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8 Commits

Author SHA1 Message Date
UncleCode
406702a77f Delete .do/deploy.template.yaml 2024-12-31 17:33:39 +08:00
UncleCode
7391d6be73 Update README.md (#390) 2024-12-30 21:24:43 +08:00
UncleCode
e4e23065f1 Update README.md (#389) 2024-12-30 21:24:06 +08:00
Robin Singh
78768fd714 Update simple-crawling.md (#379)
In the comprehensive example,

AttributeError: type object 'CacheMode' has no attribute 'ENABLE'. Did you mean: 'ENABLED'?
2024-12-27 17:42:59 +08:00
Haopeng138
bacbeb3ed4 Fix #340 example llm_extraction (#358)
@Haopeng138 Thank you so much. They are still part of the library. I forgot to update them since I moved the asynchronous versions years ago. I really appreciate it. I have to say that I feel weak in the documentation. That's why I spent a lot of time on it last week. Now, when you mention some of the things in the example folder, I realize I forgot about the example folder. I'll try to update it more. If you find anything else, please help and support. Thank you. I will add your name to contributor name as well.
2024-12-24 19:56:07 +08:00
UncleCode
ed7bc1909c Bump version to 0.4.22 2024-12-15 19:49:38 +08:00
UncleCode
e9e5b5642d Fix js_snipprt issue 0.4.21
bump to 0.4.22
2024-12-15 19:49:30 +08:00
UncleCode
7524aa7b5e Feature: Add Markdown generation to CrawlerRunConfig
- Added markdown generator parameter to CrawlerRunConfig in `async_configs.py`.
  - Implemented logic for Markdown generation in content scraping in `async_webcrawler.py`.
  - Updated version number to 0.4.21 in `__version__.py`.
2024-12-13 21:51:38 +08:00
12 changed files with 87 additions and 87 deletions

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@@ -1,22 +0,0 @@
spec:
name: crawl4ai
services:
- name: crawl4ai
git:
branch: 0.3.74
repo_clone_url: https://github.com/unclecode/crawl4ai.git
dockerfile_path: Dockerfile
http_port: 11235
instance_count: 1
instance_size_slug: professional-xs
health_check:
http_path: /health
envs:
- key: INSTALL_TYPE
value: "basic"
- key: PYTHON_VERSION
value: "3.10"
- key: ENABLE_GPU
value: "false"
routes:
- path: /

View File

@@ -1 +1,2 @@
include requirements.txt
include requirements.txt
recursive-include crawl4ai/js_snippet *.js

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@@ -1,4 +1,4 @@
# 🚀🤖 Crawl4AI: Crawl Smarter, Faster, Freely. For AI.
# 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper.
<a href="https://trendshift.io/repositories/11716" target="_blank"><img src="https://trendshift.io/api/badge/repositories/11716" alt="unclecode%2Fcrawl4ai | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

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@@ -1,2 +1,2 @@
# crawl4ai/_version.py
__version__ = "0.4.2"
__version__ = "0.4.22"

View File

@@ -7,6 +7,7 @@ from .config import (
from .user_agent_generator import UserAgentGenerator
from .extraction_strategy import ExtractionStrategy
from .chunking_strategy import ChunkingStrategy
from .markdown_generation_strategy import MarkdownGenerationStrategy
class BrowserConfig:
"""
@@ -269,6 +270,7 @@ class CrawlerRunConfig:
word_count_threshold: int = MIN_WORD_THRESHOLD ,
extraction_strategy : ExtractionStrategy=None, # Will default to NoExtractionStrategy if None
chunking_strategy : ChunkingStrategy= None, # Will default to RegexChunking if None
markdown_generator : MarkdownGenerationStrategy = None,
content_filter=None,
cache_mode=None,
session_id: str = None,
@@ -309,6 +311,7 @@ class CrawlerRunConfig:
self.word_count_threshold = word_count_threshold
self.extraction_strategy = extraction_strategy
self.chunking_strategy = chunking_strategy
self.markdown_generator = markdown_generator
self.content_filter = content_filter
self.cache_mode = cache_mode
self.session_id = session_id
@@ -364,6 +367,7 @@ class CrawlerRunConfig:
word_count_threshold=kwargs.get("word_count_threshold", 200),
extraction_strategy=kwargs.get("extraction_strategy"),
chunking_strategy=kwargs.get("chunking_strategy"),
markdown_generator=kwargs.get("markdown_generator"),
content_filter=kwargs.get("content_filter"),
cache_mode=kwargs.get("cache_mode"),
session_id=kwargs.get("session_id"),

