RAG System Design — How to Search Podcast Transcripts
Description:
Walk through the complete architecture of a production RAG API before building it. Covers the ingestion flow, query flow, and all five components — FastAPI, PostgreSQL, Qdrant, OpenAI Embeddings, and GPT-4o — working together to answer questions over podcast transcripts.
Hashtags:
#RAG #FastAPI #AIArchitecture #VectorSearch #LLM
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: RAG Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
How to build a production RAG pipeline in Python (without a vector database)
Dev.to · Ayi NEDJIMI
Architecting Sub-150ms Hybrid RAG for Voice Agents: Combining pgvector, BM25, and Async FastAPI…
Medium · Python
Security Controls in Enterprise RAG: Keys, Audit Logs, and the Hierarchy That Prevents Role Elevation
Dev.to · Manjunath
Four Metrics That Actually Tell You Whether Your Enterprise RAG Is Working
Dev.to · Manjunath
🎓
Tutor Explanation
DeepCamp AI