Q.10 Design a PDF Q&A System Using LLM

In this video, we design a complete PDF Q&A System using LLMs and RAG (Retrieval-Augmented Generation).

You’ll learn how modern AI systems can:
✅ Upload and process PDFs
✅ Extract text using OCR
✅ Generate embeddings
✅ Store vectors in Pinecone
✅ Perform semantic search
✅ Retrieve relevant chunks
✅ Use LLMs like GPT for accurate answers
✅ Reduce hallucinations using RAG
✅ Scale for enterprise-level workloads

We also cover:
🔹 Chunking strategies
🔹 Vector databases
🔹 Similarity search
🔹 Metadata filtering
🔹 Hybrid search (BM25 + Vector Search)
🔹 Reranking
🔹 Security & RBAC
🔹 Async ingestion pipelines
🔹 Scalability bottlenecks and solutions

Tech Stack Covered:

* React
* Java / Spring Boot
* Kafka
* Pinecone
* Tesseract OCR
* Amazon S3
* GPT / LLMs

Perfect for:
✔ System Design Interviews
✔ AI Engineers
✔ Backend Developers
✔ GenAI Architects
✔ Software Engineers preparing for senior/principal roles

#LLM #RAG #SystemDesign #AI #GenerativeAI #VectorDatabase #Pinecone #PDFChatbot #GPT #SoftwareArchitecture

Видео Q.10 Design a PDF Q&A System Using LLM канала Learning With Chetna