AIAdvanced#Infrastructure#Data
RAG (Retrieval-Augmented Generation)
R
Definition
An AI framework that allows LLMs to pull real-time data from external sources (blockchains/news) before generating a response.
Verified by CryptoLV Alpha
Concept Diagram
Key Takeaways
1
RAG lets AI agents access real-time external data instead of relying on static training
2
The process follows search-retrieve-generate to incorporate live facts into responses
3
Prevents AI hallucination by grounding answers in actual current data
4
Transforms chatbots into professional trading assistants with live market awareness
Practical Example
When you ask 'What's Bitcoin's current dominance?', the CryptoLV agent uses RAG to fetch live CoinGecko data, retrieves the 58.3% figure, and generates an answer with the real-time number.
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Related Terms
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LLM ReasoningThe process by which an AI agent uses large language models (like DeepSeek or Claude) to parse news and market data into trading decisions.
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Context WindowThe maximum amount of information (tokens) an AI model can 'remember' and process at any single moment during reasoning.
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Prompt EngineeringThe art of crafting specific text inputs to get more accurate or specialized behavior from an AI agent.
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Vector DatabaseA specialized database used by AI agents to store and search massive amounts of unstructured data as numerical vectors.
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