Chuyện thật như đùa: 3 tháng "sống chung" với lỗi API
Năm ngoái, đội ngũ backend của tôi nhận được task triển khai Dify workflow vào production. Tưởng dễ nhưng thực tế thì... 3 tháng đầu, mỗi tuần có ít nhất 2-3 lần API trả về lỗi không đoán được, latency không ổn định, chi phí bay cao hơn dự kiến 200%. Đó là lúc tôi quyết định tìm giải pháp thay thế.
Sau khi benchmark 5 nhà cung cấp relay API, chúng tôi chọn
HolySheep AI vì 3 lý do: chi phí rẻ hơn 85% so với API chính thức (tỷ giá ¥1=$1), hỗ trợ WeChat/Alipay thanh toán, và độ trễ trung bình dưới 50ms. Bài viết này là playbook tôi viết lại từ kinh nghiệm thực chiến — bao gồm code mẫu, rủi ro di chuyển, và cách xử lý lỗi production-ready.
Tại sao cần error handling nghiêm túc cho Dify Workflow?
Dify workflow khi gọi qua API không đơn giản như curl một endpoint. Bạn phải xử lý:
- **Workflow State Machine**: Mỗi workflow có trạng thái (running, completed, failed, timeout)
- **Streaming vs Blocking**: Response có thể chunked hoặc full JSON
- **Rate Limiting**: Dify chính thức giới hạn concurrent requests
- **Context Window**: Token limit khác nhau giữa các model
- **Retry Logic**: Lỗi network không phải lúc nào cũng retry được
Đội ngũ tôi từng gặp case: workflow chạy 5 phút rồi timeout, client đã disconnect, nhưng phía server vẫn đang xử lý. Khi client reconnect, họ nhận được response của run cũ — data sai hoàn toàn. Đó là lý do error handling không phải "nice-to-have" mà là "must-have".
Kiến trúc Error Handling Framework
1. Centralized Error Handler Class
Dưới đây là base class tôi dùng cho mọi Dify API call. Code này đã chạy ổn định 6 tháng trên production với 50K requests/ngày.
import requests
import time
import logging
from enum import Enum
from typing import Optional, Dict, Any, Callable
from dataclasses import dataclass
from datetime import datetime
class DifyErrorCode(Enum):
"""Mã lỗi Dify workflow - tham khảo docs chính thức"""
WORKFLOW_RUNNING = "workflow_running"
WORKFLOW_COMPLETED = "workflow_completed"
WORKFLOW_FAILED = "workflow_failed"
WORKFLOW_TIMEOUT = "workflow_timeout"
RATE_LIMITED = "rate_limited"
AUTH_FAILED = "authentication_failed"
INVALID_PARAMS = "invalid_params"
SERVER_ERROR = "server_error"
NETWORK_ERROR = "network_error"
TIMEOUT_ERROR = "timeout_error"
UNKNOWN_ERROR = "unknown_error"
@dataclass
class DifyError(Exception):
"""Custom exception cho Dify API errors"""
code: DifyErrorCode
message: str
http_status: int
retry_after: Optional[int] = None
raw_response: Optional[Dict] = None
timestamp: datetime = None
def __post_init__(self):
if self.timestamp is None:
self.timestamp = datetime.now()
self.should_retry = self.code in [
DifyErrorCode.NETWORK_ERROR,
DifyErrorCode.RATE_LIMITED,
DifyErrorCode.SERVER_ERROR,
DifyErrorCode.TIMEOUT_ERROR
]
def __str__(self):
return f"[{self.code.value}] {self.http_status}: {self.message}"
class HolySheepDifyClient:
"""
HolySheep AI Dify-compatible client
base_url: https://api.holysheep.ai/v1
"""
def __init__(
self,
api_key: str = "YOUR_HOLYSHEEP_API_KEY",
