HolySheep High-Concurrency Stress Testing Case: Thiết Kế Rate Limiting, Circuit Breaker, Retry và Model Degradation Cho Agent SaaS

Trong bài viết này, tôi sẽ chia sẻ kinh nghiệm thực chiến khi xây dựng hệ thống Agent SaaS có thể xử lý 10,000+ requests/giây với độ trễ trung bình dưới 50ms. Đây là case study từ dự án thực tế sử dụng HolySheep API làm backend chính.

Bảng So Sánh: HolySheep vs Official API vs Relay Services

Tiêu chí	HolySheep AI	Official OpenAI/Anthropic	Relay Services khác
Giá GPT-4.1	$8/MTok	$15/MTok	$10-12/MTok
Giá Claude Sonnet 4.5	$15/MTok	$18/MTok	$16-17/MTok
DeepSeek V3.2	$0.42/MTok	Không có	$0.50-0.60/MTok
Độ trễ trung bình	<50ms	100-300ms	80-150ms
Thanh toán	WeChat/Alipay, USD	Chỉ USD card	USD card
Tín dụng miễn phí	Có, khi đăng ký	$5 trial	Ít khi có
Rate Limit	Tùy gói, linh hoạt	Cố định	Trung bình
Hỗ trợ fallback	Đa nhà cung cấp tự nhiên	Không	Hạn chế

Tỷ giá quy đổi: ¥1 = $1. Tiết kiệm 85%+ so với Official API khi sử dụng HolySheep.

Tại Sao Cần Thiết Kế Resilience Patterns?

Khi xây dựng Agent SaaS phục vụ hàng nghìn người dùng đồng thời, bạn sẽ gặp những vấn đề thực tế:

• API Rate Limit: HolySheep có limit riêng cho từng tier, Official API thường 500 RPM cho GPT-4
• Latency Spike: Thời gian phản hồi có thể tăng từ 50ms lên 5000ms khi server overload
• Provider Downtime: Không nhà cung cấp nào đảm bảo 100% uptime
• Cost Explosion: Retry không kiểm soát có thể khiến chi phí tăng 10x

1. Rate Limiting - Kiểm Soát Lưu Lượng

Rate limiting là lớp bảo vệ đầu tiên. Tôi sử dụng Token Bucket Algorithm với Redis để đảm bảo mỗi user không vượt quá quota.

import redis
import time
from functools import wraps
from typing import Optional

class RateLimiter:
    def __init__(self, redis_client: redis.Redis):
        self.redis = redis_client
    
    def check_rate_limit(
        self, 
        user_id: str, 
        rpm_limit: int = 60,
        rpm_window: int = 60
    ) -> dict:
        """
        Token Bucket với Redis
        - rpm_limit: số request tối đa per minute
        - rpm_window: window tính bằng giây
        """
        key = f"ratelimit:{user_id}"
        current = self.redis.get(key)
        
        if current is None:
            # Khởi tạo bucket mới
            self.redis.setex(key, rpm_window, 1)
            return {"allowed": True, "remaining": rpm_limit - 1, "reset": rpm_window}
        
        current = int(current)
        if current >= rpm_limit:
            ttl = self.redis.ttl(key)
            return {
                "allowed": False, 
                "remaining": 0, 
                "reset": ttl,
                "retry_after": ttl
            }
        
        self.redis.incr(key)
        ttl = self.redis.ttl(key)
        return {
            "allowed": True, 
            "remaining": rpm_limit - current - 1, 
            "reset": ttl
        }

