Scrapegraph-ai/scrapegraphai/nodes/fetch_node_level_k.py
2024-10-02 11:01:23 +02:00

189 lines
7.4 KiB
Python

"""
FetchNodeLevelK Module
"""
from typing import List, Optional
from .base_node import BaseNode
from ..docloaders import ChromiumLoader
from ..utils.cleanup_html import cleanup_html
from ..utils.convert_to_md import convert_to_md
from langchain_core.documents import Document
from bs4 import BeautifulSoup
from urllib.parse import quote, urljoin
class FetchNodeLevelK(BaseNode):
"""
A node responsible for fetching the HTML content of a specified URL and all its sub-links
recursively up to a certain level of hyperlink the graph. This content is then used to update
the graph's state. It uses ChromiumLoader to fetch the content from a web page asynchronously
(with proxy protection).
Attributes:
llm_model: An instance of a language model client, configured for generating answers.
verbose (bool): A flag indicating whether to show print statements during execution.
Args:
input (str): Boolean expression defining the input keys needed from the state.
output (List[str]): List of output keys to be updated in the state.
node_config (dict): Additional configuration for the node.
node_name (str): The unique identifier name for the node, defaulting to "Parse".
"""
def __init__(
self,
input: str,
output: List[str],
node_config: Optional[dict] = None,
node_name: str = "FetchLevelK",
):
super().__init__(node_name, "node", input, output, 2, node_config)
self.embedder_model = node_config.get("embedder_model", None)
self.verbose = (
False if node_config is None else node_config.get("verbose", False)
)
self.cache_path = node_config.get("cache_path", False)
self.headless = (
True if node_config is None else node_config.get("headless", True)
)
self.loader_kwargs = (
{} if node_config is None else node_config.get("loader_kwargs", {})
)
self.browser_base = (
None if node_config is None else node_config.get("browser_base", None)
)
self.depth = (
1 if node_config is None else node_config.get("depth", 1)
)
self.only_inside_links = (
False if node_config is None else node_config.get("only_inside_links", False)
)
self.min_input_len = 1
def execute(self, state: dict) -> dict:
"""
Executes the node's logic to fetch the HTML content of a specified URL and all its sub-links
and update the graph's state with the content.
Args:
state (dict): The current state of the graph. The input keys will be used
to fetch the correct data types from the state.
Returns:
dict: The updated state with a new output key containing the fetched HTML content.
Raises:
KeyError: If the input key is not found in the state, indicating that the
necessary information to perform the operation is missing.
"""
self.logger.info(f"--- Executing {self.node_name} Node ---")
# Interpret input keys based on the provided input expression
input_keys = self.get_input_keys(state)
# Fetching data from the state based on the input keys
input_data = [state[key] for key in input_keys]
source = input_data[0]
documents = [{"source": source}]
self.logger.info(f"--- (Fetching HTML from: {source}) ---")
loader_kwargs = {}
if self.node_config is not None:
loader_kwargs = self.node_config.get("loader_kwargs", {})
for _ in range(self.depth):
documents = self.obtain_content(documents, loader_kwargs)
filtered_documents = [doc for doc in documents if 'document' in doc]
state.update({self.output[0]: filtered_documents})
return state
def fetch_content(self, source: str, loader_kwargs) -> Optional[str]:
if self.browser_base is not None:
try:
from ..docloaders.browser_base import browser_base_fetch
except ImportError:
raise ImportError("""The browserbase module is not installed.
Please install it using `pip install browserbase`.""")
data = browser_base_fetch(self.browser_base.get("api_key"),
self.browser_base.get("project_id"), [source])
document = [Document(page_content=content,
metadata={"source": source}) for content in data]
else:
loader = ChromiumLoader([source], headless=self.headless, **loader_kwargs)
document = loader.load()
return document
def extract_links(self, html_content: str) -> list:
soup = BeautifulSoup(html_content, 'html.parser')
links = [link['href'] for link in soup.find_all('a', href=True)]
self.logger.info(f"Extracted {len(links)} links.")
return links
def get_full_links(self, base_url: str, links: list) -> list:
full_links = []
for link in links:
if self.only_inside_links and link.startswith("http"):
continue
full_link = link if link.startswith("http") else urljoin(base_url, link)
full_links.append(full_link)
return full_links
def obtain_content(self, documents: List, loader_kwargs) -> List:
new_documents = []
for doc in documents:
source = doc['source']
if 'document' not in doc:
document = self.fetch_content(source, loader_kwargs)
if not document or not document[0].page_content.strip():
self.logger.warning(f"Failed to fetch content for {source}")
documents.remove(doc)
continue
doc['document'] = document[0].page_content
links = self.extract_links(doc['document'])
full_links = self.get_full_links(source, links)
# Check if the links are already present in other documents
for link in full_links:
# Check if any document is from the same link
if not any(d.get('source', '') == link for d in documents) and not any(d.get('source', '') == link for d in new_documents):
# Add the document
new_documents.append({"source": link})
documents.extend(new_documents)
return documents
def process_links(self, base_url: str, links: list, loader_kwargs, depth: int, current_depth: int = 1) -> dict:
content_dict = {}
for idx, link in enumerate(links, start=1):
full_link = link if link.startswith("http") else urljoin(base_url, link)
self.logger.info(f"Processing link {idx}: {full_link}")
link_content = self.fetch_content(full_link, loader_kwargs)
if current_depth < depth:
new_links = self.extract_links(link_content)
content_dict.update(self.process_links(full_link, new_links, depth, current_depth + 1))
else:
self.logger.warning(f"Failed to fetch content for {full_link}")
return content_dict