ASArnab Sahaingenai-arnab.hashnode.dev路Sep 22, 2025 路 3 min readAdvanced RagsAdvanced RAGs (Retrieval-Augmented Generation) I explored advanced types of RAG frameworks beyond the basic architecture. These are designed to make retrieval more intelligent, context-aware, and adaptive. 1. Self RAG (sRAG) Concept: The model cri...00
ASArnab Sahaingenai-arnab.hashnode.dev路Sep 22, 2025 路 1 min readObservabilityLangSmith A developer tool/platform for managing and debugging LLM (Large Language Model) applications. Helps with tracing, monitoring, and evaluation of prompts and responses. LangFuse An open-source observability and analytics platform for LL...00
ASArnab Sahaingenai-arnab.hashnode.dev路Sep 22, 2025 路 7 min readRetrieval-Augmented Generation (RAG)What is RAG? RAG = a method to combine LLMs with external knowledge (usually your own data). LLMs are powerful, but: They have a knowledge cutoff. They may hallucinate answers if the info isn鈥檛 in their training data. RAG solves this by retrievin...00
ASArnab Sahaingenai-arnab.hashnode.dev路Sep 22, 2025 路 4 min readTool Calling with LLMs馃敼 What is Tool Calling? Definition: Tool calling is when LLMs (Large Language Models) are given access to external functions, APIs, or databases. Instead of hallucinating answers, the model decides: 馃憠 鈥淒o I know this? Or should I call a tool to...00
ASArnab Sahaingenai-arnab.hashnode.dev路Sep 22, 2025 路 6 min readWorking with LLMsUsing Groq LLMs Learned how to access and interact with Groq-hosted large language models. Advantage: high-speed, low-latency inference. API Keys How to generate and securely use API keys for authentication. Best practice: store in .env files ...00
