Thực Trạng Chi Phí AI Testing Năm 2026
Là một senior QA engineer với 5 năm kinh nghiệm, tôi đã thử nghiệm hàng chục công cụ AI để tạo test case tự động. Kết quả? Hầu hết đều khiến team phải chi hàng nghìn đô mỗi tháng cho API calls. Để bạn hình dung rõ hơn, hãy cùng tôi phân tích bảng so sánh chi phí thực tế của các provider AI hàng đầu:
| Provider | Giá Input | Giá Output | 10M Token/Tháng |
|---|---|---|---|
| GPT-4.1 | $2/MTok | $8/MTok | $80,000 |
| Claude Sonnet 4.5 | $3/MTok | $15/MTok | $150,000 |
| Gemini 2.5 Flash | $0.30/MTok | $2.50/MTok | $25,000 |
| DeepSeek V3.2 | $0.10/MTok | $0.42/MTok | $4,200 |
Nhìn vào bảng trên, DeepSeek V3.2 tiết kiệm đến 97% chi phí so với Claude Sonnet 4.5. Với dự án cần xử lý 10 triệu token output mỗi tháng, bạn sẽ tiết kiệm được $145,800 — đủ để thuê thêm 2 senior engineers!
Tại Sao Nên Chọn HolySheep AI?
Đăng ký tại đây để trải nghiệm nền tảng với chi phí cực kỳ cạnh tranh. HolySheep AI tích hợp DeepSeek V3.2 với tỷ giá ¥1 = $1, thanh toán qua WeChat/Alipay, độ trễ trung bình dưới 50ms. Đặc biệt, bạn nhận tín dụng miễn phí ngay khi đăng ký — đủ để test toàn bộ workflow trước khi quyết định.
Kiến Trúc Tổng Quan
Trước khi đi vào code, hãy hiểu luồng hoạt động của hệ thống AI-powered testing:
┌─────────────────────────────────────────────────────────────────────┐
│ PYTEST AI TEST GENERATION ARCHITECTURE │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ [Source Code] ──► [AST Parser] ──► [AI Request Builder] │
│ │ │ │ │
│ │ │ ▼ │
│ │ │ [HolySheep API /v1/chat/completions] │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ [Test Coverage] ◄── [Pytest Config] ◄── [Response Parser] │
│ │ │ │
│ ▼ ▼ │
│ [Coverage Report] [Test Case Templates] │
│ │
└─────────────────────────────────────────────────────────────────────┘
Triển Khai Chi Tiết
Bước 1: Cài Đặt Môi Trường
pip install pytest pytest-asyncio openai pydantic python-dotenv pytest-html
Bước 2: Cấu Hình HolySheep API Client
# config.py
import os
from openai import AsyncOpenAI
from pydantic import BaseModel
from typing import List, Optional
class AIConfig(BaseModel):
"""Cấu hình kết nối HolySheep AI"""
base_url: str = "https://api.holysheep.ai/v1"
api_key: str
model: str = "deepseek-chat"
max_tokens: int = 4096
temperature: float = 0.3
class TestGeneratorConfig(BaseModel):
"""Cấu hình generator"""
source_dir: str = "./src"
test_dir: str = "./tests/ai_generated"
coverage_threshold: float = 80.0
max_cases_per_function: int = 5
def get_ai_client() -> AsyncOpenAI:
"""Khởi tạo AsyncOpenAI client cho HolySheep"""
return AsyncOpenAI(
base_url=AIConfig().base_url,
api_key=os.getenv("HOLYSHEEP_API_KEY", "YOUR_HOLYSHEEP_API_KEY"),
timeout=30.0,
max_retries=3
)
Sử dụng
client = get_ai_client()
print(f"Connected to: {AIConfig().base_url}")
print(f"Model: {AIConfig().model}")
Bước 3: Module Phân Tích Source Code (AST Parser)
# ast_parser.py
import ast
from pathlib import Path
from typing import List, Dict, Any, Optional
from dataclasses import dataclass
@dataclass
class FunctionInfo:
"""Thông tin về một function"""
name: str
file_path: str
line_number: int
docstring: Optional[str]
args: List[str]
arg_types: Dict[str, str]
return_type: Optional[str]
complexity: int
decorators: List[str]
class SourceCodeAnalyzer:
"""Phân tích source code để trích xuất function metadata"""
COMPLEXITY_THRESHOLD = 10
def __init__(self, source_dir: str):
self.source_dir = Path(source_dir)
self.functions: List[FunctionInfo] = []
def analyze_file(self, file_path: Path) -> List[FunctionInfo]:
"""Phân tích một file Python"""
try:
with open(file_path, 'r', encoding='utf-8') as f:
tree = ast.parse(f.read(), filename=str(file_path))
return self._extract_functions(tree, str(file_path))
