Merge branch 'main' of https://github.com/unclecode/crawl4ai

This commit updates the version number to v0.2.73 and makes corresponding changes in the README.md and Dockerfile.

Docker file install the default mode, this resolve many of installation issues.

Additionally, the installation instructions are updated to include support for different modes. Setup.py doesn't have anymore dependancy on Spacy.

The change log is also updated to reflect these changes.

Supporting websites need with-head browser.

.gitignore

@@ -182,3 +182,9 @@ docs/examples/.chainlit/*
 
 local/
 .files/
+
+a.txt
+.lambda_function.py
+ec2*
+
+update_changelog.sh

CHANGELOG.md

@@ -1,5 +1,44 @@
 # Changelog
 
+## [v0.2.73] - 2024-07-03
+
+💡 In this release, we've bumped the version to v0.2.73 and refreshed our documentation to ensure you have the best experience with our project.
+
+* Supporting website need "with-head" mode to crawl the website with head.
+* Fixing the installation issues for setup.py and dockerfile.
+* Resolve multiple issues.
+
+## [v0.2.72] - 2024-06-30
+
+This release brings exciting updates and improvements to our project! 🎉
+
+* 📚 **Documentation Updates**: Our documentation has been revamped to reflect the latest changes and additions.
+* 🚀 **New Modes in setup.py**: We've added support for three new modes in setup.py: default, torch, and transformers. This enhances the project's flexibility and usability.
+* 🐳 **Docker File Updates**: The Docker file has been updated to ensure seamless compatibility with the new modes and improvements.
+* 🕷️ **Temporary Solution for Headless Crawling**: We've implemented a temporary solution to overcome issues with crawling websites in headless mode.
+
+These changes aim to improve the overall user experience, provide more flexibility, and enhance the project's performance. We're thrilled to share these updates with you and look forward to continuing to evolve and improve our project!
+
+## [0.2.71] - 2024-06-26
+
+**Improved Error Handling and Performance** 🚧
+
+* 🚫 Refactored `crawler_strategy.py` to handle exceptions and provide better error messages, making it more robust and reliable.
+* 💻 Optimized the `get_content_of_website_optimized` function in `utils.py` for improved performance, reducing potential bottlenecks.
+* 💻 Updated `utils.py` with the latest changes, ensuring consistency and accuracy.
+* 🚫 Migrated to `ChromeDriverManager` to resolve Chrome driver download issues, providing a smoother user experience.
+
+These changes focus on refining the existing codebase, resulting in a more stable, efficient, and user-friendly experience. With these improvements, you can expect fewer errors and better performance in the crawler strategy and utility functions.
+
+## [0.2.71] - 2024-06-25
+### Fixed
+- Speed up twice the extraction function.
+
+
+## [0.2.6] - 2024-06-22
+### Fixed
+- Fix issue #19: Update Dockerfile to ensure compatibility across multiple platforms.
+
 ## [0.2.5] - 2024-06-18
 ### Added
 - Added five important hooks to the crawler:

Dockerfile

@@ -18,12 +18,11 @@ RUN apt-get update && \
     software-properties-common && \
     rm -rf /var/lib/apt/lists/*    
 
-# Install Python dependencies
+# Copy the application code
-COPY requirements.txt .
+COPY . .
-RUN pip install --no-cache-dir -r requirements.txt && \
+
-    pip install --no-cache-dir spacy torch onnxruntime uvicorn && \
+# Install Crawl4AI using the local setup.py (which will use the default installation)
-    python -m spacy download en_core_web_sm
+RUN pip install --no-cache-dir .
-    # pip install --no-cache-dir spacy torch torchvision torchaudio onnxruntime uvicorn && \
 
 # Install Google Chrome and ChromeDriver
 RUN wget -q -O - https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key add - && \
@@ -33,9 +32,6 @@ RUN wget -q -O - https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key
     wget -O /tmp/chromedriver.zip http://chromedriver.storage.googleapis.com/`curl -sS chromedriver.storage.googleapis.com/LATEST_RELEASE`/chromedriver_linux64.zip && \
     unzip /tmp/chromedriver.zip chromedriver -d /usr/local/bin/
 
-# Copy the rest of the application code
-COPY . .
-
 # Set environment to use Chrome and ChromeDriver properly
 ENV CHROME_BIN=/usr/bin/google-chrome \
     CHROMEDRIVER=/usr/local/bin/chromedriver \
@@ -43,9 +39,6 @@ ENV CHROME_BIN=/usr/bin/google-chrome \
     DBUS_SESSION_BUS_ADDRESS=/dev/null \
     PYTHONUNBUFFERED=1
 
-#  pip install -e .[all]
-RUN pip install --no-cache-dir -e .[all]
-
 # Ensure the PATH environment variable includes the location of the installed packages
 ENV PATH /opt/conda/bin:$PATH   
 
@@ -53,10 +46,13 @@ ENV PATH /opt/conda/bin:$PATH
 EXPOSE 80
 
 # Download models call cli "crawl4ai-download-models"
-RUN crawl4ai-download-models
+# RUN crawl4ai-download-models
-# RUN python crawl4ai/model_loader.py
+
+# Install mkdocs
+RUN pip install mkdocs mkdocs-terminal
+
+# Call mkdocs to build the documentation
+RUN mkdocs build
 
 # Run uvicorn
 CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "80", "--workers", "4"]
-
-

README.md

@@ -1,4 +1,4 @@
-# Crawl4AI v0.2.5 🕷️🤖
+# Crawl4AI v0.2.73 🕷️🤖
 
 [![GitHub Stars](https://img.shields.io/github/stars/unclecode/crawl4ai?style=social)](https://github.com/unclecode/crawl4ai/stargazers)
 [![GitHub Forks](https://img.shields.io/github/forks/unclecode/crawl4ai?style=social)](https://github.com/unclecode/crawl4ai/network/members)
@@ -11,7 +11,9 @@ Crawl4AI simplifies web crawling and data extraction, making it accessible for l
 ## Try it Now!
 
 - Use as REST API: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zODYjhemJ5bUmYceWpVoBMVpd0ofzNBZ?usp=sharing)
-- Use as Python library: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wz8u30rvbq6Scodye9AGCw8Qg_Z8QGsk)
+- Use as Python library: This collab is a bit outdated. I'm updating it with the newest versions, so please refer to the website for the latest documentation. This will be updated in a few days, and you'll have the latest version here. Thank you so much. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wz8u30rvbq6Scodye9AGCw8Qg_Z8QGsk)
+
+✨ visit our [Documentation Website](https://crawl4ai.com/mkdocs/)
 
 ## Features ✨
 
@@ -47,9 +49,43 @@ crawler.warmup()
 result = crawler.run(url="https://www.nbcnews.com/business")
 
