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Pdf Document Q&a (rag) project in Python.

Python project   Last updated on - March 10, 2026
langchain rag pdf faiss openai vector-store python embeddings
Ayush Pal
Ayush Pal
Python Java Data Science Machine Learning C Cpp HTML CSS JS 
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In this page Pdf Document Q&a (rag) project is a desktop application which is developed in Python platform. This Python project with tutorial and guide for developing a code. Pdf Document Q&a (rag) is a open source you can Download zip and edit as per you need. If you want more latest Python projects here. This is simple and basic level small project for learning purpose. Also you can modified this system as per your requriments and develop a perfect advance level project. This project can edit using a Visual Studio Code IDE. Following Python project contains all the important features which can be in use for the BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering, Computer Science students and Devloper for their college projects. This script developed by Ayush Pal. This desktop application 100% working smooth without any bug. It is developed using NA and Database FAISS Vector Store. This software code helpful in academic projects and research paper for final year computer science. To download Pdf Document Q&a (rag) project in Python with source code files, please scroll down to the bottom of this page for the Download Zip file of source code button.

About project

project Name

Pdf Document Q&a (rag)

Project Complexityadvanced
Duration10 Days
project ID13260
Developer NameAyush Pal
Publish DateMarch 10, 2026
project PlatformPython
Programming LanguageFor this particular Python project, NA is required
Front EndCLI Terminal Interface
Back EndPython, LangChain, OpenAI Embeddings, FAISS
IDE ToolVisual Studio Code
Database IntegrationFAISS Vector Store
project Typedesktop Application
No of project Download0
project Total View15
Today Trends16
Current Month Trends16
Last Month Trends0

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Features of the Pdf Document Q&a (rag) project

We will implement the following feature in the Python Pdf Document Q&a (rag) Project:
Upload any PDF and ask natural language questions about it using Retrieval-Augmented Generation. The program splits the PDF into chunks, embeds them into a FAISS vector store, and retrieves the most relevant sections to answer each question accurately. Key features include PDF ingestion and smart chunking, semantic search via FAISS vector store, source page citations with every answer, support for large documents beyond model context window.

User modules and function of Pdf Document Q&a (rag)

We will implement the following functionalities in the Python Pdf Document Q&a (rag) Project:
User provides a PDF file path at startup. The system indexes the document automatically. User then asks unlimited questions about the document and receives accurate answers grounded strictly in document content with page number citations shown.

Software requirement to run this project

Python 3.10 or later Visual Studio Code IDE OpenAI API Key pip install langchain langchain-openai faiss-cpu pypdf Operating System: Windows 10 / Windows 11

Hardware requirement to run this project

1. Laptop or Desktop 2. Minimum 4GB RAM 3. Minimum 2GB HDD 4. Active Internet Connection

How to install the project?

After you finish downloading the project, unzip the project file.

Step 1 : Download and extract the zip file to your desired folder

Step 2 : Install Python 3.10 or later from python.org

Step 3 : Open Visual Studio Code and click File -> Open Folder -> select extracted folder

Step 4 : Open terminal in VS Code by clicking Terminal -> New Terminal

Step 5 : Run command: pip install langchain langchain-openai faiss-cpu pypdf

Step 6 : Open file 02_pdf_document_qa.py and replace YOUR_OPENAI_API_KEY_HERE with your real API key

Step 7 : Set PDF_PATH variable to your PDF file path then run: python 02_pdf_document_qa.py

How to import database?

Step 1 : This project uses FAISS as an in-memory vector database — no installation needed

Step 2 : Prepare any PDF file you want to query

Step 3 : Place the PDF file in the same folder as the Python script

Step 4 : Open 02_pdf_document_qa.py and update PDF_PATH = "your_document.pdf" with your filename

Step 5 : Run the program — FAISS index is built automatically from your PDF on every run

Why a download Pdf Document Q&a (rag) project from kashipara?

Downloading the Pdf Document Q&a (rag) project from Kashipara is a best choice for students, beginners, and developers looking for a reliable, well documented, and ready to use project in Python.

Top benifit to Download our project over other website:

  • Our Pdf Document Q&a (rag) Source Code in Python completly working. This project easy to understand and fully customizable as per your requriments.
  • Free Download our Pdf Document Q&a (rag) projects.
  • Comprehensive Documentation:
    • We provide project Synopsis
    • Pdf Document Q&a (rag) project Abstract in PDF and PPT formats download in reports.
    • Detailed Project Report
  • UML & Technical Diagrams Included:
  • This project Ideal for Academic Projects Perfect for B.E., B.Tech, MCA, BCA, BSc CS, and IT students
  • 100% Working Project – Tested and bug free.
  • Developed for Learning & Research – A strong foundation for building advanced Pdf Document Q&a (rag) applications

How to create diagram?

Creating diagrams like Class Diagrams, Use Case Diagrams, Entity–Relationship (ER) Diagrams, Data Flow Diagrams (DFD), and Sequence Diagrams is essential for designing and understanding software systems. Here’s a proper guide to help you get started with each type:

Pdf Document Q&a (rag) project output screen

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