Skip to content

Latest commit

 

History

History
96 lines (65 loc) · 3.55 KB

README.md

File metadata and controls

96 lines (65 loc) · 3.55 KB
Raw

sentiment-analysis-api

A Simple PoC (Proof of Concept) of Sentiment Analysis API Server. API server currently using cardiffnlp/twitter-roberta-base-sentiment-latest model for sentiment analysis. cardiffnlp/twitter-roberta-base-sentiment-latest or TimeLM-21 achieves top score 73.7 in Macro Averaged-Recall metric and becomes top state-of-the-art model in sentiment analysis for twitter/social media text.

sentiment-analysis-api is a core dependency of nostr-filter-relay.

Demo

A demo gradio instance is available on HuggingFace Spaces - https://huggingface.co/spaces/rifatramadhani/sentiment-analysis.

Getting Started

You can start by cloning this repository to run or modify it locally

git clone https://github.com/atrifat/sentiment-analysis-api
cd sentiment-analysis-api

Create virtual environment using venv, pyenv, or conda. This is an example using venv to create and activate the environment:

python3 -m venv venv
source venv/bin/activate

install its dependencies

pip install -U -r requirements.txt

and run it using command

python3 app.py

You can also copy .env.example to .env file and change the environment value based on your needs before running the app.

There is also Dockerfile available if you want to build docker image locally. If you don't want to build docker image locally, you can use the published version in ghcr.io/atrifat/sentiment-analysis-api.

Run it:

docker run --init --env-file .env -p 5000:5000 -it ghcr.io/atrifat/sentiment-analysis-api

or run it in the background (daemon):

docker run --init --env-file .env -p 5000:5000 -it --name sentiment-analysis-api -d ghcr.io/atrifat/sentiment-analysis-api

If you want to test the API server, you can use GUI tools like Postman or using curl.

curl --header "Content-Type: application/json" \
  --request POST \
  --data '{"api_key":"your_own_api_key_if_you_set_them", "q":"hello world good morning"}' \
  http://localhost:5000/predict

The result of classification will be shown as follow:

{"negative":0.007959462702274323,"neutral":0.04862939938902855,"positive":0.943411111831665}

License

MIT License

Copyright (c) 2024 Rif'at Ahdi Ramadhani

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Author

Rif'at Ahdi Ramadhani (atrifat)