 # Print the extracted content
-print(result.extracted_content)
+print(result.markdown)
 ```
 
+## How to install 🛠    
+```bash
+virtualenv venv
+source venv/bin/activate
+pip install "crawl4ai @ git+https://github.com/unclecode/crawl4ai.git"
+```️
+
+### Speed-First Design 🚀
+
+Perhaps the most important design principle for this library is speed. We need to ensure it can handle many links and resources in parallel as quickly as possible. By combining this speed with fast LLMs like Groq, the results will be truly amazing.
+
+```python
+import time
+from crawl4ai.web_crawler import WebCrawler
+crawler = WebCrawler()
+crawler.warmup()
+
+start = time.time()
+url = r"https://www.nbcnews.com/business"
+result = crawler.run( url, word_count_threshold=10, bypass_cache=True)
+end = time.time()
+print(f"Time taken: {end - start}")
+```
+
+Let's take a look the calculated time for the above code snippet:
+
+```bash
+[LOG] 🚀 Crawling done, success: True, time taken: 1.3623387813568115 seconds
+[LOG] 🚀 Content extracted, success: True, time taken: 0.05715131759643555 seconds
+[LOG] 🚀 Extraction, time taken: 0.05750393867492676 seconds.
+Time taken: 1.439958095550537
+```
+Fetching the content from the page took 1.3623 seconds, and extracting the content took 0.0575 seconds. 🚀
+
 ### Extract Structured Data from Web Pages 📊
 
 Crawl all OpenAI models and their fees from the official page.
@@ -58,19 +94,30 @@ Crawl all OpenAI models and their fees from the official page.
 import os
 from crawl4ai import WebCrawler
 from crawl4ai.extraction_strategy import LLMExtractionStrategy
+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 ßfor the OpenAI model.")
 
 url = 'https://openai.com/api/pricing/'
 crawler = WebCrawler()
 crawler.warmup()
 
 result = crawler.run(
-    url=url,
+        url=url,
-    extraction_strategy=LLMExtractionStrategy(
+        word_count_threshold=1,
-        provider="openai/gpt-4",
+        extraction_strategy= LLMExtractionStrategy(
-        api_token=os.getenv('OPENAI_API_KEY'),
+            provider= "openai/gpt-4o", api_token = os.getenv('OPENAI_API_KEY'), 
-        instruction="Extract all model names and their fees for input and output tokens."
+            schema=OpenAIModelFee.schema(),
-    ),
+            extraction_type="schema",
-)
+            instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens. 
+            Do not miss any models 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,
+    )
 
 print(result.extracted_content)
 ```
@@ -98,7 +145,7 @@ print(result.extracted_content)
 
 ## Documentation 📚
 
-For detailed documentation, including installation instructions, advanced features, and API reference, visit our [Documentation Website](https://craw4ai.com/mkdocs/).
+For detailed documentation, including installation instructions, advanced features, and API reference, visit our [Documentation Website](https://crawl4ai.com/mkdocs/).
 
 ## Contributing 🤝
 
@@ -117,3 +164,7 @@ For questions, suggestions, or feedback, feel free to reach out:
 - Website: [crawl4ai.com](https://crawl4ai.com)
 
 Happy Crawling! 🕸️🚀
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=unclecode/crawl4ai&type=Date)](https://star-history.com/#unclecode/crawl4ai&Date)

crawl4ai/crawler_strategy.py

@@ -5,8 +5,12 @@ from selenium.webdriver.common.by import By
 from selenium.webdriver.support.ui import WebDriverWait
 from selenium.webdriver.support import expected_conditions as EC
 from selenium.webdriver.chrome.options import Options
-from selenium.common.exceptions import InvalidArgumentException
+from selenium.common.exceptions import InvalidArgumentException, WebDriverException
-import logging
+from selenium.webdriver.chrome.service import Service as ChromeService
+from webdriver_manager.chrome import ChromeDriverManager
+
+from .config import *
+import logging, time
 import base64
 from PIL import Image, ImageDraw, ImageFont
 from io import BytesIO
@@ -80,14 +84,20 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
         if kwargs.get("user_agent"):
             self.options.add_argument("--user-agent=" + kwargs.get("user_agent"))
         else:
-            # Set user agent
             user_agent = kwargs.get("user_agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36")
             self.options.add_argument(f"--user-agent={user_agent}")
+            self.options.add_argument("user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36")
                   
-        self.options.add_argument("--no-sandbox")
         self.options.headless = kwargs.get("headless", True)
         if self.options.headless:
             self.options.add_argument("--headless")
+        
+        self.options.add_argument("--disable-gpu")  
+        self.options.add_argument("--window-size=1920,1080")
+        self.options.add_argument("--no-sandbox")
+        self.options.add_argument("--disable-dev-shm-usage")
+        self.options.add_argument("--disable-blink-features=AutomationControlled")     
+        
         # self.options.add_argument("--disable-dev-shm-usage")
         self.options.add_argument("--disable-gpu")
         # self.options.add_argument("--disable-extensions")
@@ -118,10 +128,15 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
         }
 
         # chromedriver_autoinstaller.install()
-        import chromedriver_autoinstaller
+        # import chromedriver_autoinstaller
-        crawl4ai_folder = os.path.join(Path.home(), ".crawl4ai")
+        # crawl4ai_folder = os.path.join(Path.home(), ".crawl4ai")
-        chromedriver_path = chromedriver_autoinstaller.utils.download_chromedriver(crawl4ai_folder, False)
+        # driver = webdriver.Chrome(service=ChromeService(ChromeDriverManager().install()), options=self.options)
+        # chromedriver_path = chromedriver_autoinstaller.install()
+        # chromedriver_path = chromedriver_autoinstaller.utils.download_chromedriver()
         # self.service = Service(chromedriver_autoinstaller.install())
+        
+        
+        chromedriver_path = ChromeDriverManager().install()
         self.service = Service(chromedriver_path)
         self.service.log_path = "NUL"
         self.driver = webdriver.Chrome(service=self.service, options=self.options)
@@ -163,8 +178,20 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
         # Set extra HTTP headers
         self.driver.execute_cdp_cmd('Network.setExtraHTTPHeaders', {'headers': headers})
 
+    def _ensure_page_load(self,  max_checks=6, check_interval=0.01):
+        initial_length = len(self.driver.page_source)
         
-    def crawl(self, url: str) -> str:
+        for ix in range(max_checks):
+            # print(f"Checking page load: {ix}")
+            time.sleep(check_interval)
+            current_length = len(self.driver.page_source)
+            
+            if current_length != initial_length:
+                break
+
+        return self.driver.page_source
+    
+    def crawl(self, url: str, **kwargs) -> str:
         # Create md5 hash of the URL
         import hashlib
         url_hash = hashlib.md5(url.encode()).hexdigest()
@@ -179,10 +206,30 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
             self.driver = self.execute_hook('before_get_url', self.driver)
             if self.verbose:
                 print(f"[LOG] 🕸️ Crawling {url} using LocalSeleniumCrawlerStrategy...")
-            self.driver.get(url)
+            self.driver.get(url) #<html><head></head><body></body></html>
-            WebDriverWait(self.driver, 10).until(
+            
-                EC.presence_of_all_elements_located((By.TAG_NAME, "html"))
+            WebDriverWait(self.driver, 20).until(
+                lambda d: d.execute_script('return document.readyState') == 'complete'
             )
+            WebDriverWait(self.driver, 10).until(
+                EC.presence_of_all_elements_located((By.TAG_NAME, "body"))
+            )
+            self.driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
+            html = self._ensure_page_load() # self.driver.page_source                
+            can_not_be_done_headless = False # Look at my creativity for naming variables
+            # TODO: Very ugly way for now but it works
+            if not kwargs.get('bypass_headless', False) and html == "<html><head></head><body></body></html>":
+                print("[LOG] 🙌 Page could not be loaded in headless mode. Trying non-headless mode...")
+                can_not_be_done_headless = True
+                options = Options()
+                options.headless = False
+                # set window size very small
+                options.add_argument("--window-size=5,5")
+                driver = webdriver.Chrome(service=self.service, options=options)
+                driver.get(url)
+                html = driver.page_source
+                driver.quit()
+            
             self.driver = self.execute_hook('after_get_url', self.driver)
             
