readme

README.md

@@ -1,11 +1,75 @@
----
-title: Sepsis Classic
-emoji: 💻
-colorFrom: yellow
-colorTo: indigo
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Sepsis Prediction API
+
+This repository contains a FastAPI-based web application that provides an API for predicting sepsis disease in patients based on input features. The API leverages a machine learning model trained on relevant data. The API allows users to submit patient data and receive a prediction along with confidence scores.
+
+## Getting Started
+
+To get started with the Sepsis Prediction API, follow the steps below:
+
+### Prerequisites
+
+- Docker: Make sure you have Docker installed on your machine.
+
+### Installation
+
+1. Clone this repository to your local machine:
+
+   ```bash
+   git clone https:https://huggingface.co/UholoDala
+
+2. Navigate to the repository directory:
+    cd sepsis_classic
+
+3. Build the Docker image:
+    docker build -t sepsis-prediction-api .
+
+4. Run the Docker container:
+    docker run -d -p 7860:7860 sepsis-prediction-api
+
+The API will now be accessible at http://localhost:7860.
+
+## API Endpoints
+
+### Root Endpoint
+    - URL: http://localhost:7860/
+    - Method: GET
+    - Description: Provides basic information about the Sepsis Prediction API.
+
+### Sepsis Classification Endpoint
+    - URL: http://localhost:7860/spaces/UholoDala/sepsis_classic/classify
+    - Method: POST
+    - Description: Accepts patient data and performs sepsis classification. Provides the prediction and confidence scores.
+
+## Usage
+You can interact with the API using tools like curl, web browsers, or API testing tools like Postman.
+
+### Example curl command to perform sepsis classification:
+    curl -X POST -H "Content-Type: application/json" -d '{
+  "PlasmaGlucose": 120,
+  "BloodWorkResult_1": 4,
+  "BloodPressure": 80,
+  "BloodWorkResult_2": 7,
+  "BloodWorkResult_3": 9,
+  "BodyMassIndex": 25.5,
+  "BloodWorkResult_4": 12.5,
+  "Age": 50
+}' http://localhost:7860/spaces/UholoDala/sepsis_classic/classify
+
+## Dependencies
+    - pytest
+    - scikit-learn
+    - fastapi[all]
+    - pydantic
+    - uvicorn
+    - pypi-json
+    - requests
+    - pandas
+    - tabulate
+
+This project is licensed under the MIT License.
+
+## Acknowledgments
+This project was developed as part of the Azubi Africa Data Analysis LP6 Project. We would like to thank all contributors for their valuable insights and efforts.
+
+For more information, feel free to contact me at [email protected] or [email protected].
+