YouTube tutorial sequence to construct a RAG system with PDF doc assist utilizing Streamlit, Pinecone, LangChain, and Gemini.
The construction assumes no technical background and guides viewers step-by-step towards constructing a working AI-powered app
by the top.
Half 1: What’s RAG? (And Why It’s Superior for PDF Q&A)
• Clarify RAG in easy phrases utilizing real-life examples (like a sensible librarian).
• Use diagrams to point out how knowledge strikes from PDF → Vector DB → LLM.
• Demo the ultimate app to construct pleasure.
• Instruments overview: Streamlit, Pinecone, LangChain, Google GenAI Fashions API
Half 2: Undertaking Setup — Instruments You’ll Want
• Putting in Python, establishing digital atmosphere
• Putting in required packages (pip set up streamlit pinecone-client langchain …)
• Organising .env file for Pinecone and Google Gemini API keys
• Folder construction walkthrough (easy rationalization)
Half 3: Add & Course of PDF Recordsdata (Person-Pleasant)
• ✨ Use the rag_app_v2.py interface to add information
• The place PDFs are saved
• What occurs behind the scenes when PDFs are uploaded
• What “chunking” means and why it’s wanted (defined merely)
Half 4: Embedding PDFs into Pinecone (No Hardcoding!)
• Introduction to Vector Embeddings (with visuals)
• Clarify how LangChain + Google Gemini turns your docs into AI-searchable chunks
• Step via add_new_documents_to_index() logic
• Simple breakdown of chunking logic and importing to Pinecone
Half 5: Construct the Mind — Creating the RAG Chain
• What’s a “RAG Chain”?
• Dissecting create_rag_chain() step-by-step
• Gemini mannequin, immediate template, retriever — how they speak to one another
• Easy walkthrough of how the app solutions questions from listed PDFs
Half 6: Constructing the Frontend with Streamlit
• Walkthrough of rag_app_v2.py interface
• Customizing format and inputs for non-tech customers
• Actual-time querying and answering — reside take a look at
Half 7: Deploy Your AI PDF Chat App (FREE!)
• Utilizing platforms like Streamlit Cloud or Render
• Managing atmosphere variables safely
• Share your app with the world!
Bonus Half: Bettering Reply High quality & Debugging Suggestions
• Tweak immediate template for higher solutions
• Frequent errors and how one can repair them
• How you can monitor utilization and efficiency
By the top of the sequence, viewers will have the ability to:
✅ Add any PDF
✅ Search and chat with its content material utilizing AI
✅ Perceive what occurs behind the scenes
✅ Deploy their very own customized Q&A app
