app

import logging app = FastAPI() # Configure logging logging.basicConfig(level=logging.INFO) class TeamTask(BaseModel): task_id: int = Field(..., gt=0) role: str = Field(..., min_length=1) @app.exception_handler(RequestValidationE…

@app.on_event("startup") async def startup_event(): # Initialize any resources or connections here logging.info("Starting up...") @app.on_event("shutdown") async def shutdown_event(): # Clean up any resources or connections her…

from pydantic import ValidationError import asyncio import httpx import time app = FastAPI() # Add CORS middleware app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], a…

return jsonify({"message": "Basic request handled successfully"}) # Custom error handler for 429 status code @app.errorhandler(429) def ratelimit_handler(e): return jsonify(error="ratelimit", description=str(e.description)), 200 i…

return {"access_token": "example_token", "token_type": "bearer"} raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid credentials") @app.get("/users/me") def read_users_me(user: User = Depends(check_rol…

logging.info(f"Response status: {response.status_code}") logging.info(f"Total request processing took {time.time() - start_time:.4f} seconds") return response # Example endpoint @app.get("/items") async def read_items(): re…

from fastapi.responses import JSONResponse import logging import time app = FastAPI() # Middleware 1: Request Validation @app.middleware("http") async def validate_request(request: Request, call_next): start_time = time.time() con…

Here's an example of how you might implement a mock database for token validation: ```python from fastapi import FastAPI, Request, HTTPException from fastapi.responses import JSONResponse import logging import time from functools import lr…

app = FastAPI() # Simulated database mock_database = { "valid_token": True, "invalid_token": False } # Asynchronous token validation function with caching @lru_cache(maxsize=128) async def validate_token(token: str) -> bool: #…

if content_type != "application/json": logging.warning(f"Invalid Content-Type: {content_type}") return JSONResponse(status_code=400, content={"detail": "Invalid Content-Type"}) response = await call_next(request) …

- **Token Validation**: Replace the simulated user authentication logic with actual token validation logic. - **Role-Based Access Control**: You can extend the role-based access control logic to include more granular permissions if needed. …

from starlette.middleware.exceptions import ExceptionMiddleware app = FastAPI() # Add middleware for production readiness app.add_middleware(CORSMiddleware, allow_origins=["*"]) app.add_middleware(GZipMiddleware) app.add_middleware(HTTPSR…

1. **Load Balancer**: Use a load balancer like Nginx or HAProxy to distribute traffic across multiple instances of your FastAPI application. 2. **Database Optimization**: Ensure your database queries are optimized. Use indexes, caching,…

[Turn 5336] User: I'm trying to implement security and compliance for my API, specifically authorization and data encryption. I've been looking at different libraries and frameworks, but I'm not sure which one to use. Can you help me with t…

lifespan="on", # Lifespan of the server proxy_headers=True, # Enable proxy headers ) # Run the server if __name__ == "__main__": uvicorn.run(config) ``` ### Step 2: Define Access Roles and Handle Authorization Define roles …

from fastapi import FastAPI, Depends, HTTPException from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm from pydantic import BaseModel import jwt from datetime import datetime, timedelta from typing import Optional,…

log_message('ERROR', f"Authentication error for user {username}", {'error': str(e)}) return None # FastAPI app app = FastAPI() # Rate limiter rate_limiter = RateLimiter(max_calls=10, period=60) # 10 calls per minute # De…

return token except keycloak.exceptions.KeycloakError as e: # Handle authentication errors log_message('ERROR', f"Authentication error for user {username}", {'error': str(e)}) return None # FastAPI app a…

"client_secret": client_secret } # Create a Keycloak instance kc = keycloak.Keycloak(**keycloak_config) # Define a function to handle authentication async def authenticate(username, password): try: # Authenticate the user …

# Check cache first token = await caches.get(f"token_{username}") if token: return token # Enforce rate limiting with rate_limiter: token = await kc.token_async(userna…

raise HTTPException(status_code=401, detail="Invalid credentials") # Define another API endpoint with rate limiting @app.get("/users") async def list_users(_=Depends(rate_limit_dependency)): # Simulate fetching users from a dat…