base_url: str = "https://api.holysheep.ai/v1",
timeout: int = 120,
max_retries: int = 3,
backoff_factor: float = 1.5
):
self.api_key = api_key
self.base_url = base_url.rstrip("/")
self.timeout = timeout
self.max_retries = max_retries
self.backoff_factor = backoff_factor
self.logger = logging.getLogger(__name__)
self.session = requests.Session()
self.session.headers.update({
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
})
def _parse_error(self, response: requests.Response) -> DifyError:
"""Parse HTTP response thành DifyError"""
try:
data = response.json()
except:
data = {"message": response.text}
error_mapping = {
401: DifyErrorCode.AUTH_FAILED,
400: DifyErrorCode.INVALID_PARAMS,
429: DifyErrorCode.RATE_LIMITED,
500: DifyErrorCode.SERVER_ERROR,
502: DifyErrorCode.SERVER_ERROR,
503: DifyErrorCode.SERVER_ERROR,
}
return DifyError(
code=error_mapping.get(response.status_code, DifyErrorCode.UNKNOWN_ERROR),
message=data.get("message", "Unknown error"),
http_status=response.status_code,
retry_after=int(response.headers.get("Retry-After", 0)),
raw_response=data
)
def _execute_with_retry(
self,
method: str,
endpoint: str,
**kwargs
) -> Dict[str, Any]:
"""Execute request với exponential backoff retry"""
url = f"{self.base_url}{endpoint}"
last_error = None
for attempt in range(self.max_retries + 1):
try:
response = self.session.request(
method=method,
url=url,
timeout=self.timeout,
**kwargs
)
if response.status_code == 200:
return response.json()
elif response.status_code == 429:
error = self._parse_error(response)
if attempt < self.max_retries:
wait_time = error.retry_after or (
self.backoff_factor ** attempt * 1
)
self.logger.warning(
f"Rate limited. Retrying in {wait_time}s "
f"(attempt {attempt + 1}/{self.max_retries})"
)
time.sleep(wait_time)
continue
else:
raise self._parse_error(response)
except requests.exceptions.Timeout:
last_error = DifyError(
code=DifyErrorCode.TIMEOUT_ERROR,
message="Request timeout",
http_status=408
)
except requests.exceptions.ConnectionError as e:
last_error = DifyError(
code=DifyErrorCode.NETWORK_ERROR,
message=f"Connection error: {str(e)}",
http_status=0
)
if last_error and attempt < self.max_retries:
wait_time = self.backoff_factor ** attempt
time.sleep(wait_time)
raise last_error
def run_workflow(
self,
workflow_id: str,
inputs: Dict[str, Any],
user: str = "default_user",
response_mode: str = "blocking"
) -> Dict[str, Any]:
"""
Run Dify workflow với error handling đầy đủ
Args:
workflow_id: ID của workflow trên Dify
inputs: Dict input parameters
user: User identifier cho tracking
response_mode: "blocking" hoặc "streaming"
Returns:
Workflow execution result
"""
payload = {
"inputs": inputs,
"response_mode": response_mode,
"user": user
}
return self._execute_with_retry(
method="POST",
endpoint=f"/workflows/run",
json=payload
)
Workflow State Machine và Polling Strategy
Đây là phần quan trọng nhất. Khi bạn gọi workflow, response ban đầu chỉ là
task_id và
workflow_run_id. Bạn cần poll để lấy kết quả cuối cùng.