             # Execute JS code if provided
@@ -199,7 +246,8 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
                         lambda driver: driver.execute_script("return document.readyState") == "complete"
                     )
             
-            html = self.driver.page_source
+            if not can_not_be_done_headless:
+                html = self.driver.page_source
             self.driver = self.execute_hook('before_return_html', self.driver, html)
             
             # Store in cache
@@ -212,9 +260,18 @@ class LocalSeleniumCrawlerStrategy(CrawlerStrategy):
             
             return html
         except InvalidArgumentException:
-            raise InvalidArgumentException(f"Invalid URL {url}")
+            if not hasattr(e, 'msg'):
+                e.msg = str(e)
+            raise InvalidArgumentException(f"Failed to crawl {url}: {e.msg}")
+        except WebDriverException as e:
+            # If e does nlt have msg attribute create it and set it to str(e)
+            if not hasattr(e, 'msg'):
+                e.msg = str(e)
+            raise WebDriverException(f"Failed to crawl {url}: {e.msg}")  
         except Exception as e:
-            raise Exception(f"Failed to crawl {url}: {str(e)}")
+            if not hasattr(e, 'msg'):
+                e.msg = str(e)
+            raise Exception(f"Failed to crawl {url}: {e.msg}")
 
     def take_screenshot(self) -> str:
         try:

crawl4ai/extraction_strategy.py

@@ -10,7 +10,7 @@ from functools import partial
 from .model_loader import *
 import math
 
-import numpy as np
+
 class ExtractionStrategy(ABC):
     """
     Abstract base class for all extraction strategies.
@@ -101,7 +101,7 @@ class LLMExtractionStrategy(ExtractionStrategy):
             prompt_with_variables = PROMPT_EXTRACT_BLOCKS_WITH_INSTRUCTION
             
         if self.extract_type == "schema":
-            variable_values["SCHEMA"] = json.dumps(self.schema)
+            variable_values["SCHEMA"] = json.dumps(self.schema, indent=2)
             prompt_with_variables = PROMPT_EXTRACT_SCHEMA_WITH_INSTRUCTION
 
         for variable in variable_values:
@@ -109,7 +109,7 @@ class LLMExtractionStrategy(ExtractionStrategy):
                 "{" + variable + "}", variable_values[variable]
             )
         
-        response = perform_completion_with_backoff(self.provider, prompt_with_variables, self.api_token)
+        response = perform_completion_with_backoff(self.provider, prompt_with_variables, self.api_token) # , json_response=self.extract_type == "schema")
         try:
             blocks = extract_xml_data(["blocks"], response.choices[0].message.content)['blocks']
             blocks = json.loads(blocks)
@@ -196,6 +196,10 @@ class LLMExtractionStrategy(ExtractionStrategy):
                 time.sleep(0.5)  # 500 ms delay between each processing
         else:
             # Parallel processing using ThreadPoolExecutor
+            # extract_func = partial(self.extract, url)
+            # for ix, section in enumerate(merged_sections):
+            #     extracted_content.append(extract_func(ix, section))            
+            
             with ThreadPoolExecutor(max_workers=4) as executor:
                 extract_func = partial(self.extract, url)
                 futures = [executor.submit(extract_func, ix, section) for ix, section in enumerate(merged_sections)]
@@ -219,6 +223,8 @@ class CosineStrategy(ExtractionStrategy):
         """
         super().__init__()
         
+        import numpy as np
+        
         self.semantic_filter = semantic_filter
         self.word_count_threshold = word_count_threshold
         self.max_dist = max_dist

crawl4ai/prompts.py

@@ -186,7 +186,7 @@ The user has made the following request for what information to extract from the
 Please carefully read the URL content and the user's request. If the user provided a desired JSON schema in the <schema_block> above, extract the requested information from the URL content according to that schema. If no schema was provided, infer an appropriate JSON schema based on the user's request that will best capture the key information they are looking for.
 
 Extraction instructions:
-Return the extracted information as a list of JSON objects, with each object in the list corresponding to a block of content from the URL, in the same order as it appears on the page. Wrap the entire JSON list in <blocks> tags.
+Return the extracted information as a list of JSON objects, with each object in the list corresponding to a block of content from the URL, in the same order as it appears on the page. Wrap the entire JSON list in <blocks>...</blocks> XML tags.
 
 Quality Reflection:
 Before outputting your final answer, double check that the JSON you are returning is complete, containing all the information requested by the user, and is valid JSON that could be parsed by json.loads() with no errors or omissions. The outputted JSON objects should fully match the schema, either provided or inferred.
@@ -194,5 +194,11 @@ Before outputting your final answer, double check that the JSON you are returnin
 Quality Score:
 After reflecting, score the quality and completeness of the JSON data you are about to return on a scale of 1 to 5. Write the score inside <score> tags.
 
+Avoid Common Mistakes:
+- Do NOT add any comments using "//" or "#" in the JSON output. It causes parsing errors.
+- Make sure the JSON is properly formatted with curly braces, square brackets, and commas in the right places.
+- Do not miss closing </blocks> tag at the end of the JSON output.
+- Do not generate the Python coee show me how to do the task, this is your task to extract the information and return it in JSON format.
+
 Result
-Output the final list of JSON objects, wrapped in <blocks> tags."""
+Output the final list of JSON objects, wrapped in <blocks>...</blocks> XML tags. Make sure to close the tag properly."""

crawl4ai/utils.py

@@ -10,6 +10,7 @@ from html2text import HTML2Text
 from .prompts import PROMPT_EXTRACT_BLOCKS
 from .config import *
 from pathlib import Path
+from typing import Dict, Any
 
 class InvalidCSSSelectorError(Exception):
     pass
@@ -176,16 +177,25 @@ def replace_inline_tags(soup, tags, only_text=False):
         'mark': lambda tag: f"=={tag.text}=="
     }
     
-    for tag_name in tags:
+    replacement_data = [(tag, tag_replacements.get(tag, lambda t: t.text)) for tag in tags]
+
+    for tag_name, replacement_func in replacement_data:
         for tag in soup.find_all(tag_name):
-            if not only_text:
+            replacement_text = tag.text if only_text else replacement_func(tag)
-                replacement_text = tag_replacements.get(tag_name, lambda t: t.text)(tag)
+            tag.replace_with(replacement_text)
-                tag.replace_with(replacement_text)
-            else:
-                tag.replace_with(tag.text)
 
     return soup    
 
+    # for tag_name in tags:
+    #     for tag in soup.find_all(tag_name):
+    #         if not only_text:
+    #             replacement_text = tag_replacements.get(tag_name, lambda t: t.text)(tag)
+    #             tag.replace_with(replacement_text)
+    #         else:
+    #             tag.replace_with(tag.text)
+
+    # return soup
+
 def get_content_of_website(url, html, word_count_threshold = MIN_WORD_THRESHOLD, css_selector = None, **kwargs):
     try:
         if not html:
@@ -388,29 +398,160 @@ def get_content_of_website(url, html, word_count_threshold = MIN_WORD_THRESHOLD,
         markdown = h.handle(cleaned_html)
         markdown = markdown.replace('    ```', '```')
             
