What is Vector database?Vector database kya hai?

🧸 Think of it likeAise samjho

Like a library arranged by meaning instead of title, so books about the same idea sit on the same shelf.Title ki jagah matlab ke hisaab se lagi library jaisa, taaki ek hi idea wali kitaabein ek shelf pe hon.

📘 ExplainedVistaar se

It stores vectors with their text and metadata and uses approximate nearest neighbour indexes to search millions quickly, with filters for permissions, dates or departments. Options include pgvector in PostgreSQL and dedicated vector databases. It's the storage layer for RAG.Yeh vectors ko unke text aur metadata ke saath rakhta hai aur approximate nearest neighbour indexes se laakhon mein jaldi search karta hai, permissions, dates ya departments ke filters ke saath. Options: PostgreSQL mein pgvector aur dedicated vector databases. Yeh RAG ki storage layer hai.

💡 Real exampleAsli example

Storing 25,000 policy chunks and finding the 5 most relevant in 30 ms.25,000 policy chunks store karna aur 30 ms mein 5 sabse relevant dhoondhna.

📖 Learn it step by stepStep by step seekho

• Embeddings and vector databases: searching by meaningEmbeddings aur vector databases: matlab se search karna
• RAG: letting an LLM answer from your documentsRAG: LLM ko aapke documents se jawaab dene dena

🔗 Related termsJude hue shabd

• EmbeddingA list of numbers that captures the meaning of text, images or items, so similar meanings are close together.Numbers ki list jo text, images ya items ka matlab pakadti hai, taaki milte julte matlab paas paas hon.
• RAGLetting an LLM answer from your documents: search for relevant passages first, then generate an answer from them with citations.LLM ko aapke documents se jawaab dene dena: pehle relevant hisse dhoondho, phir unhi se citations ke saath jawaab banao.
• Semantic searchSearching by meaning rather than exact words, using embeddings.Exact shabdon ke bajaye matlab se search karna, embeddings ki madad se.