metadata

license: apache-2.0
title: FastAPI-Docker-Very-Basic-Sentiment-Analysis
sdk: docker
emoji: 💻
colorFrom: blue
colorTo: purple
short_description: This API utilizes a machine learning model to analyze text.

Very Basic Sentiment Analysis API

Introduction
Overview
Dependencies
Installation
Usage
Testing
Hugging Face Space
Contributors
License

Introduction

This API utilizes a machine learning model to analyze text for sentiment, categorizing input as positive, negative, or neutral. It leverages a pre-trained BERT model from Hugging Face Transformers, integrated within a FastAPI framework to provide quick and reliable sentiment analysis.

Overview

This project was developed to demonstrate the ability to deploy a machine learning model using FastAPI and Docker, making it accessible as a web API. The sentiment analysis model used is based on BERT, a transformer model pre-trained on a large corpus of text and fine-tuned for sentiment analysis.

Dependencies

FastAPI: A modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints.
Docker: A set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers.
Pydantic: Data validation and settings management using python type annotations.
Hugging Face Transformers: Provides thousands of pre-trained models to perform tasks on texts such as classification, information extraction, question answering, summarization, translation, text generation, etc in 100+ languages. This project specifically utilizes the Sentiment Analysis BERT model by MarieAngeA13 for analyzing text sentiment.
pytest: A framework that makes it easy to write simple tests yet scales to support complex functional testing.

Installation

Follow these instructions to set up the API locally:

Clone the repository

git clone https://github.com/abdoolamunir/very-basic-sentiment-analysis.git
cd very-basic-sentiment-analysis

Build the Docker Container

This command builds the Docker container, which includes installing all the necessary dependencies from 'requirements.txt'.

docker build -t sentiment-analysis-api .

Run the Docker container

docker run -p 8000:8000 sentiment-analysis-api

Usage

After Launching the API, you can use it as follows:

Open Swagger UI

http://localhost:8000/docs

Analyze text sentiment

To analyze the text sentiment, send a POST requent:

curl -X 'POST' \
  'http://localhost:8000/analyze' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{"text": "This product is great!"}'

Example Response

{
  "result": [
    {
      "label": "POSITIVE",
      "score": 0.9999
    }
  ]
}

Testing

To run the tests, execute the following command:

pytest

Hugging Face Space

The API is also deployed on Hugging Face Spaces. You can access it here:

Contributors

Abdullah Munir & anyone who wants to use this basic framework and add onto it :)

License

This project is released under the Apache License 2.0. See the LICENSE file in the repository for more details.

Spaces:

abdoolamunir
/

very-basic-sentiment-analysis

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