+        try:
+            meta = extract_metadata(html, soup)
+        except Exception as e:
+            print('Error extracting metadata:', str(e))
+            meta = {}
+                
+        
         # Return the Markdown content
         return{
             'markdown': markdown,
             'cleaned_html': cleaned_html,
             'success': True,
             'media': media,
-            'links': links
+            'links': links,
+            'metadata': meta
         }
 
     except Exception as e:
         print('Error processing HTML content:', str(e))
         raise InvalidCSSSelectorError(f"Invalid CSS selector: {css_selector}") from e
 
+def get_content_of_website_optimized(url: str, html: str, word_count_threshold: int = MIN_WORD_THRESHOLD, css_selector: str = None, **kwargs) -> Dict[str, Any]:
+    if not html:
+        return None
+
+    soup = BeautifulSoup(html, 'html.parser')
+    body = soup.body
+
+    if css_selector:
+        selected_elements = body.select(css_selector)
+        if not selected_elements:
+            raise InvalidCSSSelectorError(f"Invalid CSS selector, No elements found for CSS selector: {css_selector}")
+        body = soup.new_tag('div')
+        for el in selected_elements:
+            body.append(el)
+
+    links = {'internal': [], 'external': []}
+    media = {'images': [], 'videos': [], 'audios': []}
+
+    def process_element(element: element.PageElement) -> bool:
+        try:
+            if isinstance(element, NavigableString):
+                if isinstance(element, Comment):
+                    element.extract()
+                return False
+
+            if element.name in ['script', 'style', 'link', 'meta', 'noscript']:
+                element.decompose()
+                return False
+
+            keep_element = False
+
+            if element.name == 'a' and element.get('href'):
+                href = element['href']
+                url_base = url.split('/')[2]
+                link_data = {'href': href, 'text': element.get_text()}
+                if href.startswith('http') and url_base not in href:
+                    links['external'].append(link_data)
+                else:
+                    links['internal'].append(link_data)
+                keep_element = True
+
+            elif element.name == 'img':
+                media['images'].append({
+                    'src': element.get('src'),
+                    'alt': element.get('alt'),
+                    'type': 'image'
+                })
+                return True  # Always keep image elements
+
+            elif element.name in ['video', 'audio']:
+                media[f"{element.name}s"].append({
+                    'src': element.get('src'),
+                    'alt': element.get('alt'),
+                    'type': element.name
+                })
+                return True  # Always keep video and audio elements
+
+            if element.name != 'pre':
+                if element.name in ['b', 'i', 'u', 'span', 'del', 'ins', 'sub', 'sup', 'strong', 'em', 'code', 'kbd', 'var', 's', 'q', 'abbr', 'cite', 'dfn', 'time', 'small', 'mark']:
+                    if kwargs.get('only_text', False):
+                        element.replace_with(element.get_text())
+                    else:
+                        element.unwrap()
+                elif element.name != 'img':
+                    element.attrs = {}
+
+            # Process children
+            for child in list(element.children):
+                if isinstance(child, NavigableString) and not isinstance(child, Comment):
+                    if len(child.strip()) > 0:
+                        keep_element = True
+                else:
+                    if process_element(child):
+                        keep_element = True
                 
 
-def extract_metadata(html):
+            # Check word count
+            if not keep_element:
+                word_count = len(element.get_text(strip=True).split())
+                keep_element = word_count >= word_count_threshold
+
+            if not keep_element:
+                element.decompose()
+
+            return keep_element
+        except Exception as e:
+            print('Error processing element:', str(e))
+            return False
+
+    process_element(body)
+
+    def flatten_nested_elements(node):
+        if isinstance(node, NavigableString):
+            return node
+        if len(node.contents) == 1 and isinstance(node.contents[0], element.Tag) and node.contents[0].name == node.name:
+            return flatten_nested_elements(node.contents[0])
+        node.contents = [flatten_nested_elements(child) for child in node.contents]
+        return node
+
+    body = flatten_nested_elements(body)
+
+    cleaned_html = str(body).replace('\n\n', '\n').replace('  ', ' ')
+    cleaned_html = sanitize_html(cleaned_html)
+
+    h = CustomHTML2Text()
+    h.ignore_links = True
+    markdown = h.handle(cleaned_html)
+    markdown = markdown.replace('    ```', '```')
+
+    try:
+        meta = extract_metadata(html, soup)
+    except Exception as e:
+        print('Error extracting metadata:', str(e))
+        meta = {}
+
+    return {
+        'markdown': markdown,
+        'cleaned_html': cleaned_html,
+        'success': True,
+        'media': media,
+        'links': links,
+        'metadata': meta
+    }
+
+def extract_metadata(html, soup = None):
     metadata = {}
     
     if not html:
         return metadata
     
     # Parse HTML content with BeautifulSoup
-    soup = BeautifulSoup(html, 'html.parser')
+    if not soup:
+        soup = BeautifulSoup(html, 'html.parser')
 
     # Title
     title_tag = soup.find('title')
@@ -460,12 +601,16 @@ def extract_xml_data(tags, string):
     return data
     
 # Function to perform the completion with exponential backoff
-def perform_completion_with_backoff(provider, prompt_with_variables, api_token):
+def perform_completion_with_backoff(provider, prompt_with_variables, api_token, json_response = False):
     from litellm import completion 
     from litellm.exceptions import RateLimitError
     max_attempts = 3
     base_delay = 2  # Base delay in seconds, you can adjust this based on your needs
     
+    extra_args = {}
+    if json_response:
+        extra_args["response_format"] = { "type": "json_object" }
+    
     for attempt in range(max_attempts):
         try:
             response =completion(
@@ -474,7 +619,8 @@ def perform_completion_with_backoff(provider, prompt_with_variables, api_token):
                     {"role": "user", "content": prompt_with_variables}
                 ],
                 temperature=0.01,
-                api_key=api_token
+                api_key=api_token,
+                **extra_args
             )
             return response  # Return the successful response
         except RateLimitError as e:
@@ -632,3 +778,10 @@ def wrap_text(draw, text, font, max_width):
             line += (words.pop(0) + ' ')
         lines.append(line)
     return '\n'.join(lines)
+
+
+def format_html(html_string):
+    soup = BeautifulSoup(html_string, 'html.parser')
+    return soup.prettify()
+
+

crawl4ai/web_crawler.py

@@ -11,6 +11,8 @@ from .crawler_strategy import *
 from typing import List
 from concurrent.futures import ThreadPoolExecutor
 from .config import *
+import warnings
+warnings.filterwarnings("ignore", message='Field "model_name" has conflict with protected namespace "model_".')
 
 
 class WebCrawler:
@@ -46,7 +48,8 @@ class WebCrawler:
             word_count_threshold=5,
             extraction_strategy= NoExtractionStrategy(),
             bypass_cache=False,
-            verbose = False
+            verbose = False,
+            # warmup=True
         )
         self.ready = True
         print("[LOG] 🌞 WebCrawler is ready to crawl")
@@ -128,36 +131,57 @@ class WebCrawler:
             verbose=True,
             **kwargs,
         ) -> CrawlResult:
-            extraction_strategy = extraction_strategy or NoExtractionStrategy()
+            try:
-            extraction_strategy.verbose = verbose
+                extraction_strategy = extraction_strategy or NoExtractionStrategy()
-            if not isinstance(extraction_strategy, ExtractionStrategy):
+                extraction_strategy.verbose = verbose
-                raise ValueError("Unsupported extraction strategy")
+                if not isinstance(extraction_strategy, ExtractionStrategy):
-            if not isinstance(chunking_strategy, ChunkingStrategy):
+                    raise ValueError("Unsupported extraction strategy")
-                raise ValueError("Unsupported chunking strategy")
+                if not isinstance(chunking_strategy, ChunkingStrategy):
+                    raise ValueError("Unsupported chunking strategy")
                 
