Spaces:
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title: SAMH | |
emoji: ⚡ | |
colorFrom: purple | |
colorTo: blue | |
sdk: docker | |
pinned: true | |
license: mit | |
short_description: Sentment Analysis for Mental Health | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
# Sentiment Analysis API | |
 | |
This project provides a sentiment analysis API using FastAPI and a machine learning model trained on textual data. | |
## Features | |
- Data ingestion and preprocessing | |
- Model training and saving | |
- FastAPI application for serving predictions | |
- Dockerized for easy deployment | |
## Setup | |
### Prerequisites | |
- Docker installed on your system | |
### Build and Run | |
1. Build the Docker image: | |
```bash | |
docker build -t sentiment-analysis-api . | |
``` | |
2. Run the Docker container: | |
```bash | |
docker run -p 8000:8000 sentiment-analysis-api | |
``` | |
3. Access the API: | |
- Home: [http://localhost:8000](http://localhost:8000) | |
- Health Check: [http://localhost:8000/health](http://localhost:8000/health) | |
- Predict Sentiment: Use a POST request to [http://localhost:8000/predict_sentiment](http://localhost:8000/predict_sentiment) with a JSON body. | |
## Example cURL Command | |
```bash | |
curl -X POST "http://localhost:8000/predict_sentiment" -H "Content-Type: application/json" -d '{"text": "I love programming in Python."}' |