Fake News Detector

A machine learning-powered Fake News Detection system built with FastAPI, Docker, and Scikit-learn.

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Features

• Detects fake news using ML models (Logistic Regression, Random Forest, Gradient Boosting und Decision Tree)
• RESTful API with FastAPI
• Dockerized for easy deployment
• Swagger UI for API testing

API Endpoints

Method	Endpoint	Description
GET	/	Health check
POST	/predict/	Fake/Real prediction
POST	/set_model/	Switch ML model

Example Server Logs

These are example server logs when running the FastAPI app with Uvicorn:

INFO:     Started server process [1]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
INFO:     172.17.0.1:55626 - "GET /docs HTTP/1.1" 200 OK
INFO:     172.17.0.1:55626 - "GET /openapi.json HTTP/1.1" 200 OK
INFO:     172.17.0.1:55628 - "GET / HTTP/1.1" 200 OK
INFO:     172.17.0.1:56382 - "GET / HTTP/1.1" 200 OK
INFO:     172.17.0.1:64282 - "POST /predict/ HTTP/1.1" 200 OK
INFO:     172.17.0.1:59828 - "POST /predict/ HTTP/1.1" 422 Unprocessable Entity
INFO:     172.17.0.1:60682 - "POST /set_model/?model_name=RandomForest HTTP/1.1" 200 OK

Example Usage