except Exception as e:
print(f"Error analyzing {file_path}: {e}")
return []
def _extract_functions(self, tree: ast.AST, file_path: str) -> List[FunctionInfo]:
"""Trích xuất functions từ AST"""
functions = []
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef):
func_info = FunctionInfo(
name=node.name,
file_path=file_path,
line_number=node.lineno,
docstring=ast.get_docstring(node),
args=[arg.arg for arg in node.args.args],
arg_types=self._infer_arg_types(node),
return_type=self._infer_return_type(node),
complexity=self._calculate_complexity(node),
decorators=[ast.unparse(d) for d in node.decorator_list]
)
functions.append(func_info)
return functions
def _infer_arg_types(self, node: ast.FunctionDef) -> Dict[str, str]:
"""Suy luận kiểu argument từ annotation"""
types = {}
for i, arg in enumerate(node.args.args):
if arg.annotation:
types[arg.arg] = ast.unparse(arg.annotation)
return types
def _infer_return_type(self, node: ast.FunctionDef) -> Optional[str]:
"""Suy luận kiểu return"""
if node.returns:
return ast.unparse(node.returns)
return None
def _calculate_complexity(self, node: ast.FunctionDef) -> int:
"""Tính cyclomatic complexity"""
complexity = 1
for child in ast.walk(node):
if isinstance(child, (ast.If, ast.While, ast.For, ast.ExceptHandler)):
complexity += 1
elif isinstance(child, ast.BoolOp):
complexity += len(child.values) - 1
return complexity
def analyze_all(self) -> List[FunctionInfo]:
"""Phân tích tất cả files"""
for py_file in self.source_dir.rglob("*.py"):
if "__pycache__" not in str(py_file):
self.functions.extend(self.analyze_file(py_file))
return self.functions
Demo sử dụng
analyzer = SourceCodeAnalyzer("./src")
all_funcs = analyzer.analyze_all()
print(f"Analyzed {len(all_funcs)} functions")
Bước 4: AI Test Case Generator
# ai_test_generator.py
import asyncio
from typing import List, Dict, Any
from openai import AsyncOpenAI
from config import AIConfig, get_ai_client
from ast_parser import FunctionInfo
SYSTEM_PROMPT = """Bạn là một Senior QA Engineer với 10 năm kinh nghiệm.
Nhiệm vụ của bạn là tạo test case pytest chất lượng cao cho Python functions.
Yêu cầu:
1. Cover happy path và edge cases
2. Sử dụng pytest.mark.parametrize khi phù hợp
3. Mock external dependencies
4. Đặt descriptive test names theo format: test_{function_name}_{scenario}
5. Include docstring mô tả test case
6. Handle exceptions đúng cách
Output format: Chỉ xuất code Python, không giải thích."""
def build_prompt(func_info: FunctionInfo, source_code: str) -> str:
"""Xây dựng prompt cho AI"""
return f"""Hãy tạo pytest test cases cho function sau:
File: {func_info.file_path}
Line: {func_info.line_number}
Function: {func_info.name}
Args: {func_info.args}
Arg Types: {func_info.arg_types}
Return Type: {func_info.return_type}
Docstring: {func_info.docstring or "Không có docstring"}
Decorators: {', '.join(func_info.decorators) if func_info.decorators else "Không có"}
Source Code:
{source_code}
Yêu cầu:
- Test cases phải cover tất cả logic branches
- Include edge cases (empty, None, boundary values)
- Sử dụng fixtures khi cần thiết
- Mock requests/database calls nếu có
- Tuân thủ pytest best practices
"""
class AITestGenerator:
"""AI-powered test case generator sử dụng HolySheep API"""
def __init__(self, client: AsyncOpenAI = None):
self.client = client or get_ai_client()
self.config = AIConfig()
self.generated_count = 0
self.total_tokens = 0
async def generate_tests(
self,
func_info: FunctionInfo,
source_code: str
) -> Dict[str, Any]:
"""Tạo test cases cho một function"""
prompt = build_prompt(func_info, source_code)
try:
response = await self.client.chat.completions.create(
model=self.config.model,
messages=[
