feat(core): Release v0.3.73 with Browser Takeover and Docker Support

Major changes:
- Add browser takeover feature using CDP for authentic browsing
- Implement Docker support with full API server documentation
- Enhance Mockdown with tag preservation system
- Improve parallel crawling performance

This release focuses on authenticity and scalability, introducing the ability
to use users' own browsers while providing containerized deployment options.
Breaking changes include modified browser handling and API response structure.

See CHANGELOG.md for detailed migration guide.
This commit is contained in:
UncleCode
2024-11-05 20:04:18 +08:00
parent c4c6227962
commit 67a23c3182
18 changed files with 1066 additions and 61263 deletions

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import requests
import json
import time
import sys
import base64
import os
from typing import Dict, Any
class Crawl4AiTester:
def __init__(self, base_url: str = "http://localhost:8000"):
self.base_url = base_url
def submit_and_wait(self, request_data: Dict[str, Any], timeout: int = 300) -> Dict[str, Any]:
# Submit crawl job
response = requests.post(f"{self.base_url}/crawl", json=request_data)
task_id = response.json()["task_id"]
print(f"Task ID: {task_id}")
# Poll for result
start_time = time.time()
while True:
if time.time() - start_time > timeout:
raise TimeoutError(f"Task {task_id} did not complete within {timeout} seconds")
result = requests.get(f"{self.base_url}/task/{task_id}")
status = result.json()
if status["status"] == "failed":
print("Task failed:", status.get("error"))
raise Exception(f"Task failed: {status.get('error')}")
if status["status"] == "completed":
return status
time.sleep(2)
def test_docker_deployment(version="basic"):
tester = Crawl4AiTester()
print(f"Testing Crawl4AI Docker {version} version")
# Health check with timeout and retry
max_retries = 5
for i in range(max_retries):
try:
health = requests.get(f"{tester.base_url}/health", timeout=10)
print("Health check:", health.json())
break
except requests.exceptions.RequestException as e:
if i == max_retries - 1:
print(f"Failed to connect after {max_retries} attempts")
sys.exit(1)
print(f"Waiting for service to start (attempt {i+1}/{max_retries})...")
time.sleep(5)
# Test cases based on version
test_basic_crawl(tester)
if version in ["full", "transformer"]:
test_cosine_extraction(tester)
# test_js_execution(tester)
# test_css_selector(tester)
# test_structured_extraction(tester)
# test_llm_extraction(tester)
# test_llm_with_ollama(tester)
# test_screenshot(tester)
def test_basic_crawl(tester: Crawl4AiTester):
print("\n=== Testing Basic Crawl ===")
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 10
}
result = tester.submit_and_wait(request)
print(f"Basic crawl result length: {len(result['result']['markdown'])}")
assert result["result"]["success"]
assert len(result["result"]["markdown"]) > 0
def test_js_execution(tester: Crawl4AiTester):
print("\n=== Testing JS Execution ===")
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 8,
"js_code": [
"const loadMoreButton = Array.from(document.querySelectorAll('button')).find(button => button.textContent.includes('Load More')); loadMoreButton && loadMoreButton.click();"
],
"wait_for": "article.tease-card:nth-child(10)",
"crawler_params": {
"headless": True
}
}
result = tester.submit_and_wait(request)
print(f"JS execution result length: {len(result['result']['markdown'])}")
assert result["result"]["success"]
def test_css_selector(tester: Crawl4AiTester):
print("\n=== Testing CSS Selector ===")
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 7,
"css_selector": ".wide-tease-item__description",
"crawler_params": {
"headless": True
},
"extra": {"word_count_threshold": 10}
}
result = tester.submit_and_wait(request)
print(f"CSS selector result length: {len(result['result']['markdown'])}")
assert result["result"]["success"]
def test_structured_extraction(tester: Crawl4AiTester):
print("\n=== Testing Structured Extraction ===")
schema = {
"name": "Coinbase Crypto Prices",
"baseSelector": ".cds-tableRow-t45thuk",
"fields": [
{
"name": "crypto",
"selector": "td:nth-child(1) h2",
"type": "text",
},
{
"name": "symbol",
"selector": "td:nth-child(1) p",
