Family, here goes a bit more knowledge
What is a RAG system?
(for its acronym in English: Retrieval-Augmented Generation) is an artificial intelligence architecture that combines information retrieval with text generation, and is especially useful for answering complex questions or generating texts based on external documents.
How does a RAG system work?
The system has two main components:
1. Retrieval:
The model searches (retrieves) relevant information from a database, documents, or external sources (for example, articles, PDFs, vector databases, etc.).
2. Generation:
Then, a language model (like GPT) uses that retrieved information to generate a coherent, accurate, and contextual response.
Summarized process:
1. The user asks a question.
2. The system searches for relevant content in a database or text corpus.
3. The model combines that information with its prior knowledge to generate an accurate response.
What is RAG used for?
Intelligent chatbots (customer service, health, education).
Legal or financial assistants.
Personalized AI with your documents.
Enhanced search systems (for example, AI search engines).
Advantages of RAG
More accurate and up-to-date responses.
Allows working with customized databases.
Reduces the model's "hallucination" (errors or inventions).
Blessings and successes
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