Files
crawl4ai/crawl4ai/async_webcrawler.py
2024-10-21 17:58:39 -04:00

277 lines
10 KiB
Python

import os
import time
from pathlib import Path
from typing import Optional
import json
import asyncio
from .models import CrawlResult
from .async_database import async_db_manager
from .chunking_strategy import *
from .extraction_strategy import *
from .async_crawler_strategy import AsyncCrawlerStrategy, AsyncPlaywrightCrawlerStrategy, AsyncCrawlResponse
from .content_scrapping_strategy import WebScrappingStrategy
from .config import MIN_WORD_THRESHOLD, IMAGE_DESCRIPTION_MIN_WORD_THRESHOLD
from .utils import (
sanitize_input_encode,
InvalidCSSSelectorError,
format_html
)
class AsyncWebCrawler:
def __init__(
self,
crawler_strategy: Optional[AsyncCrawlerStrategy] = None,
always_by_pass_cache: bool = False,
base_directory: str = str(Path.home()),
**kwargs,
):
self.crawler_strategy = crawler_strategy or AsyncPlaywrightCrawlerStrategy(
**kwargs
)
self.always_by_pass_cache = always_by_pass_cache
self.crawl4ai_folder = os.path.join(base_directory, ".crawl4ai")
os.makedirs(self.crawl4ai_folder, exist_ok=True)
os.makedirs(f"{self.crawl4ai_folder}/cache", exist_ok=True)
self.ready = False
self.verbose = kwargs.get("verbose", False)
async def __aenter__(self):
await self.crawler_strategy.__aenter__()
await self.awarmup()
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
await self.crawler_strategy.__aexit__(exc_type, exc_val, exc_tb)
async def awarmup(self):
if self.verbose:
print("[LOG] 🌤️ Warming up the AsyncWebCrawler")
await async_db_manager.ainit_db()
await self.arun(
url="https://google.com/",
word_count_threshold=5,
bypass_cache=False,
verbose=False,
)
self.ready = True
if self.verbose:
print("[LOG] 🌞 AsyncWebCrawler is ready to crawl")
async def arun(
self,
url: str,
word_count_threshold=MIN_WORD_THRESHOLD,
extraction_strategy: ExtractionStrategy = None,
chunking_strategy: ChunkingStrategy = RegexChunking(),
bypass_cache: bool = False,
css_selector: str = None,
screenshot: bool = False,
user_agent: str = None,
verbose=True,
**kwargs,
) -> CrawlResult:
try:
extraction_strategy = extraction_strategy or NoExtractionStrategy()
extraction_strategy.verbose = verbose
if not isinstance(extraction_strategy, ExtractionStrategy):
raise ValueError("Unsupported extraction strategy")
if not isinstance(chunking_strategy, ChunkingStrategy):
raise ValueError("Unsupported chunking strategy")
word_count_threshold = max(word_count_threshold, MIN_WORD_THRESHOLD)
async_response: AsyncCrawlResponse = None
cached = None
screenshot_data = None
extracted_content = None
if not bypass_cache and not self.always_by_pass_cache:
cached = await async_db_manager.aget_cached_url(url)
if kwargs.get("warmup", True) and not self.ready:
return None
if cached:
html = sanitize_input_encode(cached[1])
extracted_content = sanitize_input_encode(cached[4])
if screenshot:
screenshot_data = cached[9]
if not screenshot_data:
cached = None
if not cached or not html:
t1 = time.time()
if user_agent:
self.crawler_strategy.update_user_agent(user_agent)
async_response: AsyncCrawlResponse = await self.crawler_strategy.crawl(url, screenshot=screenshot, **kwargs)
html = sanitize_input_encode(async_response.html)
screenshot_data = async_response.screenshot
t2 = time.time()
if verbose:
print(
f"[LOG] 🚀 Crawling done for {url}, success: {bool(html)}, time taken: {t2 - t1:.2f} seconds"
)
crawl_result = await self.aprocess_html(
url,
html,
extracted_content,
word_count_threshold,
extraction_strategy,
chunking_strategy,
css_selector,
screenshot_data,
verbose,
bool(cached),
async_response=async_response,
**kwargs,
)
crawl_result.status_code = async_response.status_code if async_response else 200
crawl_result.response_headers = async_response.response_headers if async_response else {}
