🔍 Information Retrieval System — Streamlit App

This project is a full-featured Information Retrieval (IR) demo web app built using Python and Streamlit. It showcases classical NLP and IR techniques such as TF–IDF vectorization, cosine similarity search, and LDA-based topic modeling, all presented through an interactive interface with real-time visualizations.

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🚀 Features

• ✅ TF–IDF + Cosine Similarity for ranking document relevance
• 🧠 LDA (Latent Dirichlet Allocation) for unsupervised topic modeling
• 📊 Interactive visualizations using Plotly and WordCloud
• 🗂️ Multiple document input modes: sample docs, uploaded .txt file, or manual entry
• ⚙️ Built-in preprocessing: stopword removal, stemming, case-folding
• 🧼 Robust handling of empty input, offline NLTK setup, and session-safe document management

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📁 Project Structure

Information-Retrieval-System/ ├── app/ │ ├── main.py # Core logic and Streamlit backend │ ├── test.py # Streamlit UI entry point │ ├── test.txt # Sample document lines ├── tools/ │ ├── bing_tool.py # (Optional) Search engine tool │ ├── google_tool.py │ ├── yahoo_tool.py ├── agent.py # (Optional) Custom agent logic ├── summarizer.py # (Optional) Summarization logic ├── README.md ├── requirements.txt

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🛠️ Installation

1. Clone this repository

git clone https://github.com/tzprograms/Information-Retrieval-System.git
cd Information-Retrieval-System

Install
pip install streamlit scikit-learn nltk wordcloud plotly matplotlib pandas numpy
streamlit run app/test.py