genai_app/ │ ├── app/ │ ├── __init__.py │ ├── main.py # FastAPI app entry point │ ├── config.py # Environment/config settings │ ├── models/ # Pydantic models and data schemas │ │ └── genai.py │ ├── services/ # Core GenAI logic (e.g., LangChain, transformers) │ │ └── genai_service.py │ ├── api/ # Route definitions │ │ ├── __init__.py │ │ └── genai_routes.py │ ├── utils/ # Helper functions, logging, etc. │ │ └── helpers.py │ └── middleware/ # Custom middleware (e.g., logging, auth) │ └── auth.py │ ├── tests/ # Unit and integration tests │ ├── __init__.py │ └── test_genai.py │ ├── requirements.txt # Python dependencies ├── .env # Environment variables ├── README.md # Project documentation └── run.sh # Shell script to run the app with Uvicorn 🚀 Key Components Explained
main.py
from fastapi import FastAPI from app.api.genai_routes import router as genai_router app = FastAPI(title="GenAI FastAPI App") app.include_router(genai_router) genai_routes.py
from fastapi import APIRouter from app.services.genai_service import generate_response from app.models.genai import GenAIRequest router = APIRouter() @router.post("/generate") def generate_text(request: GenAIRequest): return generate_response(request.prompt) genai_service.py
def generate_response(prompt: str) -> dict: # Call to GenAI model (e.g., OpenAI, HuggingFace, LangChain) return {"response": f"Generated text for: {prompt}"} 🧪 Running the App
run.sh
#!/bin/bash uvicorn app.main:app --reload --host 0.0.0.0 --port 8000 🧠 Optional Enhancements
- Docker support: Add
Dockerfileanddocker-compose.yml - Async support: Use
async defin routes and services - Model integration: Add HuggingFace or OpenAI SDK in
genai_service.py - LangGraph or LangChain: Integrate in
services/for advanced workflows
Source: DEV Community.
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