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": prompt}
],
max_tokens=self.config.max_tokens,
temperature=self.config.temperature,
stream=False
)
# Track usage
usage = response.usage
self.total_tokens += usage.total_tokens
self.generated_count += 1
return {
"success": True,
"function": func_info.name,
"test_code": response.choices[0].message.content,
"tokens_used": usage.total_tokens,
"cost_usd": (usage.prompt_tokens * 0.10 + usage.completion_tokens * 0.42) / 1_000_000
}
except Exception as e:
return {
"success": False,
"function": func_info.name,
"error": str(e)
}
async def batch_generate(
self,
functions: List[FunctionInfo],
source_codes: Dict[str, str]
) -> List[Dict[str, Any]]:
"""Generate tests cho nhiều functions"""
tasks = [
self.generate_tests(func, source_codes.get(func.file_path, ""))
for func in functions
]
return await asyncio.gather(*tasks)
Demo usage
async def main():
generator = AITestGenerator()
# Mock function info
sample_func = FunctionInfo(
name="calculate_discount",
file_path="./src/pricing.py",
line_number=42,
docstring="Calculate discount based on user tier",
args=["price", "tier", "membership_years"],
arg_types={"price": "float", "tier": "str", "membership_years": "int"},
return_type="float",
complexity=5,
decorators=[]
)
sample_code = '''
def calculate_discount(price: float, tier: str, membership_years: int) -> float:
"""
Calculate discount based on user tier
Args:
price: Original price
tier: User tier (bronze, silver, gold, platinum)
membership_years: Years of membership
Returns:
Discounted price
"""
base_discount = 0.0
if tier == "bronze":
base_discount = 0.05
elif tier == "silver":
base_discount = 0.10
elif tier == "gold":
base_discount = 0.20
elif tier == "platinum":
base_discount = 0.30
# Loyalty bonus
if membership_years > 5:
base_discount += 0.05
return price * (1 - base_discount)
'''
result = await generator.generate_tests(sample_func, sample_code)
if result["success"]:
print(f"Generated tests for {result['function']}")
print(f"Tokens used: {result['tokens_used']}")
print(f"Cost: ${result['cost_usd']:.6f}")
print(f"\nTest Code:\n{result['test_code']}")
else:
print(f"Error: {result['error']}")
if __name__ == "__main__":
asyncio.run(main())
Bước 5: Pytest Plugin Integration
# conftest.py - Pytest configuration và fixtures
import pytest
import asyncio
from pathlib import Path
from typing import Generator
from openai import AsyncOpenAI
from config import get_ai_client, TestGeneratorConfig
from ast_parser import SourceCodeAnalyzer
from ai_test_generator import AITestGenerator
@pytest.fixture(scope="session")
def event_loop():
"""Create event loop cho async tests"""
loop = asyncio.new_event_loop()
yield loop
loop.close()
@pytest.fixture(scope="session")
def config() -> TestGeneratorConfig:
"""Load configuration"""
return TestGeneratorConfig(
source_dir="./src",
test_dir="./tests/ai_generated",
coverage_threshold=80.0,
max_cases_per_function=5
)
@pytest.fixture(scope="session")
def ai_client() -> AsyncOpenAI:
"""HolySheep AI client fixture"""
return get_ai_client()
@pytest.fixture(scope="session")
def test_generator(ai_client: AsyncOpenAI) -> AITestGenerator:
"""AI test generator fixture"""
return AITestGenerator(client=ai_client)
@pytest.fixture(scope="session")
def source_analyzer(config: TestGeneratorConfig) -> SourceCodeAnalyzer:
"""Source code analyzer fixture"""
analyzer = SourceCodeAnalyzer(config.source_dir)
analyzer.analyze_all()
return analyzer
@pytest.fixture(scope="session")
def generated_tests(
test_generator: AITestGenerator,
source_analyzer: SourceCodeAnalyzer,
config: TestGeneratorConfig,
tmp_path_factory
) -> dict:
"""
Generate all tests once per session.
Cache kết quả để tránh regenerating khi chạy lại tests.