"type": "text",
},
{
"name": "price",
"selector": "td:nth-child(2)",
"type": "text",
}
],
}
request = {
"urls": "https://www.coinbase.com/explore",
"priority": 9,
"extraction_config": {
"type": "json_css",
"params": {
"schema": schema
}
}
}
result = tester.submit_and_wait(request)
extracted = json.loads(result["result"]["extracted_content"])
print(f"Extracted {len(extracted)} items")
print("Sample item:", json.dumps(extracted[0], indent=2))
assert result["result"]["success"]
assert len(extracted) > 0
def test_llm_extraction(tester: Crawl4AiTester):
print("\n=== Testing LLM Extraction ===")
schema = {
"type": "object",
"properties": {
"model_name": {
"type": "string",
"description": "Name of the OpenAI model."
},
"input_fee": {
"type": "string",
"description": "Fee for input token for the OpenAI model."
},
"output_fee": {
"type": "string",
"description": "Fee for output token for the OpenAI model."
}
},
"required": ["model_name", "input_fee", "output_fee"]
}
request = {
"urls": "https://openai.com/api/pricing",
"priority": 8,
"extraction_config": {
"type": "llm",
"params": {
"provider": "openai/gpt-4o-mini",
"api_token": os.getenv("OPENAI_API_KEY"),
"schema": schema,
"extraction_type": "schema",
"instruction": """From the crawled content, extract all mentioned model names along with their fees for input and output tokens."""
}
},
"crawler_params": {"word_count_threshold": 1}
}
try:
result = tester.submit_and_wait(request)
extracted = json.loads(result["result"]["extracted_content"])
print(f"Extracted {len(extracted)} model pricing entries")
print("Sample entry:", json.dumps(extracted[0], indent=2))
assert result["result"]["success"]
except Exception as e:
print(f"LLM extraction test failed (might be due to missing API key): {str(e)}")
def test_llm_with_ollama(tester: Crawl4AiTester):
print("\n=== Testing LLM with Ollama ===")
schema = {
"type": "object",
"properties": {
"article_title": {
"type": "string",
"description": "The main title of the news article"
},
"summary": {
"type": "string",
"description": "A brief summary of the article content"
},
"main_topics": {
"type": "array",
"items": {"type": "string"},
"description": "Main topics or themes discussed in the article"
}
}
}
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 8,
"extraction_config": {
"type": "llm",
"params": {
"provider": "ollama/llama2",
"schema": schema,
"extraction_type": "schema",
"instruction": "Extract the main article information including title, summary, and main topics."
}
},
"extra": {"word_count_threshold": 1},
"crawler_params": {"verbose": True}
}
try:
result = tester.submit_and_wait(request)
extracted = json.loads(result["result"]["extracted_content"])
print("Extracted content:", json.dumps(extracted, indent=2))
assert result["result"]["success"]
except Exception as e:
print(f"Ollama extraction test failed: {str(e)}")
def test_cosine_extraction(tester: Crawl4AiTester):
print("\n=== Testing Cosine Extraction ===")
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 8,
"extraction_config": {
"type": "cosine",
"params": {
"semantic_filter": "business finance economy",
"word_count_threshold": 10,
"max_dist": 0.2,
"top_k": 3
}
}
}
try:
result = tester.submit_and_wait(request)
extracted = json.loads(result["result"]["extracted_content"])
print(f"Extracted {len(extracted)} text clusters")
print("First cluster tags:", extracted[0]["tags"])
assert result["result"]["success"]
except Exception as e:
print(f"Cosine extraction test failed: {str(e)}")
def test_screenshot(tester: Crawl4AiTester):
print("\n=== Testing Screenshot ===")
request = {
"urls": "https://www.nbcnews.com/business",
"priority": 5,
"screenshot": True,
"crawler_params": {
"headless": True
}
}
result = tester.submit_and_wait(request)
print("Screenshot captured:", bool(result["result"]["screenshot"]))
if result["result"]["screenshot"]:
# Save screenshot
screenshot_data = base64.b64decode(result["result"]["screenshot"])
with open("test_screenshot.jpg", "wb") as f:
f.write(screenshot_data)
print("Screenshot saved as test_screenshot.jpg")
assert result["result"]["success"]
if __name__ == "__main__":
version = sys.argv[1] if len(sys.argv) > 1 else "basic"
# version = "full"
test_docker_deployment(version)