Creating an API for Question Answering Pipeline using FastAPI

In this article, we will discuss how to create an API for a question answering pipeline using FastAPI. FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.

First, we need to install FastAPI using pip:

        
          $ pip install fastapi
        
      

Next, we will create a new Python file for our FastAPI application. Let’s call it main.py.

Here’s a simple example of how we can create an API endpoint for our question answering pipeline using FastAPI:

        
          import fastapi
          from fastapi import FastAPI
          from pydantic import BaseModel

          app = FastAPI()

          class QuestionAnswerRequest(BaseModel):
              question: str
              context: str

          @app.post("/answer")
          def answer_question(request: QuestionAnswerRequest):
              # Your question answering pipeline logic goes here
              answer = "This is a placeholder answer"
              return {"answer": answer}
        
      

In this example, we first import the necessary modules from FastAPI. We then define a data model QuestionAnswerRequest using pydantic.BaseModel for the request body of our API endpoint. The answer_question function handles the incoming HTTP POST request, extracts the question and context from the request, and returns the answer using our question answering pipeline logic.

Save the main.py file and run the FastAPI application using the following command:

        
          $ uvicorn main:app --reload
        
      

Now, our API for the question answering pipeline is up and running. We can make POST requests to /answer endpoint to get answers to questions based on a given context.

FastAPI makes it easy to build and deploy high-performance APIs with Python, and it provides powerful type checking and validation features using Python type hints and pydantic data models. By following the steps outlined in this article, you can create your own API for a question answering pipeline using FastAPI.