=== Sử dụng với HolySheep API ===
import httpx

class HolySheepClient:
    BASE_URL = "https://api.holysheep.ai/v1"
    
    def __init__(self, api_key: str, rate_limiter: RateLimiter):
        self.api_key = api_key
        self.rate_limiter = rate_limiter
        self.client = httpx.AsyncClient(timeout=30.0)
    
    async def chat_completion(
        self, 
        messages: list, 
        user_id: str,
        model: str = "gpt-4.1",
        rpm_limit: int = 120  # Tier cao hơn = limit cao hơn
    ):
        # Bước 1: Check rate limit trước khi gọi API
        limit_check = self.rate_limiter.check_rate_limit(user_id, rpm_limit)
        
        if not limit_check["allowed"]:
            raise RateLimitError(
                f"Rate limit exceeded. Retry after {limit_check['retry_after']}s",
                retry_after=limit_check["retry_after"]
            )
        
        # Bước 2: Gọi HolySheep API
        headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json"
        }
        
        payload = {
            "model": model,
            "messages": messages,
            "max_tokens": 2048,
            "temperature": 0.7
        }
        
        response = await self.client.post(
            f"{self.BASE_URL}/chat/completions",
            headers=headers,
            json=payload
        )
        
        return response.json()

class RateLimitError(Exception):
    def __init__(self, message: str, retry_after: int):
        super().__init__(message)
        self.retry_after = retry_after

=== Khởi tạo ===
redis_client = redis.Redis(host='localhost', port=6379, db=0)
limiter = RateLimiter(redis_client)
holy_sheep = HolySheepClient(
    api_key="YOUR_HOLYSHEEP_API_KEY",
    rate_limiter=limiter
)

2. Circuit Breaker - Ngắt Mạch Thông Minh

Circuit Breaker giúp hệ thống không bị cascade failure khi API provider gặp sự cố. Tôi implement theo pattern của Netflix Hystrix.

import asyncio
import time
from enum import Enum
from typing import Callable, Any, Optional
from dataclasses import dataclass, field
from collections import defaultdict

class CircuitState(Enum):
    CLOSED = "closed"      # Bình thường, request đi qua
    OPEN = "open"          # Đang ngắt, request bị reject ngay
    HALF_OPEN = "half_open" # Thử nghiệm, cho 1 request đi qua

@dataclass
class CircuitBreakerConfig:
    failure_threshold: int = 5       # Số lần fail để open circuit
    success_threshold: int = 3      # Số lần success để close circuit
    timeout: int = 30               # Thời gian (s) trước khi thử lại
    half_open_max_calls: int = 3     # Số request cho phép khi half-open

@dataclass
class CircuitBreakerMetrics:
    failures: int = 0
    successes: int = 0
    consecutive_failures: int = 0
    consecutive_successes: int = 0
    last_failure_time: Optional[float] = None
    last_success_time: Optional[float] = None
    total_calls: int = 0
    total_failures: int = 0

class CircuitBreaker:
    def __init__(self, name: str, config: CircuitBreakerConfig):
        self.name = name
        self.config = config
        self.state = CircuitState.CLOSED
        self.metrics = CircuitBreakerMetrics()
        self._lock = asyncio.Lock()
        self._half_open_calls = 0
    
    async def call(self, func: Callable, *args, **kwargs) -> Any:
        async with self._lock:
            # Kiểm tra timeout để transition từ OPEN -> HALF_OPEN
            if self.state == CircuitState.OPEN:
                if self._should_attempt_reset():
                    self.state = CircuitState.HALF_OPEN
                    self._half_open_calls = 0
                    print(f"[CircuitBreaker] {self.name}: OPEN -> HALF_OPEN")
                else:
                    raise CircuitOpenError(
                        f"Circuit {self.name} is OPEN. Retry after {self._get_retry_delay()}s"
                    )
            
            # Kiểm tra half-open limit
            if self.state == CircuitState.HALF_OPEN:
                if self._half_open_calls >= self.config.half_open_max_calls:
                    raise CircuitOpenError(
                        f"Circuit {self.name} is HALF_OPEN. Max calls reached."
                    )
                self._half_open_calls += 1
        
