Revolutionize Document Search with AI-Powered RAG Solutions

Revolutionize Document Search with AI-Powered RAG SolutionsRevolutionize Document Search with AI-Powered RAG Solutions

The network for creativity

Join 1.25M professional creatives like you

Connect with clients, get discovered, and run your business 100% commission-free

Creatives on Contra have earned over $150M and we are just getting started

Back to feedPost

UMAR ASHFAQ

• 15h

Short Description

Built a production-ready Retrieval-Augmented Generation (RAG) application that enables users to upload PDF documents and ask natural language questions. The system retrieves relevant information from uploaded documents and generates accurate, context-aware responses using Groq's Llama 3.1 model.

Overview

This application helps users search and understand documents using AI instead of manually reading through PDFs. Users simply upload a document, ask questions in natural language, and receive intelligent answers based on the document's content.

Key Features

Upload and process PDF documents

AI-powered document search

Natural language question answering

RAG (Retrieval-Augmented Generation)

Chat history during the session

Fast AI responses using Groq

Modern Streamlit interface

Document statistics and metadata

Production-ready architecture

Technologies Used

Python

Streamlit

Groq API

Llama 3.1 8B

RAG Architecture

PyPDF2

Hugging Face Spaces

GitHub

My Role

Designed and developed the complete application, including:

PDF ingestion pipeline

Document text extraction

RAG workflow implementation

LLM integration using Groq

Streamlit user interface

Deployment on Hugging Face Spaces

Documentation and GitHub repository

Business Value

This solution enables businesses, students, and professionals to quickly retrieve information from large documents, reducing manual effort and improving productivity through AI-powered document understanding.

Live Demo

Add your Hugging Face Space:

https://huggingface.co/spaces/Umar519/intelligent-document-search

Hugging Face AI Agent Designer AI Automation AI Engineer Python Visual Studio Code

Bisrat Girma

• Jun 30

🔥 a well performing Prediction marketplace

Product Management AI Development AI Engineer Google Antigravity TypeScript Visual Studio Code

Sebastian F. T.

• Jun 30

Stop copy-pasting. Start automating. 🚀

If your team is still spending hours manually tracking competitor prices, scrolling through real estate portals, or copying company data into your CRM—you are losing both time and market share.

Data is the fuel for modern business, but raw web data is messy, fragmented, and hard to capture.

As a Data Automation & OSINT Engineer, I build custom, under-the-radar Python pipelines that do the heavy lifting for you. I transform chaotic public web data into clean, structured, and "CRM-ready" intelligence.

Here is what I’ve been building lately:

📊 Pricing Intelligence: Real-time telecom scrapers that map competitor device bundles and trigger automatic alerts on "Price Drops".

🏠 Market Intelligence: High-frequency real estate harvesters that isolate market anomalies and flag undervalued properties instantly.

🛡️ B2B Enrichment: Backend pipelines interfacing directly with official financial registries for instant corporate KYC validation.

My goal? To take repetitive, soul-crushing data tasks off your plate so you can focus entirely on strategy and growth.

📂 Check out my updated portfolio to see my live dashboards and automated architectures.

Are you looking to automate a specific data pipeline for your business? Let's connect and chat in the DMs! 👇

#DataAutomation #WebScraping #OSINT #Python #FreelanceDeveloper #GrowthHacking:

Web Scraping Python Data Engineering

Vasile Bratu

• Jun 30

Built a custom Python B2B lead generation tool that scrapes business directories, bypasses Cloudflare/WAF bot-detection using curl_cffi and Playwright, and syncs verified leads in real-time to Google Sheets for outreach campaigns.