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Creating an OpenAI-Powered FastAPI Application with Docker.
Overview
Introduction
Docker is a popular platform for containerizing applications and dependencies, while Continuous Integration (CI) automates building, testing, and validating code changes. This topic explores the use of Docker for CI in conjunction with GitLab's managed CI/CD pipelines, which offer pipeline orchestration and version control. Developers can define a pipeline with various stages and jobs, such as building and testing Docker images, and push them to a container registry. Using Docker in CI allows for greater portability and consistency, improving development speed and code quality.
Preprequisites
create new directory and switch to it
mkdir api && cd api
create a FastAPI file
cat <<EOF>main.py
import os, openai, requests
from typing import Union
from fastapi import FastAPI
from dotenv import load_dotenv
load_dotenv()
app = FastAPI()
openai.api_key = os.getenv("OPENAI_API_KEY")
@app.get("/health")
def test_health_endpoint():
response = requests.get(f"{os.getenv('HOST')}/openapi.json")
if response.status_code == 200:
return {"status": "ok"}
else:
return {"s tatus": "error", "message": "Failed to connect to openapi.json"}
@app.get("/completion")
async def openai_endpoint(query: str):
response = openai.Completion.create(engine="davinci", prompt=query, max_tokens=10)
return {"response": response.choices[0].text}
EOF
add python requirements file
cat <<EOF>>requirements.txt
fastapi
uvicorn
openai
python-dotenv
requests
EOF
add dotenv file
cat <<EOF>>.env
OPENAI_API_KEY=<your-openapi-key>
HOST=127.0.0.1:8080
EOF
valid key can be generated here
create a Dockerfile for this application
FROM python:3.9-slim-buster
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
ENV OPENAPI_KEY ""
CMD ["python", "-m", "uvicorn", "main:app", "--host=0.0.0.0", "--port=8000"]
add a docker compose file and put it outside the "api" folder
version: '3.7'
services:
api:
build:
context: api
dockerfile: Dockerfile
env_file:
- ./api/.env
ports:
- "8000:8000"
volumes:
- ./api:/app/api
command: uvicorn api.main:app --host=0.0.0.0 --port=8000
check and sync the file structure and content with my GitHub repository
once all ready, try out by starting the applicaiton in docker
docker compose up api
cool thing about FastAPI, it's autogenerates SwaggerUI for you, you can access our endpoints quickly at http://127.0.0.1:8000/docs
Conclusion
- created basic FastAPI application connecting to Openai API interfaces
- create Docker configuration for running the application