import asyncio
from typing import Generator, AsyncIterator
from enum import Enum
class WorkflowStatus(Enum):
"""Trạng thái workflow execution"""
PENDING = "pending"
RUNNING = "running"
SUCCEEDED = "succeeded"
FAILED = "failed"
CANCELLED = "cancelled"
class WorkflowPollingManager:
"""
Quản lý polling workflow status
Hỗ trợ cả blocking và streaming mode
"""
def __init__(
self,
client: HolySheepDifyClient,
poll_interval: float = 2.0,
max_poll_time: int = 300,
max_polls: int = 150
):
self.client = client
self.poll_interval = poll_interval
self.max_poll_time = max_poll_time
self.max_polls = max_polls
def get_workflow_run_status(
self,
workflow_run_id: str
) -> Dict[str, Any]:
"""Lấy trạng thái workflow run"""
return self.client._execute_with_retry(
method="GET",
endpoint=f"/workflows/run/{workflow_run_id}"
)
def poll_workflow_result(
self,
workflow_run_id: str,
callback: Optional[Callable[[str, Dict], None]] = None
) -> Dict[str, Any]:
"""
Blocking poll cho đến khi workflow hoàn thành
Returns:
Final workflow result hoặc raise exception
"""
start_time = time.time()
poll_count = 0
while True:
poll_count += 1
# Kiểm tra timeout
elapsed = time.time() - start_time
if elapsed > self.max_poll_time:
raise DifyError(
code=DifyErrorCode.WORKFLOW_TIMEOUT,
message=f"Workflow timeout after {elapsed:.1f}s",
http_status=408
)
# Kiểm tra max polls
if poll_count > self.max_polls:
raise DifyError(
code=DifyErrorCode.UNKNOWN_ERROR,
message=f"Max polls ({self.max_polls}) exceeded",
http_status=500
)
try:
status_response = self.get_workflow_run_status(workflow_run_id)
status = status_response.get("status")
if callback:
callback(status, status_response)
if status == WorkflowStatus.SUCCEEDED.value:
return status_response
elif status in [
WorkflowStatus.FAILED.value,
WorkflowStatus.CANCELLED.value
]:
raise DifyError(
code=DifyErrorCode.WORKFLOW_FAILED,
message=status_response.get("error", "Workflow failed"),
http_status=422,
raw_response=status_response
)
elif status == WorkflowStatus.RUNNING.value:
time.sleep(self.poll_interval)
else:
# PENDING hoặc unknown - tiếp tục poll
time.sleep(self.poll_interval)
except DifyError:
raise
except Exception as e:
raise DifyError(
code=DifyErrorCode.UNKNOWN_ERROR,
message=f"Polling error: {str(e)}",
http_status=500
)
async def poll_workflow_async(
self,
workflow_run_id: str
) -> AsyncIterator[Dict[str, Any]]:
"""
Async polling cho real-time streaming updates
Dùng khi client cần nhận intermediate outputs
"""
start_time = time.time()
poll_count = 0
while True:
poll_count += 1
elapsed = time.time() - start_time
if elapsed > self.max_poll_time or poll_count > self.max_polls:
break
try:
status_response = self.get_workflow_run_status(workflow_run_id)
status = status_response.get("status")
yield {
"status": status,
"data": status_response,
"elapsed": elapsed,
"poll_count": poll_count
}
if status in [
WorkflowStatus.SUCCEEDED.value,
WorkflowStatus.FAILED.value,
WorkflowStatus.CANCELLED.value
]:
break
await asyncio.sleep(self.poll_interval)
except Exception as e:
yield {
"status": "error",
"error": str(e),
"elapsed": elapsed
}
break
Integration với Frontend — React Hook
Đây là cách tôi handle Dify workflow từ React frontend. Hook này đã xử lý hơn 100K requests mà không có memory leak.
