#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
🤔#LDO Financial indicators for Lido in 2025 show that total revenue decreased by 23% on an annual basis to $40.5 million, with net staking commission revenue amounting to $37.4 million.
The DAO is evaluating a potential LDO buyback program in the second quarter of 2026. link
#LDO/USDT analysis :
#LDO is in a downtrend, currently rejecting from the 200 EMA resistance after going through a correction phase. It is expected to continue its bearish momentum and test the previous swing low. Wait for the break of the $1.091 level downside for a short entry.
TF : 15min
Entry : $1.091
Target : $0.993
SL : $1.153
#LDO/USDT analysis -
#LDO has recently broken out of the channel after facing rejection from the 200 EMA in a downtrend. It is now expected to continue its downward momentum and test new lows.
TF : 2H
Entry : $1.530
Target : $1.398
SL : $1.604