# Further validation logic if 'required_field' not in data: raise ValueError("Missing required field in request data") return data except ValueError as ve: logging.error(f"ValueError:…

Ensure that your Pydantic models are optimized for performance. Use built-in types and avoid unnecessary conversions. ```python from pydantic import BaseModel from typing import List class Item(BaseModel): name: str description: s…

{"id": 2, "title": "Title 2", "content": "Content 2"}, ] @app.post("/query", response_model=QueryResponse) def query(request: QueryRequest): # Simulate querying the data store start = request.offset end = request.offset + r…

from fastapi import FastAPI, Depends, HTTPException from pydantic import BaseModel from typing import List, Optional from sqlalchemy.orm import Session from fastapi_sqlalchemy import DBSessionMiddleware, db app = FastAPI() # Example in-me…

from fastapi import FastAPI, Depends from pydantic import BaseModel from typing import List, Optional import redis from fastapi.middleware.cors import CORSMiddleware app = FastAPI() # Initialize Redis client r = redis.Redis(host='localhos…

from fastapi.middleware.trustedhost import TrustedHostMiddleware from fastapi.middleware.cors import CORSMiddleware from fastapi.middleware.gzip import GZipMiddleware from fastapi.middleware.httpsredirect import HTTPSRedirectMiddleware app…

1. **Pydantic Model Optimization**: - Use `Field` to add constraints like `gt` (greater than) and `lt` (less than) to validate the `limit` field. 2. **Caching**: - Use Redis to cache the results of frequent queries to reduce the o…

{"id": 2, "title": "Title 2", "content": "Content 2"}, ] # Middleware to handle CORS app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) ``` …

def health_check(): return {"status": "OK"} ``` #### Dense Retrieval Service ```python from fastapi import FastAPI, HTTPException from pydantic import BaseModel import requests app = FastAPI() class SearchQuery(BaseModel): query…

from prometheus_client import start_http_server, Summary, Counter app = FastAPI() # Prometheus metrics REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request') TOTAL_REQUESTS = Counter('total_requests', 'Total…

return response.json() except requests.exceptions.HTTPError as e: raise HTTPException(status_code=response.status_code, detail=str(e)) except requests.exceptions.ConnectionError as e: raise HTT…

Using Redis as a caching layer can significantly reduce memory usage and improve response times by storing frequently accessed data in memory. #### Steps to Implement Redis Caching 1. **Install Redis**: ```sh sudo apt-get update …

- **Security**: TLS 1.3 encryption - **Authentication and Authorization**: Keycloak roles ### 2. **FastAPI Endpoint Implementation** Here's an example implementation using FastAPI: ```python from fastapi import FastAPI, Depends, HTTPExce…

sparse_results = {"results": [], "total_results": 0} return JSONResponse(content={"error_code": e.status_code, "message": e.detail}, status_code=e.status_code) try: dense_results = call_dense_retrieval(query…

except requests.exceptions.HTTPError as e: raise HTTPException(status_code=response.status_code, detail=str(e)) except requests.exceptions.ConnectionError as e: raise HTTPException(status_code=503, detail=str(e)) …

return JSONResponse(content={"error_code": e.status_code, "message": e.detail}, status_code=e.status_code) try: dense_results = call_dense_retrieval(query) except HTTPException as e: dense_results = {"re…

Here's an improved version of your API: ```python from fastapi import FastAPI, HTTPException, Depends from pydantic import BaseModel from typing import Optional import redis from fastapi.middleware.cors import CORSMiddleware from fastapi.b…

[Turn 7623] Assistant: Certainly! Let's enhance your API design to include more robust error handling, caching strategies, and efficient use of FastAPI features. We'll also add some middleware for better request handling and background task…

from fastapi import FastAPI from transformers import AutoModel, AutoTokenizer # Initialize FastAPI app app = FastAPI() # Load pre-trained model and tokenizer model = AutoModel.from_pretrained("my-secure-model") tokenizer = AutoTokenizer.f…

from fastapi.responses import JSONResponse from fastapi.exceptions import RequestValidationError from starlette.exceptions import HTTPException as StarletteHTTPException app = FastAPI() # Middleware for CORS app.add_midd…