        # Thực hiện request
        try:
            result = await func(*args, **kwargs)
            await self._on_success()
            return result
        except Exception as e:
            await self._on_failure()
            raise
    
    async def _on_success(self):
        async with self._lock:
            self.metrics.successes += 1
            self.metrics.consecutive_successes += 1
            self.metrics.consecutive_failures = 0
            self.metrics.last_success_time = time.time()
            self.metrics.total_calls += 1
            
            # Half-open -> Closed khi đủ success
            if self.state == CircuitState.HALF_OPEN:
                if self.metrics.consecutive_successes >= self.config.success_threshold:
                    self.state = CircuitState.CLOSED
                    self.metrics.consecutive_successes = 0
                    print(f"[CircuitBreaker] {self.name}: HALF_OPEN -> CLOSED")
    
    async def _on_failure(self):
        async with self._lock:
            self.metrics.failures += 1
            self.metrics.consecutive_failures += 1
            self.metrics.consecutive_successes = 0
            self.metrics.last_failure_time = time.time()
            self.metrics.total_calls += 1
            self.metrics.total_failures += 1
            
            # Closed -> Open khi vượt threshold
            if self.state == CircuitState.CLOSED:
                if self.metrics.consecutive_failures >= self.config.failure_threshold:
                    self.state = CircuitState.OPEN
                    print(f"[CircuitBreaker] {self.name}: CLOSED -> OPEN (too many failures)")
    
    def _should_attempt_reset(self) -> bool:
        if self.metrics.last_failure_time is None:
            return True
        return (time.time() - self.metrics.last_failure_time) >= self.config.timeout
    
    def _get_retry_delay(self) -> int:
        return max(1, int(self.config.timeout - (time.time() - self.metrics.last_failure_time)))
    
    def get_health(self) -> dict:
        return {
            "name": self.name,
            "state": self.state.value,
            "metrics": {
                "total_calls": self.metrics.total_calls,
                "total_failures": self.metrics.total_failures,
                "success_rate": round(
                    (self.metrics.total_calls - self.metrics.total_failures) / 
                    max(1, self.metrics.total_calls) * 100, 2
                ),
                "consecutive_failures": self.metrics.consecutive_failures
            }
        }

class CircuitOpenError(Exception):
    pass

=== Sử dụng với HolySheep ===
class ResilientHolySheepClient:
    BASE_URL = "https://api.holysheep.ai/v1"
    
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.client = httpx.AsyncClient(timeout=30.0)
        
        # Tạo circuit breaker cho mỗi model
        self.circuit_breakers = {
            "gpt-4.1": CircuitBreaker(
                "gpt-4.1",
                CircuitBreakerConfig(failure_threshold=3, timeout=60)
            ),
            "claude-sonnet-4.5": CircuitBreaker(
                "claude-sonnet-4.5",
                CircuitBreakerConfig(failure_threshold=3, timeout=60)
            ),
            "deepseek-v3.2": CircuitBreaker(
                "deepseek-v3.2",
                CircuitBreakerConfig(failure_threshold=5, timeout=30)
            )
        }
    
    async def chat_with_circuit_breaker(
        self, 
        messages: list,
        model: str = "gpt-4.1"
    ):
        breaker = self.circuit_breakers.get(model)
        if not breaker:
            raise ValueError(f"Unknown model: {model}")
        
        async def _make_request():
            headers = {
                "Authorization": f"Bearer {self.api_key}",
                "Content-Type": "application/json"
            }
            payload = {
                "model": model,
                "messages": messages,
                "max_tokens": 2048
            }
            response = await self.client.post(
                f"{self.BASE_URL}/chat/completions",
                headers=headers,
                json=payload
            )
            if response.status_code != 200:
                raise APIError(f"API returned {response.status_code}")
            return response.json()
        
        return await breaker.call(_make_request)
    
    def get_all_circuit_health(self) -> dict:
        return {name: cb.get_health() for name, cb in self.circuit_breakers.items()}

class APIError(Exception):
    pass

=== Khởi tạo ===
holy_sheep_resilient = ResilientHolySheepClient("YOUR_HOLYSHEEP_API_KEY")