"""
cache_dir = tmp_path_factory.mktemp("test_cache")
cache_file = cache_dir / "generated_tests.json"
if cache_file.exists():
import json
with open(cache_file) as f:
return json.load(f)
# Generate tests cho các functions cần test
source_codes = {}
for func in source_analyzer.functions:
file_path = Path(func.file_path)
if file_path.exists() and str(file_path) not in source_codes:
source_codes[str(file_path)] = file_path.read_text()
results = asyncio.run(
test_generator.batch_generate(
source_analyzer.functions,
source_codes
)
)
# Save to cache
import json
with open(cache_file, 'w') as f:
json.dump(results, f)
return results
Pytest hook để customize test generation
def pytest_collection_modifyitems(config, items):
"""Modify test collection - tự động skip nếu không có source"""
skip_ai = pytest.mark.skip(reason="AI test generation disabled")
if not config.getoption("--enable-ai-tests", default=False):
for item in items:
if "ai_generated" in str(item.fspath):
item.add_marker(skip_ai)
def pytest_addoption(parser):
"""Add custom CLI options"""
parser.addoption(
"--enable-ai-tests",
action="store_true",
default=False,
help="Enable AI-generated tests"
)
parser.addoption(
"--regenerate-tests",
action="store_true",
default=False,
help="Force regenerate AI tests"
)
Bước 6: CLI Tool Hoàn Chỉnh
# generate_tests.py - CLI tool để generate và quản lý tests
#!/usr/bin/env python3
"""
Pytest AI Test Generator CLI
Usage: python generate_tests.py --source ./src --output ./tests
"""
import argparse
import asyncio
import json
import sys
from pathlib import Path
from datetime import datetime
from tabulate import tabulate
from config import get_ai_client, TestGeneratorConfig
from ast_parser import SourceCodeAnalyzer
from ai_test_generator import AITestGenerator
class TestGenerationCLI:
"""CLI cho test generation workflow"""
def __init__(self, config: TestGeneratorConfig):
self.config = config
self.client = get_ai_client()
self.generator = AITestGenerator(self.client)
self.analyzer = SourceCodeAnalyzer(config.source_dir)
self.results = []
def load_source_codes(self) -> dict:
"""Load tất cả source codes"""
source_codes = {}
for py_file in Path(self.config.source_dir).rglob("*.py"):
if "__pycache__" not in str(py_file):
try:
source_codes[str(py_file)] = py_file.read_text(encoding='utf-8')
except Exception as e:
print(f"Warning: Cannot read {py_file}: {e}")
return source_codes
async def run(self, regenerate: bool = False):
"""Execute test generation"""
print("=" * 60)
print("PYTEST AI TEST GENERATOR - HolySheep Edition")
print("=" * 60)
# Step 1: Analyze source code
print("\n[1/4] Analyzing source code...")
functions = self.analyzer.analyze_all()
print(f" Found {len(functions)} functions to analyze")
# Step 2: Load source codes
print("\n[2/4] Loading source codes...")
source_codes = self.load_source_codes()
print(f" Loaded {len(source_codes)} files")
# Step 3: Generate tests
print("\n[3/4] Generating tests via HolySheep AI...")
print(f" Model: {self.generator.config.model}")
print(f" Base URL: {self.generator.config.base_url}")
self.results = await self.generator.batch_generate(functions, source_codes)
# Step 4: Save results
print("\n[4/4] Saving generated tests...")
self._save_results()
# Print summary
self._print_summary()
def _save_results(self):
"""Save generated tests to files"""
output_dir = Path(self.config.test_dir)
output_dir.mkdir(parents=True, exist_ok=True)
success_count = 0
for result in self.results:
if result.get("success"):
success_count += 1
func_name = result["function"]
test_code = result["test_code"]
# Clean test code (remove markdown formatting if any)
if test_code.startswith("```python"):
test_code = test_code.replace("``python", "").replace("``", "")
# Save to file
output_file = output_dir / f"test_{func_name}.py"
output_file.write_text(test_code, encoding='utf-8')
# Save metadata
metadata = {
"generated_at": datetime.now().isoformat(),
"total_functions": len(self.results),
"success_count": success_count,
"total_tokens": self.generator.total_tokens,
"results": [
{
"function": r.get("function"),
"success": r.get("success"),
"tokens_used": r.get("tokens_used"),
"cost_usd": r.get("cost_usd"),
"error": r.get("error")
}
for r in self.results
]
}
metadata_file = output_dir / "generation_metadata.json"
metadata_file.write_text(json.dumps(metadata, indent=2), encoding='utf-8')
print(f" Saved {success_count} test files to {output_dir}")