View File

@@ -7,7 +7,8 @@ from pathlib import Path
from typing import Optional, List, Union
import json
import asyncio
from contextlib import nullcontext, asynccontextmanager
# from contextlib import nullcontext, asynccontextmanager
from contextlib import asynccontextmanager
from .models import CrawlResult, MarkdownGenerationResult
from .async_database import async_db_manager
from .chunking_strategy import *
@@ -15,6 +16,7 @@ from .content_filter_strategy import *
from .extraction_strategy import *
from .async_crawler_strategy import AsyncCrawlerStrategy, AsyncPlaywrightCrawlerStrategy, AsyncCrawlResponse
from .cache_context import CacheMode, CacheContext, _legacy_to_cache_mode
from .markdown_generation_strategy import DefaultMarkdownGenerator, MarkdownGenerationStrategy
from .content_scraping_strategy import WebScrapingStrategy
from .async_logger import AsyncLogger
from .async_configs import BrowserConfig, CrawlerRunConfig
@@ -132,17 +134,12 @@ class AsyncWebCrawler:
async def __aexit__(self, exc_type, exc_val, exc_tb):
await self.crawler_strategy.__aexit__(exc_type, exc_val, exc_tb)
@asynccontextmanager
async def nullcontext(self):
yield
async def awarmup(self):
"""Initialize the crawler with warm-up sequence."""
self.logger.info(f"Crawl4AI {crawl4ai_version}", tag="INIT")
self.ready = True
@asynccontextmanager
async def nullcontext(self):
"""异步空上下文管理器"""
@@ -323,7 +320,8 @@ class AsyncWebCrawler:
config=config, # Pass the config object instead of individual parameters
screenshot=screenshot_data,
pdf_data=pdf_data,
verbose=config.verbose
verbose=config.verbose,
**kwargs
)
# Set response data
@@ -424,7 +422,8 @@ class AsyncWebCrawler:
css_selector=config.css_selector,
only_text=config.only_text,
image_description_min_word_threshold=config.image_description_min_word_threshold,
content_filter=config.content_filter
content_filter=config.content_filter,
**kwargs
)
if result is None:
@@ -435,16 +434,29 @@ class AsyncWebCrawler:
except Exception as e:
raise ValueError(f"Process HTML, Failed to extract content from the website: {url}, error: {str(e)}")
# Extract results
markdown_v2 = result.get("markdown_v2", None)
cleaned_html = sanitize_input_encode(result.get("cleaned_html", ""))
markdown = sanitize_input_encode(result.get("markdown", ""))
fit_markdown = sanitize_input_encode(result.get("fit_markdown", ""))
fit_html = sanitize_input_encode(result.get("fit_html", ""))
media = result.get("media", [])
links = result.get("links", [])
metadata = result.get("metadata", {})
# Markdown Generation
markdown_generator: Optional[MarkdownGenerationStrategy] = config.markdown_generator or DefaultMarkdownGenerator()
if not config.content_filter and not markdown_generator.content_filter:
markdown_generator.content_filter = PruningContentFilter()
markdown_result: MarkdownGenerationResult = markdown_generator.generate_markdown(
cleaned_html=cleaned_html,
base_url=url,
# html2text_options=kwargs.get('html2text', {})
)
markdown_v2 = markdown_result
markdown = sanitize_input_encode(markdown_result.raw_markdown)
# Log processing completion
self.logger.info(
message="Processed {url:.50}... | Time: {timing}ms",

View File

@@ -602,16 +602,16 @@ class WebScrapingStrategy(ContentScrapingStrategy):
cleaned_html = str_body.replace('\n\n', '\n').replace(' ', ' ')
markdown_content = self._generate_markdown_content(
cleaned_html=cleaned_html,
html=html,
url=url,
success=success,
**kwargs
)
# markdown_content = self._generate_markdown_content(
# cleaned_html=cleaned_html,
# html=html,
# url=url,
# success=success,
# **kwargs
# )
return {
**markdown_content,
# **markdown_content,
'cleaned_html': cleaned_html,
'success': success,
'media': media,