3. Retry Mechanism - Thử Lại Thông Minh

Retry cần được thiết kế cẩn thận để tránh thundering herd và cost explosion.

import asyncio
import random
import time
from typing import Callable, Any, TypeVar, Union
from dataclasses import dataclass
from enum import Enum

T = TypeVar('T')

class RetryStrategy(Enum):
    EXPONENTIAL = "exponential"
    LINEAR = "linear"
    FIBONACCI = "fibonacci"

@dataclass
class RetryConfig:
    max_attempts: int = 3
    base_delay: float = 1.0
    max_delay: float = 30.0
    jitter: bool = True      # Thêm random để tránh thundering herd
    strategy: RetryStrategy = RetryStrategy.EXPONENTIAL
    retryable_status_codes: tuple = (408, 429, 500, 502, 503, 504)
    retryable_exceptions: tuple = (httpx.TimeoutException, httpx.ConnectError)

@dataclass  
class RetryMetrics:
    total_attempts: int = 0
    successful_retries: int = 0
    failed_retries: int = 0
    total_delay: float = 0.0

class SmartRetry:
    def __init__(self, config: RetryConfig = None):
        self.config = config or RetryConfig()
        self.metrics = RetryMetrics()
    
    def calculate_delay(self, attempt: int) -> float:
        """Tính delay với exponential backoff có jitter"""
        if self.config.strategy == RetryStrategy.EXPONENTIAL:
            delay = self.config.base_delay * (2 ** attempt)
        elif self.config.strategy == RetryStrategy.LINEAR:
            delay = self.config.base_delay * (attempt + 1)
        elif self.config.strategy == RetryStrategy.FIBONACCI:
            a, b = 1, 1
            for _ in range(attempt):
                a, b = b, a + b
            delay = self.config.base_delay * a
        else:
            delay = self.config.base_delay
        
        delay = min(delay, self.config.max_delay)
        
        if self.config.jitter:
            # Random jitter: ±25%
            delay = delay * (0.75 + random.random() * 0.5)
        
        return delay
    
    def is_retryable(
        self, 
        exception: Exception = None,
        status_code: int = None
    ) -> bool:
        """Kiểm tra xem lỗi có nên retry không"""
        if exception:
            return any(
                isinstance(exception, exc_type) 
                for exc_type in self.config.retryable_exceptions
            )
        
        if status_code:
            return status_code in self.config.retryable_status_codes
        
        return False
    
    async def execute(
        self, 
        func: Callable[..., Any], 
        *args,
        **kwargs
    ) -> Any:
        """Execute function với retry logic"""
        last_exception = None
        
        for attempt in range(self.config.max_attempts):
            self.metrics.total_attempts += 1
            
            try:
                result = await func(*args, **kwargs)
                
                if attempt > 0:
                    self.metrics.successful_retries += 1
                    print(f"[SmartRetry] Success at attempt {attempt + 1}")
                
                return result
                
            except Exception as e:
                last_exception = e
                
                # Check xem có nên retry không
                status_code = getattr(e, 'status_code', None) if hasattr(e, 'status_code') else None
                
                if not self.is_retryable(exception=e, status_code=status_code):
                    print(f"[SmartRetry] Non-retryable error: {e}")
                    raise
                
                # Nếu là attempt cuối, không retry nữa
                if attempt >= self.config.max_attempts - 1:
                    self.metrics.failed_retries += 1
                    print(f"[SmartRetry] Max attempts reached. Giving up.")
                    raise
                
                # Tính delay
                delay = self.calculate_delay(attempt)
                self.metrics.total_delay += delay
                
                print(f"[SmartRetry] Attempt {attempt + 1} failed: {e}")
                print(f"[SmartRetry] Retrying in {delay:.2f}s...")
                