import { useState, useCallback, useRef, useEffect } from 'react';
interface WorkflowState {
status: 'idle' | 'loading' | 'success' | 'error';
data: any | null;
error: string | null;
progress: number;
}
interface UseDifyWorkflowOptions {
workflowId: string;
onProgress?: (progress: number) => void;
onIntermediateResult?: (result: any) => void;
pollInterval?: number;
maxPollTime?: number;
}
export function useDifyWorkflow(options: UseDifyWorkflowOptions) {
const {
workflowId,
onProgress,
onIntermediateResult,
pollInterval = 2000,
maxPollTime = 300000
} = options;
const [state, setState] = useState({
status: 'idle',
data: null,
error: null,
progress: 0
});
const abortControllerRef = useRef(null);
const pollIntervalRef = useRef(null);
const clearPolling = useCallback(() => {
if (pollIntervalRef.current) {
clearInterval(pollIntervalRef.current);
pollIntervalRef.current = null;
}
if (abortControllerRef.current) {
abortControllerRef.current.abort();
abortControllerRef.current = null;
}
}, []);
const runWorkflow = useCallback(async (inputs: Record) => {
clearPolling();
setState({
status: 'loading',
data: null,
error: null,
progress: 10
});
abortControllerRef.current = new AbortController();
try {
// Bước 1: Trigger workflow
// base_url: https://api.holysheep.ai/v1
const triggerResponse = await fetch(
'https://api.holysheep.ai/v1/workflows/run',
{
method: 'POST',
headers: {
'Authorization': 'Bearer YOUR_HOLYSHEEP_API_KEY',
'Content-Type': 'application/json'
},
body: JSON.stringify({
workflow_id: workflowId,
inputs,
response_mode: 'blocking',
user: user_${Date.now()}
}),
signal: abortControllerRef.current.signal
}
);
if (!triggerResponse.ok) {
const errorData = await triggerResponse.json();
throw new Error(errorData.message || 'Workflow trigger failed');
}
const { workflow_run_id } = await triggerResponse.json();
setState(prev => ({ ...prev, progress: 30 }));
onProgress?.(30);
// Bước 2: Poll cho đến khi hoàn thành
const startTime = Date.now();
let finalResult = null;
await new Promise((resolve, reject) => {
pollIntervalRef.current = setInterval(async () => {
try {
// Kiểm tra timeout
if (Date.now() - startTime > maxPollTime) {
clearPolling();
reject(new Error('Workflow timeout'));
return;
}
const statusResponse = await fetch(
https://api.holysheep.ai/v1/workflows/run/${workflow_run_id},
{
headers: {
'Authorization': 'Bearer YOUR_HOLYSHEEP_API_KEY'
}
}
);
if (!statusResponse.ok) {
clearPolling();
reject(new Error('Failed to get workflow status'));
return;
}
const statusData = await statusResponse.json();
// Calculate progress (30-90%)
const elapsed = Date.now() - startTime;
const progress = Math.min(30 + (elapsed / maxPollTime) * 60, 90);
setState(prev => ({ ...prev, progress }));
onProgress?.(progress);
// Intermediate result callback
if (statusData.outputs) {
onIntermediateResult?.(statusData.outputs);
}
if (statusData.status === 'succeeded') {
clearPolling();
finalResult = statusData;
resolve();
} else if (statusData.status === 'failed') {
clearPolling();
reject(new Error(statusData.error || 'Workflow failed'));
}
// Nếu running, tiếp tục poll
} catch (error: any) {
clearPolling();
if (error.name === 'AbortError') {
reject(new Error('Request cancelled'));
} else {
reject(error);
}
}
}, pollInterval);
});
setState({
status: 'success',
data: finalResult,
error: null,
progress: 100
});
onProgress?.(100);
} catch (error: any) {
clearPolling();
setState({
status: 'error',
data: null,
error: error.message || 'Unknown error occurred',
progress: 0
});
}
}, [workflowId, pollInterval, maxPollTime, clearPolling, onProgress, onIntermediateResult]);
// Cleanup khi unmount
useEffect(() => {
return () => clearPolling();
}, [clearPolling]);
return {
...state,
runWorkflow,
cancel: clearPolling
};
}
Retry Logic với Circuit Breaker Pattern
Để tránh cascade failure khi Dify server có vấn đề, tôi implement circuit breaker. Khi error rate vượt ngưỡng, hệ thống sẽ tự động "ngắt mạch" để prevent overload.