def _print_summary(self):
"""Print generation summary"""
print("\n" + "=" * 60)
print("GENERATION SUMMARY")
print("=" * 60)
success_results = [r for r in self.results if r.get("success")]
failed_results = [r for r in self.results if not r.get("success")]
# Summary table
table_data = [
["Total Functions", len(self.results)],
["Successful", len(success_results)],
["Failed", len(failed_results)],
["Total Tokens Used", self.generator.total_tokens],
["Total Cost (DeepSeek)", f"${self.generator.total_tokens * 0.42 / 1_000_000:.4f}"],
["Equivalent Claude Cost", f"${self.generator.total_tokens * 15 / 1_000_000:.2f}"],
["Savings vs Claude", f"{((15 - 0.42) / 15 * 100):.1f}%"]
]
print(tabulate(table_data, tablefmt="grid"))
if failed_results:
print("\nFailed Functions:")
for r in failed_results:
print(f" - {r.get('function')}: {r.get('error')}")
def main():
parser = argparse.ArgumentParser(description="AI-powered pytest test generator")
parser.add_argument("--source", default="./src", help="Source directory")
parser.add_argument("--output", default="./tests/ai_generated", help="Output directory")
parser.add_argument("--coverage-threshold", type=float, default=80.0, help="Coverage threshold %%")
parser.add_argument("--max-cases", type=int, default=5, help="Max cases per function")
parser.add_argument("--regenerate", action="store_true", help="Force regenerate")
args = parser.parse_args()
config = TestGeneratorConfig(
source_dir=args.source,
test_dir=args.output,
coverage_threshold=args.coverage_threshold,
max_cases_per_function=args.max_cases
)
cli = TestGenerationCLI(config)
asyncio.run(cli.run(regenerate=args.regenerate))
if __name__ == "__main__":
main()
Chạy Tool
# Tạo file .env
echo "HOLYSHEEP_API_KEY=YOUR_HOLYSHEEP_API_KEY" > .env
Chạy generation
python generate_tests.py --source ./src --output ./tests/ai_generated
Kết quả mẫu:
============================================================
PYTEST AI TEST GENERATOR - HolySheep Edition
============================================================
#
[1/4] Analyzing source code...
Found 42 functions to analyze
#
[2/4] Loading source codes...
Loaded 15 files
#
[3/4] Generating tests via HolySheep AI...
Model: deepseek-chat
Base URL: https://api.holysheep.ai/v1
#
[4/4] Saving generated tests...
Saved 42 test files to ./tests/ai_generated
#
============================================================
GENERATION SUMMARY
============================================================
+----------------------+------------+
| Total Functions | 42 |
| Successful | 40 |
| Failed | 2 |
| Total Tokens Used | 125,000 |
| Total Cost (DeepSeek)| $0.0525 |
| Equivalent Claude | $1.8750 |
| Savings vs Claude | 97.2% |
+----------------------+------------+
Chạy pytest với coverage
pytest ./tests/ai_generated --cov=./src --cov-report=html --cov-report=term
Hoặc với custom config
pytest ./tests/ai_generated --cov=./src --cov-config=.covrc --html=report.html
Lỗi Thường Gặp Và Cách Khắc Phục
1. Lỗi Authentication - Invalid API Key
# ❌ Lỗi thường gặp:
openai.AuthenticationError: Incorrect API key provided
Nguyên nhân:
- API key không đúng hoặc chưa được set
- Key bị expired
- Base URL sai
✅ Cách khắc phục:
1. Kiểm tra biến môi trường
import os
print(f"HOLYSHEEP_API_KEY: {os.getenv('HOLYSHEEP_API_KEY', 'NOT SET')}")
2. Đảm bảo set đúng base_url
client = AsyncOpenAI(
base_url="https://api.holysheep.ai/v1", # Phải là /v1
api_key=os.getenv("HOLYSHEEP_API_KEY")
)
3. Verify credentials
import httpx
response = httpx.get(
"https://api.holysheep.ai/v1/models",
headers={"Authorization": f"Bearer {os.getenv('HOLYSHEEP_API_KEY')}"}
)
print(f"Status: {response.status_code}")
print(f"Models: {response.json()}")
2. Lỗi Rate Limit - 429 Too Many Requests
# ❌ Lỗi:
RateLimitError: Rate limit reached for requests
✅ Cách khắc phục:
import asyncio
from openai import RateLimitError
class RateLimitHandler:
"""Xử lý rate limit với exponential backoff"""
def __init__(self, max_retries: int = 5):
self.max_retries = max_retries
self.base_delay = 1 # seconds
async def call_with_retry(self, func, *args, **kwargs):
"""Gọi API với retry logic"""
for attempt in range(self.max_retries):
try:
return await func(*args, **kwargs)
except RateLimitError as e:
if attempt == self.max_retries - 1:
raise
delay = self.base_delay * (2 ** attempt)
wait_time = min(delay, 60) # Max 60 seconds
print(f"Rate limit hit. Waiting {wait_time}s before retry...")
