Build RAG AI App | Summarization & Suggestion for 5 Questions from Uploa...

Build RAG AI App | Summarization & Suggestion for 5 Questions from Uploaded PDF through LLMs | Part8

In this video, we take our previous RAG (Retrieval Augmented Generation) application and evolve it into a more sophisticated "Intelligent System" or "AI Agent" for interacting with PDFs. Using the powerful combination of LangChain, Pinecone, and Google Gemini, wrapped in a dynamic Gradio interface, we build an app where users can:

✅ Upload a PDF: A dedicated step to ingest your document.

✅ Process Intelligently: The system acts as an agent to automatically load, split, embed, and index the PDF content into Pinecone.

✅ Generate Insights: Immediately after processing, the system generates a concise summary of the document and suggests 5 key questions it can answer with LLMs.

✅ Ask Questions: A separate interface allows users to query the processed PDF content using the RAG pipeline.

By the end of video, you should be able to have working application that can 

✅ Summarize PDF content

✅ Generate intelligent suggested questions

✅ Use AI to provide context-aware answers

✅ Work as a user-friendly AI assistant for document understanding

We'll write the code from scratch (or build upon the previous version), explaining each step:

👉 Setting up the project and API keys (.env, config.py) - Already covered.

👉 Implementing the PDF loading, text splitting, and embedding logic using LangChain and Google Generative AI Embeddings (Already covered but have few changes like split functions into smaller functions).

👉 Storing the vector embeddings in Pinecone for efficient retrieval.

👉 Developing prompt strategies for RAG Q&A, document summarization, and question generation.

👉 Connecting these components using LangChain principles (LCEL i.e. LangChain Expression Language) to create distinct "agent" workflows (processing agent, querying agent).

👉 Structuring the Gradio UI with gr.Blocks and separate tabs for clear workflow for process PDF & Ask Questions.

👉 Making the Gradio interface interactive to trigger these different processes.

This tutorial will show you how to create a multi-functional AI application that goes beyond simple chat!

💡 Whether you're a beginner or an AI enthusiast, this project-based series will guide you to build your own AI-powered document Q&A system.