#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
#AMP/USDT analysis :
#AMP is currently exhibiting an uptrend, consistently reaching new highs while trading above the 200 EMA. The price is now retracing toward the 200 EMA and a significant support level.
It is expected that the price will test this zone and subsequently rebound, which will allow the bullish momentum to persist and potentially lead to a retest of previous highs.
TF : 1D
Entry : $0.006750
Target : $0.011915
SL : $0.004950
#AMP/USDT analysis :
#AMP has broken above a previously tested resistance level and has bounced back after a retest. This suggests a continuation of its bullish momentum, with the price likely to test previous highs from the current level.
TF : 1D
Entry : $0.005420
Target : $0.013400
SL : $0.004180
#AMP has a trading range on 12H Time frame, we expect a good pump from bottom of this range,also after breakup will have another bullish movement again
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