await asyncio.sleep(wait_time)
except Exception as e:
raise
async def batch_with_throttle(self, tasks, max_concurrent: int = 5):
"""Batch processing với concurrency limit"""
semaphore = asyncio.Semaphore(max_concurrent)
async def limited_task(task):
async with semaphore:
return await self.call_with_retry(task)
return await asyncio.gather(*[limited_task(t) for t in tasks])
Sử dụng:
handler = RateLimitHandler(max_retries=5)
result = await handler.call_with_retry(
generator.generate_tests, func_info, source_code
)
3. Lỗi Parsing - Invalid Response Format
# ❌ Lỗi:
JSONDecodeError hoặc test code không hợp lệ
✅ Cách khắc phục:
import re
from typing import Optional
def clean_test_code(raw_response: str) -> Optional[str]:
"""Clean và validate AI response"""
# Bước 1: Loại bỏ markdown formatting
code = raw_response.strip()
# Remove ```python ... if code.startswith("
python"):
code = code[9:]
if code.startswith("```"):
code = code[3:]
if code.endswith("```"):
code = code[:-3]
code = code.strip()
# Bước 2: Validate syntax
try:
compile(code, '', 'exec')
return code
except SyntaxError as e:
print(f"Syntax error in generated code: {e}")
# Thử fix common issues
# 1. Thêm import pytest nếu thiếu
if "pytest" in code and "import pytest" not in code:
code = "import pytest\n" + code
# 2. Fix missing colons
code = re.sub(r'(\s+)def\s+', r'\1def ', code)
try:
compile(code, '', 'exec')
return code
except SyntaxError:
return None
Validation pipeline
def validate_and_save(code: str, output_path: Path) -> bool:
"""Validate và save test code"""
cleaned = clean_test_code(code)
if cleaned is None:
print(f"Invalid code for {output_path}")
return False
# Additional checks
if "def test_" not in cleaned:
print(f"No test functions found in {output_path}")
return False
output_path.write_text(cleaned, encoding='utf-8')
return True
Sử dụng trong generator:
result = await generator.generate_tests(func_info, source_code)
if result["success"]:
test_code = result["test_code"]
saved = validate_and_save(
test_code,
Path(config.test_dir) / f"test_{func_info.name}.py"
)
print(f"Saved: {saved}")
4. Lỗi Async Event Loop
# ❌ Lỗi:
RuntimeError: Event loop is closed
✅ Cách khắc phục:
import nest_asyncio
nest_asyncio.apply() # Cho phép nested event loops
Hoặc sử dụng playwright-style loop:
import asyncio
from functools import partial
def run_async(coro):
"""Run coroutine trong sync context"""
try:
loop = asyncio.get_running_loop()
# Already in async context
return coro
except RuntimeError:
# No running loop, create new one
return asyncio.run(coro)
Trong pytest:
@pytest.fixture(scope="session")
def event_loop():
"""Shared event loop cho session"""
import platform
if platform.system() == "Windows":
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
loop = asyncio.new_event_loop()
yield loop
loop.close()
Hoặc đơn giản hơn - dùng sync client thay vì async:
from openai import OpenAI # Sync version
def generate_tests_sync(generator: AITestGenerator, func: FunctionInfo, code: str):
"""Sync wrapper cho async generator"""
# Chuyển đổi sang sync
loop = asyncio.new_event_loop()
result = loop.run_until_complete(
generator.generate_tests(func, code)
)
loop.close()
return result
Tính Toán Chi Phí Thực Tế
Dựa trên kinh nghiệm triển khai thực tế của tôi, đây là bảng tính chi phí cho một dự án vừa:
| Metric | Giá Trị |
|---|---|
| Source files analyzed | 50 files |
| Functions generated | 200 functions |
| Avg tokens/function (input) | 1,500 tokens |
| Avg tokens/function (output) | 800 tokens |
| Total input tokens | 300,000 tokens |
| Total output tokens | 160,000 tokens |
| Chi phí DeepSeek V3.2 | $0.12 |
| Chi phí Gemini 2.5 Flash | $1.65 |
| Chi phí Claude Sonnet 4.5 | $2.80 |
| Tiết kiệm vs Claude | 95.7% |