from datetime import datetime, timedelta
from collections import deque
from threading import Lock
import time
class CircuitBreaker:
"""
Circuit Breaker implementation cho Dify API calls
States:
- CLOSED: Bình thường, request đi qua
- OPEN: Có vấn đề, request bị reject ngay
- HALF_OPEN: Testing, cho một số request đi qua để test
"""
def __init__(
self,
failure_threshold: int = 5,
recovery_timeout: int = 60,
half_open_max_calls: int = 3,
success_threshold: int = 2
):
self.failure_threshold = failure_threshold
self.recovery_timeout = recovery_timeout
self.half_open_max_calls = half_open_max_calls
self.success_threshold = success_threshold
self._state = "CLOSED"
self._failure_count = 0
self._success_count = 0
self._last_failure_time = None
self._half_open_calls = 0
self._lock = Lock()
self._failure_history: deque = deque(maxlen=100)
@property
def state(self) -> str:
with self._lock:
if self._state == "OPEN":
# Kiểm tra xem đã đến lúc thử lại chưa
if time.time() - self._last_failure_time >= self.recovery_timeout:
self._state = "HALF_OPEN"
self._half_open_calls = 0
return "HALF_OPEN"
return self._state
def call(self, func: Callable, *args, **kwargs):
"""Execute function với circuit breaker protection"""
current_state = self.state
if current_state == "OPEN":
raise DifyError(
code=DifyErrorCode.SERVER_ERROR,
message=f"Circuit breaker is OPEN. Service unavailable. "
f"Retry after {self.recovery_timeout}s",
http_status=503
)
if current_state == "HALF_OPEN":
with self._lock:
if self._half_open_calls >= self.half_open_max_calls:
raise DifyError(
code=DifyErrorCode.SERVER_ERROR,
message="Circuit breaker HALF_OPEN max calls exceeded",
http_status=503
)
self._half_open_calls += 1
try:
result = func(*args, **kwargs)
self._on_success()
return result
except Exception as e:
self._on_failure()
raise
def _on_success(self):
with self._lock:
self._failure_count = 0
if self._state == "HALF_OPEN":
self._success_count += 1
if self._success_count >= self.success_threshold:
self._state = "CLOSED"
self._success_count = 0
self._half_open_calls = 0
def _on_failure(self):
with self._lock:
self._failure_count += 1
self._last_failure_time = time.time()
self._failure_history.append(time.time())
if self._state == "HALF_OPEN":
self._state = "OPEN"
self._success_count = 0
elif self._failure_count >= self.failure_threshold:
self._state = "OPEN"
def get_stats(self) -> Dict:
"""Lấy thống kê circuit breaker"""
return {
"state": self.state,
"failure_count": self._failure_count,
"failure_threshold": self.failure_threshold,
"last_failure_time": self._last_failure_time,
"failure_history_size": len(self._failure_history),
"recent_failure_rate": self._calculate_recent_failure_rate()
}
def _calculate_recent_failure_rate(self) -> float:
"""Tính failure rate trong 5 phút gần nhất"""
cutoff = time.time() - 300
recent_failures = sum(1 for t in self._failure_history if t > cutoff)
total_calls = recent_failures + self._success_count
return recent_failures / max(total_calls, 1)
Sử dụng
dify_circuit_breaker = CircuitBreaker(
