#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
#ETHFI
Here's a closer look at the technical analysis:
• Volume has been steadily increasing over the past three days.
• The 5-day Exponential Moving Average (EMA5) has crossed over the 20-day EMA, indicating a positive trend.
• While the Relative Strength Index (RSI) is high in lower time frames, it remains relatively low on the daily chart.
The price has broken out of resistance with significant volume. If it can sustain this momentum without retracing back into the previous range, there's potential for further upward movement