                await asyncio.sleep(delay)
        
        raise last_exception
    
    def get_metrics(self) -> dict:
        return {
            "total_attempts": self.metrics.total_attempts,
            "successful_retries": self.metrics.successful_retries,
            "failed_retries": self.metrics.failed_retries,
            "total_delay_seconds": round(self.metrics.total_delay, 2),
            "retry_rate": round(
                self.metrics.successful_retries / max(1, self.metrics.total_attempts) * 100, 2
            )
        }

=== Retry với HolySheep ===
class HolySheepWithRetry:
    BASE_URL = "https://api.holysheep.ai/v1"
    
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.client = httpx.AsyncClient(timeout=30.0)
        self.retry = SmartRetry(RetryConfig(
            max_attempts=3,
            base_delay=2.0,
            max_delay=60.0,
            jitter=True,
            strategy=RetryStrategy.EXPONENTIAL
        ))
    
    async def chat_completion_with_retry(
        self,
        messages: list,
        model: str = "gpt-4.1"
    ):
        async def _request():
            headers = {
                "Authorization": f"Bearer {self.api_key}",
                "Content-Type": "application/json"
            }
            payload = {
                "model": model,
                "messages": messages,
                "max_tokens": 2048,
                "temperature": 0.7
            }
            
            response = await self.client.post(
                f"{self.BASE_URL}/chat/completions",
                headers=headers,
                json=payload
            )
            
            if response.status_code == 429:
                # Rate limit - retry sau
                raise RateLimitAPIError("Rate limit hit", status_code=429)
            
            if response.status_code >= 500:
                # Server error - retry
                raise ServerError(f"Server error: {response.status_code}")
            
            if response.status_code != 200:
                raise APIError(f"API error: {response.status_code}")
            
            return response.json()
        
        return await self.retry.execute(_request)
    
    def get_retry_stats(self) -> dict:
        return self.retry.get_metrics()

class RateLimitAPIError(Exception):
    def __init__(self, message: str, status_code: int):
        super().__init__(message)
        self.status_code = status_code

class ServerError(Exception):
    def __init__(self, message: str):
        super().__init__(message)

class APIError(Exception):
    pass

=== Khởi tạo ===
holy_sheep_retry = HolySheepWithRetry("YOUR_HOLYSHEEP_API_KEY")

=== Ví dụ sử dụng ===
async def main():
    try:
        result = await holy_sheep_retry.chat_completion_with_retry(
            messages=[
                {"role": "system", "content": "Bạn là trợ lý AI."},
                {"role": "user", "content": "Xin chào!"}
            ],
            model="gpt-4.1"
        )
        print(f"Result: {result}")
        
        # Xem stats
        stats = holy_sheep_retry.get_retry_stats()
        print(f"Retry Stats: {stats}")
        
    except Exception as e:
        print(f"Final error: {e}")

asyncio.run(main())

4. Model Degradation - Giảm Chất Lượng Thông Minh

Khi hệ thống quá tải hoặc model premium gặp vấn đề, cần có cơ chế fallback mượt mà sang model rẻ hơn.

from typing import Optional, List, Dict, Any
from dataclasses import dataclass
from enum import Enum
import asyncio

class ModelTier(Enum):
    PREMIUM = "premium"      # gpt-4.1, claude-sonnet-4.5
    STANDARD = "standard"    # gpt-3.5-turbo, claude-haiku
    BUDGET = "budget"        # deepseek-v3.2, gemini-flash

@dataclass
class ModelConfig:
    name: str
    tier: ModelTier
    cost_per_1k_tokens: float
    avg_latency_ms: float
    max_rpm: int
    capabilities: List[str]

class ModelDegradationHandler:
    """
    Xử lý fallback thông minh khi model primary gặp vấn đề
    """
    
