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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."}' |