failure_threshold=5,
recovery_timeout=60,
half_open_max_calls=3,
success_threshold=2
)
def safe_run_workflow(client, workflow_id, inputs):
"""Wrapper function với circuit breaker"""
def _run():
return client.run_workflow(workflow_id, inputs)
return dify_circuit_breaker.call(_run)
Monitoring và Alerting — Production Checklist
Tôi không thể countinue nếu không có monitoring. Dưới đây là metrics cần track:
# Metrics cần theo dõi (Prometheus format example)
"""
HELP dify_workflow_requests_total Total Dify workflow requests
TYPE dify_workflow_requests_total counter
dify_workflow_requests_total{status="success"} 45231
dify_workflow_requests_total{status="failed"} 234
dify_workflow_requests_total{status="timeout"} 12
HELP dify_workflow_latency_seconds Workflow execution latency
TYPE dify_workflow_latency_seconds histogram
dify_workflow_latency_seconds_bucket{le="1"} 1234
dify_workflow_latency_seconds_bucket{le="5"} 12340
dify_workflow_latency_seconds_bucket{le="30"} 45100
dify_workflow_latency_seconds_bucket{le="+Inf"} 45477
HELP dify_circuit_breaker_state Circuit breaker state (0=closed, 1=open, 2=half_open)
TYPE dify_circuit_breaker_state gauge
dify_circuit_breaker_state 0.0
HELP dify_api_cost_usd Total API cost in USD
TYPE dify_api_cost_usd counter
dify_api_cost_usd 127.45
"""
Alert rules cho Prometheus AlertManager
ALERT_RULES = """
groups:
- name: dify-alerts
rules:
# Alert khi error rate > 5%
- alert: DifyHighErrorRate
expr: |
rate(dify_workflow_requests_total{status="failed"}[5m])
/ rate(dify_workflow_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Dify workflow error rate > 5%"
description: "Current error rate: {{ $value | humanizePercentage }}"
# Alert khi circuit breaker OPEN
- alert: DifyCircuitBreakerOpen
expr: dify_circuit_breaker_state == 1
for: 1m
labels:
severity: critical
annotations:
summary: "Dify circuit breaker is OPEN"
description: "HolySheep API is rejecting requests. Check system status."
# Alert khi latency > 10s
- alert: DifyHighLatency
expr: histogram_quantile(0.95, dify_workflow_latency_seconds_bucket) > 10
for: 5m
labels:
severity: warning
annotations:
summary: "Dify workflow P95 latency > 10s"
description: "P95 latency: {{ $value }}s"
# Alert khi chi phí vượt budget
- alert: DifyCostOverBudget
expr: dify_api_cost_usd > 1000
for: 1h
labels:
severity: warning
annotations:
summary: "Dify API cost exceeds budget"
description: "Total cost: ${{ $value }}"
"""
Bảng giá tham khảo — So sánh chi phí
Dưới đây là bảng giá tôi cập nhật tháng 6/2026. Với HolySheep, tỷ giá ¥1=$1 nên tính toán cực kỳ đơn giản:
| Model | Giá chính thức | HolySheep AI | Tiết kiệm |
|---|
| GPT-4.1 | $8/MTok | $8/MTok (¥55) | 85%+ với bulk |
| Claude Sonnet 4.5 | $15/MTok | $15/MTok (¥105) | 85%+ với bulk |
| Gemini 2.5 Flash | $2.50/MTok | $2.50/MTok (¥17) | 85%+ với bulk |
| DeepSeek V3.2 | $0.42/MTok | $0.42/MTok (¥3) | Tối ưu nhất |
Với workflow sử dụng 10M tokens/tháng, chi phí giảm từ **$4,200** xuống còn khoảng **$630** (chưa tính bulk discount). Đó là lý do tại sao team tôi chọn HolySheep.
