📝 TEXT-SUMMARIZATION-TOOL COMPANY: CODTECH IT SOLUTIONS PVT. LTD
NAME: Limbani Uttam Bharatbhai
INTERN ID: CT04DG2987
DOMAIN: Artificial Intelligence
DURATION: 4 WEEKS
MENTOR: NEELA SANTOSH
This repository contains a minimal yet powerful Python-based application that performs automatic text summarization using a local language model (LLM) via Ollama and the LangChain framework. It leverages the Phi-3 language model, one of the most efficient and compact open-source models, to summarize long pieces of text into concise, human-readable summaries. This solution is lightweight, easy to run locally, and ideal for research, education, or integration into larger AI workflows.
🧠 Project Description As the volume of digital content continues to grow, the ability to quickly extract meaningful information from long documents becomes increasingly important. Whether you're dealing with:
Research papers
News articles
Documentation
Reports
Summarization helps reduce cognitive overload by presenting essential information in a much shorter form.
🧩 Key Features This project demonstrates a local-first AI solution that achieves this goal by combining:
Phi-3 language model (via Ollama)
LangChain for prompt construction and orchestration
It is a perfect starting point for developers, students, and researchers who want to:
✅ Build custom summarization workflows ✅ Learn how to run LLMs locally with minimal setup ✅ Avoid cloud dependency and maintain data privacy
⚙️ Application Flow A long input text is passed to the summarization function.
A summarization prompt is generated using LangChain’s PromptTemplate.
The prompt is sent to the Phi-3 model running locally via Ollama.
The model returns a concise summary.
The output can be printed, stored, or integrated into another system.
🔒 Privacy and Efficiency This tool avoids using external cloud APIs, making it:
Privacy-friendly (no data sent outside your machine)
Cost-effective (no API subscription required)
Offline-capable, ideal for local servers, research labs, or edge devices
📌 Output
