Custom Middleware

import time
from collections import defaultdict, deque
from typing import Dict

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.tools.duckduckgo import DuckDuckGoTools
from fastapi import Request, Response
from fastapi.responses import JSONResponse
from starlette.middleware.base import BaseHTTPMiddleware


# === Rate Limiting Middleware ===
class RateLimitMiddleware(BaseHTTPMiddleware):
    """
    Rate limiting middleware that limits requests per IP address.
    """

    def __init__(self, app, requests_per_minute: int = 60, window_size: int = 60):
        super().__init__(app)
        self.requests_per_minute = requests_per_minute
        self.window_size = window_size
        # Store request timestamps per IP
        self.request_history: Dict[str, deque] = defaultdict(lambda: deque())

    async def dispatch(self, request: Request, call_next) -> Response:
        # Get client IP
        client_ip = request.client.host if request.client else "unknown"
        current_time = time.time()

        # Clean old requests outside the window
        history = self.request_history[client_ip]
        while history and current_time - history[0] > self.window_size:
            history.popleft()

        # Check if rate limit exceeded
        if len(history) >= self.requests_per_minute:
            return JSONResponse(
                status_code=429,
                content={
                    "detail": f"Rate limit exceeded. Max {self.requests_per_minute} requests per minute."
                },
            )

        # Add current request to history
        history.append(current_time)

        # Add rate limit headers
        response = await call_next(request)
        response.headers["X-RateLimit-Limit"] = str(self.requests_per_minute)
        response.headers["X-RateLimit-Remaining"] = str(
            self.requests_per_minute - len(history)
        )
        response.headers["X-RateLimit-Reset"] = str(
            int(current_time + self.window_size)
        )

        return response


# === Request/Response Logging Middleware ===
class RequestLoggingMiddleware(BaseHTTPMiddleware):
    """
    Request/response logging middleware with timing and basic info.
    """

    def __init__(self, app, log_body: bool = False, log_headers: bool = False):
        super().__init__(app)
        self.log_body = log_body
        self.log_headers = log_headers
        self.request_count = 0

    async def dispatch(self, request: Request, call_next) -> Response:
        self.request_count += 1
        start_time = time.time()

        # Basic request info
        client_ip = request.client.host if request.client else "unknown"
        print(
            f"🔍 Request #{self.request_count}: {request.method} {request.url.path} from {client_ip}"
        )

        # Optional: Log headers
        if self.log_headers:
            print(f"📋 Headers: {dict(request.headers)}")

        # Optional: Log request body
        if self.log_body and request.method in ["POST", "PUT", "PATCH"]:
            body = await request.body()
            if body:
                print(f"📝 Body: {body.decode()}")

        # Process request
        response = await call_next(request)

        # Log response info
        duration = time.time() - start_time
        status_emoji = "✅" if response.status_code < 400 else "❌"
        print(
            f"{status_emoji} Response: {response.status_code} in {duration * 1000:.1f}ms"
        )

        # Add request count to response header
        response.headers["X-Request-Count"] = str(self.request_count)

        return response


# === Setup database and agent ===
db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

agent = Agent(
    id="demo-agent",
    name="Demo Agent",
    model=OpenAIChat(id="gpt-4o"),
    db=db,
    tools=[DuckDuckGoTools()],
    markdown=True,
)

agent_os = AgentOS(
    description="Essential middleware demo with rate limiting and logging",
    agents=[agent],
)

app = agent_os.get_app()

# Add custom middleware
app.add_middleware(
    RateLimitMiddleware,
    requests_per_minute=10,
    window_size=60,
)

app.add_middleware(
    RequestLoggingMiddleware,
    log_body=False,
    log_headers=False,
)

if __name__ == "__main__":
    """
    Run the essential middleware demo using AgentOS serve method.
    
    Features:
    1. Rate Limiting (10 requests/minute)
    2. Request/Response Logging
    
    Test commands:
    
    1. Test rate limiting:
       for i in {1..15}; do curl http://localhost:7777/config; done
    
    2. Check rate limit headers:
       curl -v http://localhost:7777/config
    
    Look for:
    - Console logs showing request/response info
    - Rate limit headers: X-RateLimit-Limit, X-RateLimit-Remaining, X-RateLimit-Reset
    - Request count header: X-Request-Count
    - 429 errors when rate limit exceeded
    """

    agent_os.serve(
        app="fastapi_app_with_custom_middleware:app",
        host="localhost",
        port=7777,
        reload=True,
    )