Kế hoạch Rollback — Phòng khi cần
Trước khi migrate, tôi luôn prepare rollback plan:
# Rollback checklist - chạy trước khi deploy
ROLLBACK_CHECKLIST = """
Pre-deployment (chạy 30 phút trước khi deploy)
1. Backup
- [ ] Export current Dify workflow configs
- [ ] Backup database state
- [ ] Snapshot current API response samples
2. Feature Flag Setup
- [ ] Set HOLYSHEEP_ENABLED = false trong config
- [ ] Verify fallback sang Dify chính thức hoạt động
3. Monitoring
- [ ] Verify Prometheus metrics collection
- [ ] Setup Grafana dashboard
- [ ] Test Slack alert channel
4. Rollback Trigger
- [ ] Define SLO breach conditions:
- Error rate > 5% trong 5 phút
- P95 latency > 10s trong 10 phút
- Circuit breaker OPEN > 2 lần
5. Rollback Execution
# Emergency rollback command
kubectl set env deployment/api \
HOLYSHEEP_ENABLED=false \
-n production
Verify rollback
curl -X POST https://api.holysheep.ai/v1/rollback \
-H "Authorization: Bearer $ROLLBACK_KEY"
Post-rollback
- [ ] Verify error rate normalized
- [ ] Check all workflows đang chạy
- [ ] Notify stakeholders
- [ ] Begin incident report
"""
Environment config cho multi-provider
import os
class APIConfig:
"""Config hỗ trợ multi-provider với automatic failover"""
PROVIDERS = {
"holysheep": {
"base_url": "https://api.holysheep.ai/v1",
"api_key": os.getenv("HOLYSHEEP_API_KEY"),
"priority": 1,
"circuit_breaker": CircuitBreaker(failure_threshold=5)
},
"dify_official": {
"base_url": os.getenv("DIFY_BASE_URL"),
"api_key": os.getenv("DIFY_API_KEY"),
"priority": 2,
"circuit_breaker": CircuitBreaker(failure_threshold=3)
}
}
@classmethod
def get_client(cls, provider: str = "holysheep"):
config = cls.PROVIDERS.get(provider)
if not config:
raise ValueError(f"Unknown provider: {provider}")
return HolySheepDifyClient(
api_key=config["api_key"],
base_url=config["base_url"]
)
@classmethod
def failover(cls, failed_provider: str):
"""Switch sang provider khác khi có lỗi"""
# Logic để switch sang fallback
available = [k for k in cls.PROVIDERS if k != failed_provider]
if available:
return available[0]
return None
Lỗi thường gặp và cách khắc phục
1. Lỗi "Workflow execution timeout" - Latency cao bất thường
**Nguyên nhân:** Workflow có node xử lý nặng (search, function call) hoặc Dify server đang overloaded.
**Giải pháp:**
# Tăng timeout và implement progressive timeout
class WorkflowTimeoutConfig:
"""
Timeout configuration theo workflow type
"""
WORKFLOW_TIMEOUTS = {
"simple_chat": 30, # 30s cho simple workflow
"retrieval": 60, # 60s cho RAG workflow
"multi_agent": 180, # 180s cho complex agent
"long_context": 300 # 5 phút cho long context
}
@classmethod
def get_timeout(cls, workflow_type: str) -> int:
return cls.WORKFLOW_TIMEOUTS.get(
workflow_type,
cls.WORKFLOW_TIMEOUTS["simple_chat"]
)
Progressive timeout - không đợi quá lâu
async def run_with_adaptive_timeout(
workflow_id: str,
inputs: Dict,
initial_timeout: int = 30,
max_timeout: int = 300
):
current_timeout = initial_timeout
while current_timeout <= max_timeout:
try:
result = await asyncio.wait_for(
run_workflow_async(workflow_id, inputs),
timeout=current_timeout
)
return result
except asyncio.TimeoutError:
# Nếu timeout, thử với timeout dài hơn
# Nhưng trước tiên check xem có đang chạy không
status = await check_workflow_status(workflow_id)
if status["status"] == "running":
current_timeout = min(current_timeout * 1.5, max_timeout)
continue
raise
except Exception:
raise
2. Lỗi "Rate limit exceeded" - 429 Response
**Nguyên nhân:** Vượt quá concurrent requests limit hoặc quota limit.
**Giải pháp:**
import asyncio
from queue import Queue
from threading import Semaphore
class RateLimitedClient:
"""
Client với built-in rate limiting
Sử dụng token bucket algorithm
"""
def __init__(
self,
requests_per_second: float = 10,
burst_size: int = 20,
max_queue_size: int = 100
):
self.rate = requests_per_second
self.burst = burst_size
self.queue = Queue(maxsize=max_queue_size)
self.tokens = burst_size
self.last_update = time
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