
SL : $1.124