Скачать или смотреть Local RAG PDF Chatbot with LangChain, FAISS & Ollama | PDF Question Answering Demo

In this video, I demonstrate a PDF‑based Question Answering system built using a Retrieval‑Augmented Generation (RAG) pipeline.
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The app lets you upload any PDF and ask questions whose answers are generated only from the document content, powered by a local LLM running through Ollama.
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🔗 GitHub Repository
https://github.com/Aakash109-hub/loca...

🧠 What this RAG app does

Upload a PDF and chat with it using natural language
Retrieves the most relevant chunks from the document using vector search
Generates grounded answers from a local LLM instead of calling cloud APIs
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​🛠 Tech stack used

PyPDFLoader for loading PDF documents
RecursiveCharacterTextSplitter for smart text chunking
HuggingFace sentence‑transformer embeddings for vector representations
​- FAISS as the vector database for fast similarity search
​- LangChain to orchestrate the RAG pipeline (retrieval + generation)
​- Ollama for local LLM‑based answer generation
​- Streamlit for the web user interface

🎯 Who this video is for
Developers and students exploring RAG and PDF Question Answering
Anyone interested in running local LLMs for privacy‑friendly document QA
​- Recruiters reviewing my AI/ML projects and practical GenAI skills