Python + AI: Building Your First AI-Powered Web App with FastAPI

Introduction

In this tutorial, we'll build a modern web application using Python, FastAPI, and AI integration. This will demonstrate how AI can enhance your applications without replacing your role as a developer.

Setting Up the Project

First, let's create our project structure:

mkdir ai-fastapi-app
cd ai-fastapi-app
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install fastapi uvicorn python-multipart openai

Creating the FastAPI Application

Let's create our main application file:

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import openai
import os

app = FastAPI(title="AI-Powered Web App")

class ChatRequest(BaseModel):
    message: str
    context: str = ""

@app.post("/chat")
async def chat_with_ai(request: ChatRequest):
    try:
        # Initialize OpenAI client
        client = openai.OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
        
        # Create chat completion
        response = client.chat.completions.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": "You are a helpful coding assistant."},
                {"role": "user", "content": f"Context: {request.context}\n\nUser: {request.message}"}
            ]
        )
        
        return {"response": response.choices[0].message.content}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.get("/")
async def root():
    return {"message": "AI-Powered Web App is running!"}

Conclusion

This tutorial demonstrates how to integrate AI capabilities into your web applications using FastAPI. The key takeaway is that AI should enhance your development process, not replace it. You remain in control of the architecture, business logic, and user experience.

Remember: AI is a tool that makes you more productive, not a replacement for your skills as a developer.