-            if word_count_threshold < MIN_WORD_THRESHOLD:
+                # if word_count_threshold < MIN_WORD_THRESHOLD:
-                word_count_threshold = MIN_WORD_THRESHOLD
+                #     word_count_threshold = MIN_WORD_THRESHOLD
                     
-            # Check cache first
+                word_count_threshold = max(word_count_threshold, 0)
-            cached = None
-            extracted_content = None
-            if not bypass_cache and not self.always_by_pass_cache:
-                cached = get_cached_url(url)
 
-            if cached:
+                # Check cache first
-                html = cached[1]
+                cached = None
-                extracted_content = cached[2]
+                screenshot_data = None
-                if screenshot:
+                extracted_content = None
-                    screenshot = cached[9]
+                if not bypass_cache and not self.always_by_pass_cache:
+                    cached = get_cached_url(url)
                 
-            else:
+                if kwargs.get("warmup", True) and not self.ready:
-                if user_agent:
+                    return None
-                    self.crawler_strategy.update_user_agent(user_agent)
-                html = self.crawler_strategy.crawl(url)
-                if screenshot:
-                    screenshot = self.crawler_strategy.take_screenshot()
                 
-            return self.process_html(url, html, extracted_content, word_count_threshold, extraction_strategy, chunking_strategy, css_selector, screenshot, verbose, bool(cached), **kwargs)
+                if cached:
+                    html = cached[1]
+                    extracted_content = cached[4]
+                    if screenshot:
+                        screenshot_data = cached[9]
+                        if not screenshot_data:
+                            cached = None
+                
+                if not cached or not html:
+                    if user_agent:
+                        self.crawler_strategy.update_user_agent(user_agent)
+                    t1 = time.time()
+                    html = self.crawler_strategy.crawl(url, **kwargs)
+                    t2 = time.time()
+                    if verbose:
+                        print(f"[LOG] 🚀 Crawling done for {url}, success: {bool(html)}, time taken: {t2 - t1} seconds")
+                    if screenshot:
+                        screenshot_data = self.crawler_strategy.take_screenshot()
+
+                
+                crawl_result = self.process_html(url, html, extracted_content, word_count_threshold, extraction_strategy, chunking_strategy, css_selector, screenshot_data, verbose, bool(cached), **kwargs)
+                crawl_result.success = bool(html)
+                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)
 
     def process_html(
             self,
@@ -176,8 +200,14 @@ class WebCrawler:
             t = time.time()
             # Extract content from HTML
             try:
-                result = get_content_of_website(url, html, word_count_threshold, css_selector=css_selector, only_text=kwargs.get("only_text", False))
+                # t1 = time.time()
-                metadata = extract_metadata(html)
+                # result = get_content_of_website(url, html, word_count_threshold, css_selector=css_selector, only_text=kwargs.get("only_text", False))
+                # print(f"[LOG] 🚀 Crawling done for {url}, success: True, time taken: {time.time() - t1} seconds")
+                t1 = time.time()
+                result = get_content_of_website_optimized(url, html, word_count_threshold, css_selector=css_selector, only_text=kwargs.get("only_text", False))
+                if verbose:
+                    print(f"[LOG] 🚀 Content extracted for {url}, success: True, time taken: {time.time() - t1} seconds")
+                
                 if result is None:
                     raise ValueError(f"Failed to extract content from the website: {url}")
             except InvalidCSSSelectorError as e:
@@ -187,9 +217,7 @@ class WebCrawler:
             markdown = result.get("markdown", "")
             media = result.get("media", [])
             links = result.get("links", [])
-
+            metadata = result.get("metadata", {})
-            if verbose:
-                print(f"[LOG] 🚀 Crawling done for {url}, success: True, time taken: {time.time() - t} seconds")
                         
             if extracted_content is None:
                 if verbose:
@@ -197,7 +225,7 @@ class WebCrawler:
 
                 sections = chunking_strategy.chunk(markdown)
                 extracted_content = extraction_strategy.run(url, sections)
-                extracted_content = json.dumps(extracted_content)
+                extracted_content = json.dumps(extracted_content, indent=4, default=str)
 
                 if verbose:
                     print(f"[LOG] 🚀 Extraction done for {url}, time taken: {time.time() - t} seconds.")
@@ -221,7 +249,7 @@ class WebCrawler:
             return CrawlResult(
                 url=url,
                 html=html,
-                cleaned_html=cleaned_html,
+                cleaned_html=format_html(cleaned_html),
                 markdown=markdown,
                 media=media,
                 links=links,

docs/md/assets/styles.css

@@ -15,7 +15,6 @@
     --mono-font-stack: Menlo, Monaco, Lucida Console, Liberation Mono, DejaVu Sans Mono, Bitstream Vera Sans Mono,
         Courier New, monospace, serif;
 
-    
     --background-color: #151515; /* Dark background */
     --font-color: #eaeaea; /* Light font color for contrast */
     --invert-font-color: #151515; /* Dark color for inverted elements */
@@ -30,12 +29,16 @@
     --global-font-color: #eaeaea; /* Light font color for global elements */
 
     --background-color: #222225;
+
+    --background-color: #070708;
     --page-width: 70em;
     --font-color: #e8e9ed;
     --invert-font-color: #222225;
     --secondary-color: #a3abba;
+    --secondary-color: #d5cec0;
     --tertiary-color: #a3abba;
     --primary-color: #09b5a5; /* Updated to the brand color */
+    --primary-color: #50ffff; /* Updated to the brand color */
     --error-color: #ff3c74;
     --progress-bar-background: #3f3f44;
     --progress-bar-fill: #09b5a5; /* Updated to the brand color */
@@ -73,11 +76,78 @@ pre, code {
     border-bottom: 1px dashed var(--secondary-color);
 } */
 
-.terminal-mkdocs-main-content{
+.terminal-mkdocs-main-content {
     line-height: var(--global-line-height);
 }
 
-strong, .highlight {
+strong,
+.highlight {
     /* background: url(//s2.svgbox.net/pen-brushes.svg?ic=brush-1&color=50ffff); */
     background-color: #50ffff33;
 }
+
+.terminal-card > header {
+    color: var(--font-color);
+    text-align: center;
+    background-color: var(--progress-bar-background);
+    padding: 0.3em 0.5em;
+}
+.btn.btn-sm {
+    color: var(--font-color);
+    padding: 0.2em 0.5em;
+    font-size: 0.8em;
+}
+
+.loading-message {
+    display: none;
+    margin-top: 20px;
+}
+
+.response-section {
+    display: none;
+    padding-top: 20px;
+}
+
+.tabs {
+    display: flex;
+    flex-direction: column;
+}
+.tab-list {
+    display: flex;
+    padding: 0;
+    margin: 0;
+    list-style-type: none;
+    border-bottom: 1px solid var(--font-color);
+}
+.tab-item {
+    cursor: pointer;
+    padding: 10px;
+    border: 1px solid var(--font-color);
+    margin-right: -1px;
+    border-bottom: none;
+}
+.tab-item:hover,
+.tab-item:focus,
+.tab-item:active {
+    background-color: var(--progress-bar-background);
+}
+.tab-content {
+    display: none;
+    border: 1px solid var(--font-color);
+    border-top: none;
+}
+.tab-content:first-of-type {
+    display: block;
+}
+
+.tab-content header {
+    padding: 0.5em;
+    display: flex; 
+    justify-content: end; 
+    align-items: center;
+    background-color: var(--progress-bar-background);
+}
+.tab-content pre {
+    margin: 0;
+    max-height: 300px; overflow: auto; border:none;
+}

