𝗛𝗼𝘄 𝗜 𝗠𝗮𝗱𝗲 𝗠𝘆 𝗔𝗜 𝗣𝗗𝗙 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗼𝗿 𝗦𝗺𝗮𝗿𝘁

𝗛𝗼𝘄 𝗜 𝗠𝗮𝗱𝗲 𝗠𝘆 𝗔𝗜 𝗣𝗗𝗙 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗼𝗿 𝗦𝗺𝗮𝗿𝘁

You want to chat with a PDF. You upload a document and ask questions.

Sending a whole PDF to an AI fails. The AI misses details. It makes things up.

I used RAG. This is Retrieval-Augmented Generation.

It works like an open-book exam. You do not memorize the book. You find the right page and answer.

Here is the process:

• Extract text from the PDF.
• Split text into small pieces. These are chunks.
• Add overlap between chunks to keep context.
• Turn chunks into numbers. These are embeddings.
• Store them in a vector database like Pinecone.

When you ask a question:

• The AI turns your question into a vector.
• It finds chunks with similar meaning.
• It sends only these chunks to the AI.

I learned three things:

• Similarity thresholds stop lies. If the match is poor, the AI says I do not know.
• HyDE improves results. The AI writes a fake answer first to find the right text.
• Chunking is key. It matters more than the AI model.

RAG lets AI use private data. It stops hallucinations.

Source: https://dev.to/abinash1417/how-i-used-rag-to-make-my-ai-pdf-generator-actually-smart-7h4 Optional learning community: https://t.me/GyaanSetuAi