View File

@@ -1,41 +1,40 @@
import os
import time
from crawl4ai.web_crawler import WebCrawler
from crawl4ai.chunking_strategy import *
from crawl4ai.extraction_strategy import *
from crawl4ai.crawler_strategy import *
import asyncio
from pydantic import BaseModel, Field
url = r'https://openai.com/api/pricing/'
crawler = WebCrawler()
crawler.warmup()
from pydantic import BaseModel, Field
class OpenAIModelFee(BaseModel):
model_name: str = Field(..., description="Name of the OpenAI model.")
input_fee: str = Field(..., description="Fee for input token for the OpenAI model.")
output_fee: str = Field(..., description="Fee for output token for the OpenAI model.")
result = crawler.run(
url=url,
word_count_threshold=1,
extraction_strategy= LLMExtractionStrategy(
# provider= "openai/gpt-4o", api_token = os.getenv('OPENAI_API_KEY'),
provider= "groq/llama-3.1-70b-versatile", api_token = os.getenv('GROQ_API_KEY'),
schema=OpenAIModelFee.model_json_schema(),
extraction_type="schema",
instruction="From the crawled content, extract all mentioned model names along with their "\
"fees for input and output tokens. Make sure not to miss anything in the entire content. "\
'One extracted model JSON format should look like this: '\
'{ "model_name": "GPT-4", "input_fee": "US$10.00 / 1M tokens", "output_fee": "US$30.00 / 1M tokens" }'
),
bypass_cache=True,
)
from crawl4ai import AsyncWebCrawler
model_fees = json.loads(result.extracted_content)
async def main():
# Use AsyncWebCrawler
async with AsyncWebCrawler() as crawler:
result = await crawler.arun(
url=url,
word_count_threshold=1,
extraction_strategy= LLMExtractionStrategy(
# provider= "openai/gpt-4o", api_token = os.getenv('OPENAI_API_KEY'),
provider= "groq/llama-3.1-70b-versatile", api_token = os.getenv('GROQ_API_KEY'),
schema=OpenAIModelFee.model_json_schema(),
extraction_type="schema",
instruction="From the crawled content, extract all mentioned model names along with their " \
"fees for input and output tokens. Make sure not to miss anything in the entire content. " \
'One extracted model JSON format should look like this: ' \
'{ "model_name": "GPT-4", "input_fee": "US$10.00 / 1M tokens", "output_fee": "US$30.00 / 1M tokens" }'
),
print(len(model_fees))
)
print("Success:", result.success)
model_fees = json.loads(result.extracted_content)
print(len(model_fees))
with open(".data/data.json", "w", encoding="utf-8") as f:
f.write(result.extracted_content)
with open(".data/data.json", "w", encoding="utf-8") as f:
f.write(result.extracted_content)
asyncio.run(main())

View File

@@ -142,6 +142,7 @@ async def extract_structured_data_using_llm(provider: str, api_token: str = None
crawler_config = CrawlerRunConfig(
cache_mode=CacheMode.BYPASS,
word_count_threshold=1,
page_timeout = 80000,
extraction_strategy=LLMExtractionStrategy(
provider=provider,
api_token=api_token,
@@ -497,21 +498,21 @@ async def main():
# Advanced examples
# await extract_structured_data_using_css_extractor()
# await extract_structured_data_using_llm("openai/gpt-4o", os.getenv("OPENAI_API_KEY"))
await extract_structured_data_using_llm("openai/gpt-4o", os.getenv("OPENAI_API_KEY"))
# await crawl_dynamic_content_pages_method_1()
# await crawl_dynamic_content_pages_method_2()
# Browser comparisons
await crawl_custom_browser_type()
# await crawl_custom_browser_type()
# Performance testing
# await speed_comparison()
# Screenshot example
await capture_and_save_screenshot(
"https://www.example.com",
os.path.join(__location__, "tmp/example_screenshot.jpg")
)
# await capture_and_save_screenshot(
# "https://www.example.com",
# os.path.join(__location__, "tmp/example_screenshot.jpg")
# )
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -239,8 +239,10 @@ async def crawl_dynamic_content_pages_method_1():
all_commits = []
js_next_page = """
const button = document.querySelector('a[data-testid="pagination-next-button"]');
if (button) button.click();
(() => {
const button = document.querySelector('a[data-testid="pagination-next-button"]');
if (button) button.click();
})();
"""
for page in range(3): # Crawl 3 pages
@@ -604,14 +606,14 @@ async def fit_markdown_remove_overlay():
async def main():
await extract_structured_data_using_llm("openai/gpt-4o", os.getenv("OPENAI_API_KEY"))
# await extract_structured_data_using_llm("openai/gpt-4o", os.getenv("OPENAI_API_KEY"))
await simple_crawl()
await simple_example_with_running_js_code()
await simple_example_with_css_selector()
# await use_proxy()
await capture_and_save_screenshot("https://www.example.com", os.path.join(__location__, "tmp/example_screenshot.jpg"))
await extract_structured_data_using_css_extractor()
# await simple_crawl()
# await simple_example_with_running_js_code()
# await simple_example_with_css_selector()
# # await use_proxy()
# await capture_and_save_screenshot("https://www.example.com", os.path.join(__location__, "tmp/example_screenshot.jpg"))
# await extract_structured_data_using_css_extractor()
# LLM extraction examples
# await extract_structured_data_using_llm()

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@@ -99,7 +99,7 @@ async def main():
remove_overlay_elements=True,
# Cache control
cache_mode=CacheMode.ENABLE # Use cache if available
cache_mode=CacheMode.ENABLED # Use cache if available
)
if result.success:

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@@ -57,6 +57,9 @@ setup(
author_email="unclecode@kidocode.com",
license="MIT",
packages=find_packages(),
package_data={
'crawl4ai': ['js_snippet/*.js'] # This matches the exact path structure
},
install_requires=default_requirements
+ ["playwright", "aiofiles"], # Added aiofiles
extras_require={