Chain of Thought – A Query Transformation Technique for Advanced RAG
Less Abstract Approach
Apr 23, 20253 min read378
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Reciprocal Rank Fusion – A Query Transformation Technique for Advanced RAG
RAG Fusion Approach
Apr 23, 20254 min read159
Hypothetical Document Embeddings (HyDE) – A Query Transformation Technique for Advanced RAG
HyDE generates a hypothetical document ( based on Pre-Trained Knowledge of LLM ), from User Query, then instead of creating vector embeddings of user query and search in our vector database, it creates embeddings of that hypothetical Document , and f...
Apr 22, 20253 min read101
Query ROUTING (logical & semantic concepts) + Graph Database
In Retrieval-Augmented Generation, success depends on more than just good data — it’s about choosing the smartest routes for storage, search, and retrieval. Every step, from indexing information to delivering answers, can be optimized. Query Routing ...
Apr 22, 20257 min read147
Parallel Query Retrieval – A Query Transformation Technique for Advanced RAG
Fan Out Approach
Apr 21, 20253 min read96
Advanced RAG - Overview
Advanced RAG : Rag with optimization , to make Response more Accurate for User . RAG is Retrieval-Augmented Generation , its basically Retrieving (Fetching) Relevant information from some External data source and providing it as a context to LLMs, Au...
Apr 19, 20253 min read183
Unlocking the Power of RAG: Enhancing AI with Retrieval-Augmented Generation
Terms Covered: RAG , Ingestion/ Indexing, Retrieval , Context Window , Chunking, Embeddings, Vector Embeddings, LLM Model , Vector databases, Meta-data , Prompt , LangChain, RAGTools What is RAG ❓ Retrieval-Augmented Generation Its basically, Retrie...
Apr 17, 20257 min read125