docs/md/changelog.md

@@ -1,5 +1,43 @@
 # Changelog
 
+## [v0.2.73] - 2024-07-03
+
+💡 In this release, we've bumped the version to v0.2.73 and refreshed our documentation to ensure you have the best experience with our project.
+
+* Supporting website need "with-head" mode to crawl the website with head.
+* Fixing the installation issues for setup.py and dockerfile.
+* Resolve multiple issues.
+
+## [v0.2.72] - 2024-06-30
+
+This release brings exciting updates and improvements to our project! 🎉
+
+* 📚 **Documentation Updates**: Our documentation has been revamped to reflect the latest changes and additions.
+* 🚀 **New Modes in setup.py**: We've added support for three new modes in setup.py: default, torch, and transformers. This enhances the project's flexibility and usability.
+* 🐳 **Docker File Updates**: The Docker file has been updated to ensure seamless compatibility with the new modes and improvements.
+* 🕷️ **Temporary Solution for Headless Crawling**: We've implemented a temporary solution to overcome issues with crawling websites in headless mode.
+
+These changes aim to improve the overall user experience, provide more flexibility, and enhance the project's performance. We're thrilled to share these updates with you and look forward to continuing to evolve and improve our project!
+
+## [0.2.71] - 2024-06-26
+
+**Improved Error Handling and Performance** 🚧
+
+* 🚫 Refactored `crawler_strategy.py` to handle exceptions and provide better error messages, making it more robust and reliable.
+* 💻 Optimized the `get_content_of_website_optimized` function in `utils.py` for improved performance, reducing potential bottlenecks.
+* 💻 Updated `utils.py` with the latest changes, ensuring consistency and accuracy.
+* 🚫 Migrated to `ChromeDriverManager` to resolve Chrome driver download issues, providing a smoother user experience.
+
+These changes focus on refining the existing codebase, resulting in a more stable, efficient, and user-friendly experience. With these improvements, you can expect fewer errors and better performance in the crawler strategy and utility functions.
+
+## [0.2.71] - 2024-06-25
+### Fixed
+- Speed up twice the extraction function.
+
+## [0.2.6] - 2024-06-22
+### Fixed
+- Fix issue #19: Update Dockerfile to ensure compatibility across multiple platforms.
+
 ## [0.2.5] - 2024-06-18
 ### Added
 - Added five important hooks to the crawler:

docs/md/demo.md

@@ -0,0 +1,198 @@
+# Interactive Demo for Crowler
+<div id="demo">
+    <form id="crawlForm" class="terminal-form">
+        <fieldset>
+            <legend>Enter URL and Options</legend>
+            <div class="form-group">
+                <label for="url">Enter URL:</label>
+                <input type="text" id="url" name="url" required>
+            </div>
+            <div class="form-group">
+                <label for="screenshot">Get Screenshot:</label>
+                <input type="checkbox" id="screenshot" name="screenshot">
+            </div>
+            <div class="form-group">
+                <button class="btn btn-default" type="submit">Submit</button>
+            </div>
+        </fieldset>
+    </form>
+
+    <div id="loading" class="loading-message">
+        <div class="terminal-alert terminal-alert-primary">Loading... Please wait.</div>
+    </div>
+
+    <section id="response" class="response-section">
+        <h2>Response</h2>
+        <div class="tabs">
+            <ul class="tab-list">
+                <li class="tab-item" onclick="showTab('markdown')">Markdown</li>
+                <li class="tab-item" onclick="showTab('cleanedHtml')">Cleaned HTML</li>
+                <li class="tab-item" onclick="showTab('media')">Media</li>
+                <li class="tab-item" onclick="showTab('extractedContent')">Extracted Content</li>
+                <li class="tab-item" onclick="showTab('screenshot')">Screenshot</li>
+                <li class="tab-item" onclick="showTab('pythonCode')">Python Code</li>
+            </ul>
+            <div class="tab-content" id="tab-markdown">
+                <header>
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="copyToClipboard('markdownContent')">Copy</button>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadContent('markdownContent', 'markdown.md')">Download</button>
+                    </div>
+                </header>
+                <pre><code id="markdownContent" class="language-markdown hljs"></code></pre>
+            </div>
+
+            <div class="tab-content" id="tab-cleanedHtml" style="display: none;">
+                <header >
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="copyToClipboard('cleanedHtmlContent')">Copy</button>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadContent('cleanedHtmlContent', 'cleaned.html')">Download</button>
+                    </div>
+                </header>
+                <pre><code id="cleanedHtmlContent" class="language-html hljs"></code></pre>
+            </div>
+
+            <div class="tab-content" id="tab-media" style="display: none;">
+                <header >
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="copyToClipboard('mediaContent')">Copy</button>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadContent('mediaContent', 'media.json')">Download</button>
+                    </div>
+                </header>
+                <pre><code id="mediaContent" class="language-json hljs"></code></pre>
+            </div>
+
+            <div class="tab-content" id="tab-extractedContent" style="display: none;">
+                <header >
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="copyToClipboard('extractedContentContent')">Copy</button>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadContent('extractedContentContent', 'extracted_content.json')">Download</button>
+                    </div>
+                </header>
+                <pre><code id="extractedContentContent" class="language-json hljs"></code></pre>
+            </div>
+
+            <div class="tab-content" id="tab-screenshot" style="display: none;">
+                <header >
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadImage('screenshotContent', 'screenshot.png')">Download</button>
+                    </div>
+                </header>
+                <pre><img id="screenshotContent" /></pre>
+            </div>
+
+            <div class="tab-content" id="tab-pythonCode" style="display: none;">
+                <header >
+                    <div>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="copyToClipboard('pythonCode')">Copy</button>
+                        <button class="btn btn-default btn-ghost btn-sm" onclick="downloadContent('pythonCode', 'example.py')">Download</button>
+                    </div>
+                </header>
+                <pre><code id="pythonCode" class="language-python hljs"></code></pre>
+            </div>
+        </div>
+    </section>
+
+    <script>
+        function showTab(tabId) {
+            const tabs = document.querySelectorAll('.tab-content');
+            tabs.forEach(tab => tab.style.display = 'none');
+            document.getElementById(`tab-${tabId}`).style.display = 'block';
+        }
+
+        function redo(codeBlock, codeText){
+            codeBlock.classList.remove('hljs');
+            codeBlock.removeAttribute('data-highlighted');
+
+            // Set new code and re-highlight
+            codeBlock.textContent = codeText;
+            hljs.highlightBlock(codeBlock);
+        }
+
+        function copyToClipboard(elementId) {
+            const content = document.getElementById(elementId).textContent;
+            navigator.clipboard.writeText(content).then(() => {
+                alert('Copied to clipboard');
+            });
+        }
+
+        function downloadContent(elementId, filename) {
+            const content = document.getElementById(elementId).textContent;
+            const blob = new Blob([content], { type: 'text/plain' });
+            const url = window.URL.createObjectURL(blob);
+            const a = document.createElement('a');
+            a.style.display = 'none';
+            a.href = url;
+            a.download = filename;
+            document.body.appendChild(a);
+            a.click();
+            window.URL.revokeObjectURL(url);
+            document.body.removeChild(a);
+        }
+
+        function downloadImage(elementId, filename) {
+            const content = document.getElementById(elementId).src;
+            const a = document.createElement('a');
+            a.style.display = 'none';
+            a.href = content;
+            a.download = filename;
+            document.body.appendChild(a);
+            a.click();
+            document.body.removeChild(a);
+        }
+
+        document.getElementById('crawlForm').addEventListener('submit', function(event) {
+            event.preventDefault();
+            document.getElementById('loading').style.display = 'block';
+            document.getElementById('response').style.display = 'none';
+
+            const url = document.getElementById('url').value;
+            const screenshot = document.getElementById('screenshot').checked;
+            const data = {
+                urls: [url],
+                bypass_cache: false,
+                word_count_threshold: 5,
+                screenshot: screenshot
+            };
+
+            fetch('/crawl', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json'
+                },
+                body: JSON.stringify(data)
+            })
+            .then(response => response.json())
+            .then(data => {
+                data = data.results[0]; // Only one URL is requested
+                document.getElementById('loading').style.display = 'none';
+                document.getElementById('response').style.display = 'block';
+                redo(document.getElementById('markdownContent'), data.markdown);
+                redo(document.getElementById('cleanedHtmlContent'), data.cleaned_html);
+                redo(document.getElementById('mediaContent'), JSON.stringify(data.media, null, 2));
+                redo(document.getElementById('extractedContentContent'), data.extracted_content);
+                if (screenshot) {
+                    document.getElementById('screenshotContent').src = `data:image/png;base64,${data.screenshot}`;
+                }
+                const pythonCode = `
+from crawl4ai.web_crawler import WebCrawler
+
+crawler = WebCrawler()
+crawler.warmup()
+
+result = crawler.run(
+    url='${url}',
+    screenshot=${screenshot}
+)
+print(result)
+                `;
+                redo(document.getElementById('pythonCode'), pythonCode);
+            })
+            .catch(error => {
+                document.getElementById('loading').style.display = 'none';
+                document.getElementById('response').style.display = 'block';
+                document.getElementById('markdownContent').textContent = 'Error: ' + error;
+            });
+        });
+    </script>
+</div>

