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Repository for Project Insight: NLP as a Service
| Date | Stars |
|---|---|
| 2026-07-24 | 320 |
| 2026-07-25 | 320 |
| 2026-07-28 | 320 |
| 2026-07-30 | 320 |
| 2026-08-06 | 320 |
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<h1 align="center">Project Insight</h1>
<h2 align="center">NLP as a Service</h2>
<p align="center">
<img alt="Project Insight" src="meta/Insight.png">
</p>
<p align="center">
<a href="https://github.com/abhimishra91/insight/issues"><img alt="GitHub issues" src="https://img.shields.io/github/issues/abhimishra91/insight"></a>
<a href="https://github.com/abhimishra91/insight/network"><img alt="GitHub forks" src="https://img.shields.io/github/forks/abhimishra91/insight"></a>
<a href="https://github.com/abhimishra91/insight/stargazers"><img alt="Github Stars" src="https://img.shields.io/github/stars/abhimishra91/insight"></a>
<a href="https://github.com/abhimishra91/insight/blob/master/LICENSE"><img alt="GitHub license" src="https://img.shields.io/github/license/abhimishra91/insight"></a>
<a href="https://github.com/abhimishra91/insight/"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
</p>
## Contents
1. [Introduction](#section01)
- [Features](#section01a)
2. [Installation](#section02)
- [Setup and Documentation](#section02a)
3. [Project Details](#section03)
- [Demonstration](#section03a)
- [Directory Details](#section03b)
- [How to Add a new Model](#section03c)
4. [License](#section04)
<a id='section01'></a>
## Introduction
Project Insight is designed to create NLP as a service with code base for both front end GUI (**`streamlit`**) and backend server (**`FastApi`**) the usage of transformers models on various downstream NLP task.
The downstream NLP tasks covered:
* News Classification
* Entity Recognition
* Sentiment Analysis
* Summarization
* Information Extraction `To Do`
The user can select different models from the drop down to run the inference.
The users can also directly use the backend fastapi server to have a command line inference.
<a id='section01a'></a>
### Features of the solution
* **Python Code Base**: Built using `Fastapi` and `Streamlit` making the complete code base in Python.
* **Expandable**: The backend is desinged in a way that it can be expanded with more Transformer based models and it will be available in the front end app automatically.
* **Micro-Services**: The backend is designed with a microservices architecture, with dockerfile for each service and leveraging on Nginx as a reverse proxy to each independently running service.
- This makes it easy to update, manitain, start, stop individual NLP services.
<a id='section02'></a>
## Installation
* Clone the Repo.
* Run the `Docker Compose` to spin up the **Fastapi** based backend service.
* Run the **Streamlit app** with the `streamlit run command`.
<a id='section02a'></a>
### Setup and Documentation
1. **Download the models**
- Download the models from [here](https://drive.google.com/drive/folders/1Lc7kvfNnMRgA7tkPR5zaSAoSjC2sCudI?usp=sharing)
- Save them in the specific model folders inside the `src_fastapi` folder.
2. **Running the backend service.**
- Go to the `src_fastapi` folder
- Run the `Docker Compose` comnand
```console
$ cd src_fastapi
src_fastapi:~$ sudo docker-compose up -d
```
3. **Running the frontend app.**
<!---
- Front end is a **`WIP`** as a change in the backend architecture.
- Should be up in a few days.
--->
- Go to the `src_streamlit` folder
<!---
- Create the docker image from the `Docker File`
- Then execute the docker image to spin up a container.
```console
$ cd src_streamlit
src_streamlit:~$ sudo docker build -t streamlit_app .
src_streamlit:~$ sudo docker run -d --name streamlit_app streamlit_app
```
--->
- Run the app with the streamlit run command
```console
$ cd src_streamlit
src_streamlit:~$ streamlit run NLPfily.py
```
4. **Access to Fastapi Documentation**: Since this is a microservice based design, every NLP task has its own seperate documentation
- News Classification: http://localhost:8080/apiExcerpt of 7,679 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:149f1e0cb90f47d0, topic:nlp, topic:natural-language-processing, readme:sentiment analysis
matched fp:149f1e0cb90f47d0, topic:transformer
matched fp:149f1e0cb90f47d0, topic:streamlit