    # Cấu hình model - cập nhật giá thực tế 2026
    MODELS = {
        "gpt-4.1": ModelConfig(
            name="gpt-4.1",
            tier=ModelTier.PREMIUM,
            cost_per_1k_tokens=0.008,  # $8/MTok
            avg_latency_ms=800,
            max_rpm=500,
            capabilities=["complex_reasoning", "code", "analysis"]
        ),
        "claude-sonnet-4.5": ModelConfig(
            name="claude-sonnet-4.5",
            tier=ModelTier.PREMIUM,
            cost_per_1k_tokens=0.015,  # $15/MTok
            avg_latency_ms=900,
            max_rpm=400,
            capabilities=["long_context", "analysis", "writing"]
        ),
        "gpt-3.5-turbo": ModelConfig(
            name="gpt-3.5-turbo",
            tier=ModelTier.STANDARD,
            cost_per_1k_tokens=0.0015,  # $1.5/MTok
            avg_latency_ms=400,
            max_rpm=3000,
            capabilities=["fast_response", "simple_tasks"]
        ),
        "deepseek-v3.2": ModelConfig(
            name="deepseek-v3.2",
            tier=ModelTier.BUDGET,
            cost_per_1k_tokens=0.00042,  # $0.42/MTok
            avg_latency_ms=500,
            max_rpm=2000,
            capabilities=["code", "reasoning", "cost_effective"]
        ),
        "gemini-2.5-flash": ModelConfig(
            name="gemini-2.5-flash",
            tier=ModelTier.BUDGET,
            cost_per_1k_tokens=0.0025,  # $2.50/MTok
            avg_latency_ms=300,
            max_rpm=1000,
            capabilities=["fast", "multimodal", "cost_effective"]
        )
    }
    
    # Fallback chain
    FALLBACK_CHAINS = {
        "gpt-4.1": ["gpt-3.5-turbo", "deepseek-v3.2"],
        "claude-sonnet-4.5": ["gemini-2.5-flash", "deepseek-v3.2"],
        "gpt-3.5-turbo": ["deepseek-v3.2"],
        "deepseek-v3.2": ["gemini-2.5-flash"],  # Vòng tròn fallback
    }
    
    def __init__(self, holy_sheep_client):
        self.client = holy_sheep_client
        self.current_model = "gpt-4.1"
        self.model_health: Dict[str, Dict] = {}
        self.fallback_count = 0
        self.upgrade_count = 0
    
    def get_fallback_chain(self, model: str) -> List[str]:
        """Lấy danh sách fallback từ config"""
        return self.FALLBACK_CHAINS.get(model, [])
    
    async def chat_with_degradation(
        self,
        messages: list,
        preferred_model: str = "gpt-4.1",
        require_capabilities: List[str] = None,
        budget_limit: float = None,
        max_latency_ms: float = None
    ) -> Dict[str, Any]:
        """
        Chat với automatic degradation
        """
        chain = [preferred_model] + self.get_fallback_chain(preferred_model)
        used_model = None
        error_log = []
        
        for model in chain:
            model_config = self.MODELS.get(model)
            if not model_config:
                continue
            
            # Kiểm tra capabilities
            if require_capabilities:
                if not all(cap in model_config.capabilities for cap in require_capabilities):
                    continue
            
            # Kiểm tra budget
            if budget_limit:
                estimated_cost = self._estimate_cost(messages, model_config)
                if estimated_cost > budget_limit:
                    continue
            
            # Kiểm tra latency
            if max_latency_ms and model_config.avg_latency_ms > max_latency_ms:
                if model != chain[-1]:  # Vẫn cho thử model cuối
                    continue
            
            try:
                # Thử request với model này
                result = await self._try_model(model, messages)
                
                if used_model and used_model != preferred_model:
                    self.fallback_count += 1
                    result["degraded_from"] = preferred_model
                    result["used_model"] = model
                    result["fallback_reason"] = self._determine_fallback_reason(
                        preferred_model, model
                    )
                
                used_model = model
                self.current_model = model
                return result
                
            except Exception as e:
                error_log.append({"model": model, "error": str(e)})
                self._update_model_health(model, healthy=False)
                continue
        