docs/md/index.md

@@ -1,7 +1,12 @@
-# Crawl4AI Documentation
+# Crawl4AI v0.2.73
 
 Welcome to the official documentation for Crawl4AI! 🕷️🤖 Crawl4AI is an open-source Python library designed to simplify web crawling and extract useful information from web pages. This documentation will guide you through the features, usage, and customization of Crawl4AI.
 
+
+## Try the [Demo](demo.md)
+
+Just try it now and crawl different pages to see how it works. You can set the links, see the structures of the output, and also view the Python sample code on how to run it. The old demo is available at [/old_demo](/old) where you can see more details.
+
 ## Introduction
 
 Crawl4AI has one clear task: to make crawling and data extraction from web pages easy and efficient, especially for large language models (LLMs) and AI applications. Whether you are using it as a REST API or a Python library, Crawl4AI offers a robust and flexible solution.

docs/md/installation.md

@@ -1,39 +1,67 @@
 # Installation 💻
 
 There are three ways to use Crawl4AI:
+
 1. As a library (Recommended)
 2. As a local server (Docker) or using the REST API
-3. As a Google Colab notebook. [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wz8u30rvbq6Scodye9AGCw8Qg_Z8QGsk)
+3. As a Google Colab notebook.    
 
 ## Library Installation
 
-To install Crawl4AI as a library, follow these steps:
+Crawl4AI offers flexible installation options to suit various use cases. Choose the option that best fits your needs:
 
-1. Install the package from GitHub:
+- **Default Installation** (Basic functionality):
+```bash
+virtualenv venv
+source venv/bin/activate
+pip install "crawl4ai @ git+https://github.com/unclecode/crawl4ai.git"
 ```
+Use this for basic web crawling and scraping tasks.
+
+- **Installation with PyTorch** (For advanced text clustering):
+```bash
+virtualenv venv
+source venv/bin/activate
+pip install "crawl4ai[torch] @ git+https://github.com/unclecode/crawl4ai.git"
+```
+Choose this if you need the CosineSimilarity cluster strategy.
+
+- **Installation with Transformers** (For summarization and Hugging Face models):
+```bash
+virtualenv venv
+source venv/bin/activate
+pip install "crawl4ai[transformer] @ git+https://github.com/unclecode/crawl4ai.git"
+```
+Opt for this if you require text summarization or plan to use Hugging Face models.
+
+- **Full Installation** (All features):
+```bash
 virtualenv venv
 source venv/bin/activate
 pip install "crawl4ai[all] @ git+https://github.com/unclecode/crawl4ai.git"
 ```
+This installs all dependencies for full functionality.
 
