Introducing Toxicity Classifier API using FastAPI

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. It is easy to use and allows for creating APIs quickly and efficiently. In this article, we will introduce the Toxicity Classifier API using FastAPI.

What is the Toxicity Classifier API?

The Toxicity Classifier API is a machine learning model that classifies text into toxic and non-toxic categories. It can be used to automatically flag content that is potentially harmful or offensive. This API is based on a pre-trained model that has been trained on a large dataset of toxic and non-toxic text.

Using FastAPI for the Toxicity Classifier API

FastAPI provides a great platform for building and deploying machine learning models as APIs. It provides a simple and intuitive way to define and expose endpoints for a machine learning model. With FastAPI, it is easy to define an endpoint for the toxicity classifier model and handle requests for classifying text.

Sample Code

Here is a simple example of how the Toxicity Classifier API can be defined using FastAPI:


from fastapi import FastAPI
from pydantic import BaseModel
import joblib

app = FastAPI()

class TextRequest(BaseModel):
text: str

@app.post("/classify")
def classify_text(request: TextRequest):
model = joblib.load('toxicity_classifier_model.pkl')
prediction = model.predict([request.text])[0]
return {"toxicity": prediction}


Conclusion

FastAPI is a great choice for building and deploying machine learning models as APIs, and the Toxicity Classifier API is a useful tool for automatically classifying text as toxic or non-toxic. By using FastAPI to build the Toxicity Classifier API, developers can easily integrate the toxicity classification model into their applications.

Overall, the Toxicity Classifier API using FastAPI provides a powerful and efficient way to classify text for toxicity, enabling developers to build safer and more inclusive applications.