crawl_result.success = bool(html)
crawl_result.session_id = kwargs.get("session_id", None)
return crawl_result
except Exception as e:
if not hasattr(e, "msg"):
e.msg = str(e)
print(f"[ERROR] 🚫 Failed to crawl {url}, error: {e.msg}")
return CrawlResult(url=url, html="", success=False, error_message=e.msg)
async def arun_many(
self,
urls: List[str],
word_count_threshold=MIN_WORD_THRESHOLD,
extraction_strategy: ExtractionStrategy = None,
chunking_strategy: ChunkingStrategy = RegexChunking(),
bypass_cache: bool = False,
css_selector: str = None,
screenshot: bool = False,
user_agent: str = None,
verbose=True,
**kwargs,
) -> List[CrawlResult]:
tasks = [
self.arun(
url,
word_count_threshold,
extraction_strategy,
chunking_strategy,
bypass_cache,
css_selector,
screenshot,
user_agent,
verbose,
**kwargs
)
for url in urls
]
return await asyncio.gather(*tasks)
async def aprocess_html(
self,
url: str,
html: str,
extracted_content: str,
word_count_threshold: int,
extraction_strategy: ExtractionStrategy,
chunking_strategy: ChunkingStrategy,
css_selector: str,
screenshot: str,
verbose: bool,
is_cached: bool,
**kwargs,
) -> CrawlResult:
t = time.time()
# Extract content from HTML
try:
t1 = time.time()
scrapping_strategy = WebScrappingStrategy()
result = await scrapping_strategy.ascrap(
url,
html,
word_count_threshold=word_count_threshold,
css_selector=css_selector,
only_text=kwargs.get("only_text", False),
image_description_min_word_threshold=kwargs.get(
"image_description_min_word_threshold", IMAGE_DESCRIPTION_MIN_WORD_THRESHOLD
),
)
if verbose:
print(
f"[LOG] 🚀 Content extracted for {url}, success: True, time taken: {time.time() - t1:.2f} seconds"
)
if result is None:
raise ValueError(f"Process HTML, Failed to extract content from the website: {url}")
except InvalidCSSSelectorError as e:
raise ValueError(str(e))
except Exception as e:
raise ValueError(f"Process HTML, Failed to extract content from the website: {url}, error: {str(e)}")
cleaned_html = sanitize_input_encode(result.get("cleaned_html", ""))
markdown = sanitize_input_encode(result.get("markdown", ""))
media = result.get("media", [])
links = result.get("links", [])
metadata = result.get("metadata", {})
if extracted_content is None and extraction_strategy and chunking_strategy:
if verbose:
print(
f"[LOG] 🔥 Extracting semantic blocks for {url}, Strategy: {self.__class__.__name__}"
)
# Check if extraction strategy is type of JsonCssExtractionStrategy
if isinstance(extraction_strategy, JsonCssExtractionStrategy) or isinstance(extraction_strategy, JsonCssExtractionStrategy):
extraction_strategy.verbose = verbose
extracted_content = extraction_strategy.run(url, [html])
extracted_content = json.dumps(extracted_content, indent=4, default=str, ensure_ascii=False)
else:
sections = chunking_strategy.chunk(markdown)
extracted_content = extraction_strategy.run(url, sections)
extracted_content = json.dumps(extracted_content, indent=4, default=str, ensure_ascii=False)
if verbose:
print(
f"[LOG] 🚀 Extraction done for {url}, time taken: {time.time() - t:.2f} seconds."
)
screenshot = None if not screenshot else screenshot
if not is_cached:
await async_db_manager.acache_url(
url,
html,
cleaned_html,
markdown,
extracted_content,
True,
json.dumps(media),
json.dumps(links),
json.dumps(metadata),
screenshot=screenshot,
)
return CrawlResult(
url=url,
html=html,
cleaned_html=format_html(cleaned_html),
markdown=markdown,
media=media,
links=links,
metadata=metadata,
screenshot=screenshot,
extracted_content=extracted_content,
success=True,
error_message="",
)
async def aclear_cache(self):
await async_db_manager.aclear_db()
async def aflush_cache(self):
await async_db_manager.aflush_db()
async def aget_cache_size(self):
return await async_db_manager.aget_total_count()