Update README.md

README.md

@@ -1,42 +1,50 @@
-# Sentiment Analysis API
-![alt text](image.png)
-
-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."}'
+title: SAMH
+emoji: 📚
+colorFrom: indigo
+colorTo: blue
+sdk: docker
+pinned: false
+license: apache-2.0
+
+# Sentiment Analysis API
+![alt text](image.png)
+
+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."}'