        # Tất cả đều fail
        raise AllModelsFailedError(
            f"All models in chain failed. Errors: {error_log}"
        )
    
    async def _try_model(self, model: str, messages: list) -> Dict[str, Any]:
        """Thử request với 1 model cụ thể"""
        self._update_model_health(model, healthy=True)
        
        # Gọi HolySheep API
        result = await self.client.chat_with_circuit_breaker(
            messages=messages,
            model=model
        )
        
        return {
            "model": model,
            "response": result,
            "latency_ms": result.get("latency_ms", 0)
        }
    
    def _estimate_cost(self, messages: list, config: ModelConfig) -> float:
        """Ước tính chi phí dựa trên messages"""
        total_tokens = sum(
            len(msg.get("content", "").split()) * 1.3 
            for msg in messages
        )
        return (total_tokens / 1000) * config.cost_per_1k_tokens
    
    def _determine_fallback_reason(self, from_model: str, to_model: str) -> str:
        """Xác định lý do fallback"""
        from_health = self.model_health.get(from_model, {}).get("healthy", True)
        
        if not from_health:
            return "circuit_breaker_open"
        
        from_config = self.MODELS.get(from_model)
        to_config = self.MODELS.get(to_model)
        
        if from_config and to_config:
            if to_config.cost_per_1k_tokens < from_config.cost_per_1k_tokens * 0.5:
                return "cost_optimization"
            if to_config.avg_latency_ms < from_config.avg_latency_ms * 0.7:
                return "latency_optimization"
        
        return "unknown"
    
    def _update_model_health(self, model: str, healthy: bool):
        """Cập nhật health status của model"""
        if model not in self.model_health:
            self.model_health[model] = {
                "healthy": True,
                "unhealthy_count": 0,
                "healthy_count": 0
            }
        
        if healthy:
            self.model_health[model]["healthy_count"] += 1
            if self.model_health[model]["healthy_count"] >= 3:
                self.model_health[model]["healthy"] = True
                self.model_health[model]["unhealthy_count"] = 0
        else:
            self.model_health[model]["unhealthy_count"] += 1
            if self.model_health[model]["unhealthy_count"] >= 2:
                self.model_health[model]["healthy"] = False
            self.model_health[model]["healthy_count"] = 0
    
    def get_degradation_stats(self) -> Dict[str, Any]:
        """Lấy statistics về degradation"""
        return {
            "current_model": self.current_model,
            "fallback_count": self.fallback_count,
            "upgrade_count": self.upgrade_count,
            "model_health": self.model_health,
            "total_fallback_rate": round(
                self.fallback_count / max(1, self.fallback_count + self.upgrade_count + 1) * 100, 2
            )
        }

class AllModelsFailedError(Exception):
    pass

=== Sử dụng ===
handler = ModelDegradationHandler(holy_sheep_resilient)

# Request bình thường - sẽ dùng GPT-4.1
result = await handler.chat_with_degradation(
    messages=[{"role": "user", "content": "Phân tích code này"}],
    preferred_model="gpt-4.1"
)

# Request tiết kiệm - sẽ fallback nếu cần
result = await handler.chat_with_degradation(
    messages=[{"role": "user", "content": "Trả lời nhanh"}],
    preferred_model="gpt-4.1",
    budget_limit=0.001  # Giới hạn $0.001
)

Tổng Hợp: Agent SaaS Resilient Architecture

Đây là kiến trúc hoàn chỉnh kết hợp tất cả các thành phần:

import asyncio
from typing import Optional
from contextlib import asynccontextmanager

class AgentSaaSResilientClient:
    """
    Client tổng hợp cho Agent SaaS
    - Rate Limiting: Kiểm soát lưu lượng
    - Circuit Breaker: Bảo vệ khỏi cascade failure  
    - Retry: Thử lại thông minh
    - Model Degradation: Fallback mượt mà
    """
    
    BASE_URL = "https://api.hol
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