-💡 Better to run the following CLI-command to load the required models. This is optional, but it will boost the performance and speed of the crawler. You need to do this only once.
+- **Development Installation** (For contributors):
-```
+```bash
-crawl4ai-download-models
-```
-
-2. Alternatively, you can clone the repository and install the package locally:
-```
 virtualenv venv
 source venv/bin/activate
 git clone https://github.com/unclecode/crawl4ai.git
 cd crawl4ai
-pip install -e .[all]
+pip install -e ".[all]"
+```
+Use this if you plan to modify the source code.
+
+💡 After installation, if you have used "torch", "transformer" or "all", it's recommended to run the following CLI command to load the required models. This is optional but will boost the performance and speed of the crawler. You need to do this only once, this is only for when you install using []
+```bash
+crawl4ai-download-models
 ```
 
 ## Using Docker for Local Server
 
-3. Use Docker to run the local server:
+To run Crawl4AI as a local server using Docker:
-```
+
+```bash
 # For Mac users
 # docker build --platform linux/amd64 -t crawl4ai .
 # For other users
@@ -43,4 +71,9 @@ docker run -d -p 8000:80 crawl4ai
 
 ## Using Google Colab
 
-You can also use Crawl4AI in a Google Colab notebook for easy setup and experimentation. Simply open the following Colab notebook and follow the instructions: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wz8u30rvbq6Scodye9AGCw8Qg_Z8QGsk)
+
+You can also use Crawl4AI in a Google Colab notebook for easy setup and experimentation. Simply open the following Colab notebook and follow the instructions: 
+
+    ⚠️ This collab is a bit outdated. I'm updating it with the newest versions, so please refer to the website for the latest documentation. This will be updated in a few days, and you'll have the latest version here. Thank you so much.
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wz8u30rvbq6Scodye9AGCw8Qg_Z8QGsk)

docs/md/interactive_content.html

@@ -0,0 +1,28 @@
+<h1>Try Our Library</h1>
+<form id="apiForm">
+    <label for="inputField">Enter some input:</label>
+    <input type="text" id="inputField" name="inputField" required>
+    <button type="submit">Submit</button>
+</form>
+<div id="result"></div>
+
+<script>
+    document.getElementById('apiForm').addEventListener('submit', function(event) {
+        event.preventDefault();
+        const input = document.getElementById('inputField').value;
+        fetch('https://your-api-endpoint.com/api', {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json'
+            },
+            body: JSON.stringify({ input: input })
+        })
+        .then(response => response.json())
+        .then(data => {
+            document.getElementById('result').textContent = JSON.stringify(data);
+        })
+        .catch(error => {
+            document.getElementById('result').textContent = 'Error: ' + error;
+        });
+    });
+</script>

main.py

@@ -10,6 +10,10 @@ from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 from fastapi.middleware.cors import CORSMiddleware  
 from fastapi.templating import Jinja2Templates
+from fastapi.exceptions import RequestValidationError
+from starlette.middleware.base import BaseHTTPMiddleware
+from starlette.responses import FileResponse
+from fastapi.responses import RedirectResponse
 
 from pydantic import BaseModel, HttpUrl
 from concurrent.futures import ThreadPoolExecutor, as_completed
@@ -39,12 +43,15 @@ app.add_middleware(
 # Mount the pages directory as a static directory
 app.mount("/pages", StaticFiles(directory=__location__ + "/pages"), name="pages")
 app.mount("/mkdocs", StaticFiles(directory="site", html=True), name="mkdocs")
+site_templates = Jinja2Templates(directory=__location__ + "/site")
 templates = Jinja2Templates(directory=__location__ + "/pages")
-# chromedriver_autoinstaller.install()  # Ensure chromedriver is installed
+
 @lru_cache()
 def get_crawler():
     # Initialize and return a WebCrawler instance
-    return WebCrawler(verbose = True)
+    crawler = WebCrawler(verbose = True)
+    crawler.warmup()
+    return crawler
 
 class CrawlRequest(BaseModel):
     urls: List[str]
@@ -61,8 +68,11 @@ class CrawlRequest(BaseModel):
     user_agent: Optional[str] = None
     verbose: Optional[bool] = True
 
+@app.get("/")
+def read_root():
+    return RedirectResponse(url="/mkdocs")
 
-@app.get("/", response_class=HTMLResponse)
+@app.get("/old", response_class=HTMLResponse)
 async def read_index(request: Request):
     partials_dir = os.path.join(__location__, "pages", "partial")
     partials = {}
@@ -79,7 +89,6 @@ async def get_total_url_count():
     count = get_total_count()
     return JSONResponse(content={"count": count})
 
-# Add endpoit to clear db
 @app.get("/clear-db")
 async def clear_database():
     # clear_db()
@@ -148,7 +157,6 @@ async def crawl_urls(crawl_request: CrawlRequest, request: Request):
             
 @app.get("/strategies/extraction", response_class=JSONResponse)
 async def get_extraction_strategies():
-    # Load docs/extraction_strategies.json" and return as JSON response
     with open(f"{__location__}/docs/extraction_strategies.json", "r") as file:
         return JSONResponse(content=file.read())
 
@@ -160,4 +168,4 @@ async def get_chunking_strategies():
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8080)
+    uvicorn.run(app, host="0.0.0.0", port=8888)

mkdocs.yml

@@ -2,9 +2,11 @@ site_name: Crawl4AI Documentation
 docs_dir: docs/md
 nav:
   - Home: index.md
-  - Introduction: introduction.md
+  - Demo: demo.md  # Add this line
-  - Installation: installation.md
+  - First Steps:
-  - Quick Start: quickstart.md
+      - Introduction: introduction.md
+      - Installation: installation.md
+      - Quick Start: quickstart.md
   - Examples:
       - Intro: examples/index.md
       - LLM Extraction: examples/llm_extraction.md
@@ -21,8 +23,9 @@ nav:
   - API Reference:
       - Core Classes and Functions: api/core_classes_and_functions.md
       - Detailed API Documentation: api/detailed_api_documentation.md
-  - Change Log: changelog.md
+  - Miscellaneous:
-  - Contact: contact.md
+      - Change Log: changelog.md
+      - Contact: contact.md
 
 theme:
   name: terminal

pages/index.html

@@ -25,7 +25,7 @@
         <header class="bg-zinc-950 text-lime-500 py-4 flex">
             
             <div class="mx-auto px-4">
-                <h1 class="text-2xl font-bold">🔥🕷️ Crawl4AI: Web Data for your Thoughts v0.2.5</h1>
+                <h1 class="text-2xl font-bold">🔥🕷️ Crawl4AI: Web Data for your Thoughts</h1>
             </div>
             <div class="mx-auto px-4 flex font-bold text-xl gap-2">
                 <span>📊 Total Website Processed</span>

requirements.txt

@@ -20,3 +20,4 @@ torch==2.3.1
 onnxruntime==1.18.0
 tokenizers==0.19.1
 pillow==10.3.0
+webdriver-manager==4.0.1

setup.py

@@ -1,6 +1,5 @@
 from setuptools import setup, find_packages
 import os
-import sys
 from pathlib import Path
 import subprocess
 from setuptools.command.install import install
@@ -14,42 +13,27 @@ os.makedirs(f"{crawl4ai_folder}/cache", exist_ok=True)
 with open("requirements.txt") as f:
     requirements = f.read().splitlines()
 
-# Read the requirements from requirements.txt
-with open("requirements.crawl.txt") as f:
-    requirements_crawl_only = f.read().splitlines()
-
 # Define the requirements for different environments
-requirements_without_torch = [req for req in requirements if not req.startswith("torch")]
+default_requirements = [req for req in requirements if not req.startswith(("torch", "transformers", "onnxruntime", "nltk", "spacy", "tokenizers", "scikit-learn", "numpy"))]
-requirements_without_transformers = [req for req in requirements if not req.startswith("transformers")]
+torch_requirements = [req for req in requirements if req.startswith(("torch", "nltk", "spacy", "scikit-learn", "numpy"))]
-requirements_without_nltk = [req for req in requirements if not req.startswith("nltk")]
+transformer_requirements = [req for req in requirements if req.startswith(("transformers", "tokenizers", "onnxruntime"))]
-requirements_without_torch_transformers_nlkt = [req for req in requirements if not req.startswith("torch") and not req.startswith("transformers") and not req.startswith("nltk")]
-requirements_crawl_only = [req for req in requirements if not req.startswith("torch") and not req.startswith("transformers") and not req.startswith("nltk")]
-
-class CustomInstallCommand(install):
-    """Customized setuptools install command to install spacy without dependencies."""
-    def run(self):
-        install.run(self)
-        subprocess.check_call([os.sys.executable, '-m', 'pip', 'install', 'spacy', '--no-deps'])
 
 setup(
     name="Crawl4AI",
-    version="0.2.5",
+    version="0.2.73",
     description="🔥🕷️ Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper",
-    long_description=open("README.md").read(),
+    long_description=open("README.md", encoding="utf-8").read(),
     long_description_content_type="text/markdown",
     url="https://github.com/unclecode/crawl4ai",
     author="Unclecode",
     author_email="unclecode@kidocode.com",
     license="MIT",
     packages=find_packages(),
-    install_requires=requirements_without_torch_transformers_nlkt,
+    install_requires=default_requirements,
     extras_require={
-        "all": requirements,  # Include all requirements
+        "torch": torch_requirements,
-        "colab": requirements_without_torch,  # Exclude torch for Colab
+        "transformer": transformer_requirements,
-        "crawl": requirements_crawl_only,  # Include only crawl requirements
+        "all": requirements,
-    },
-    cmdclass={
-        'install': CustomInstallCommand,
     },
     entry_points={
         'console_scripts': [