diff --git a/src/backend/base/langflow/components/data/url.py b/src/backend/base/langflow/components/data/url.py index 17fe2b8e1539..a147ea90aef9 100644 --- a/src/backend/base/langflow/components/data/url.py +++ b/src/backend/base/langflow/components/data/url.py @@ -18,12 +18,7 @@ DEFAULT_MAX_DEPTH = 1 DEFAULT_FORMAT = "Text" URL_REGEX = re.compile( - r"^(https?:\/\/)?" - r"(www\.)?" - r"([a-zA-Z0-9.-]+)" - r"(\.[a-zA-Z]{2,})?" - r"(:\d+)?" - r"(\/[^\s]*)?$", + r"^(https?:\/\/)?" r"(www\.)?" r"([a-zA-Z0-9.-]+)" r"(\.[a-zA-Z]{2,})?" r"(:\d+)?" r"(\/[^\s]*)?$", re.IGNORECASE, ) @@ -247,14 +242,14 @@ def fetch_url_contents(self) -> list[dict]: """ try: urls = list({self.ensure_url(url) for url in self.urls if url.strip()}) - logger.info(f"URLs: {urls}") + logger.debug(f"URLs: {urls}") if not urls: msg = "No valid URLs provided." raise ValueError(msg) all_docs = [] for url in urls: - logger.info(f"Loading documents from {url}") + logger.debug(f"Loading documents from {url}") try: loader = self._create_loader(url) @@ -264,7 +259,7 @@ def fetch_url_contents(self) -> list[dict]: logger.warning(f"No documents found for {url}") continue - logger.info(f"Found {len(docs)} documents from {url}") + logger.debug(f"Found {len(docs)} documents from {url}") all_docs.extend(docs) except requests.exceptions.RequestException as e: diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json index c2e57315cbe2..dbb6b6cb61af 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -1054,7 +1054,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import re\n\nimport requests\nfrom bs4 import BeautifulSoup\nfrom langchain_community.document_loaders import RecursiveUrlLoader\nfrom loguru import logger\n\nfrom langflow.custom.custom_component.component import Component\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.helpers.data import safe_convert\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SliderInput, TableInput\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.services.deps import get_settings_service\n\n# Constants\nDEFAULT_TIMEOUT = 30\nDEFAULT_MAX_DEPTH = 1\nDEFAULT_FORMAT = \"Text\"\nURL_REGEX = re.compile(\n r\"^(https?:\\/\\/)?\"\n r\"(www\\.)?\"\n r\"([a-zA-Z0-9.-]+)\"\n r\"(\\.[a-zA-Z]{2,})?\"\n r\"(:\\d+)?\"\n r\"(\\/[^\\s]*)?$\",\n re.IGNORECASE,\n)\n\n\nclass URLComponent(Component):\n \"\"\"A component that loads and parses content from web pages recursively.\n\n This component allows fetching content from one or more URLs, with options to:\n - Control crawl depth\n - Prevent crawling outside the root domain\n - Use async loading for better performance\n - Extract either raw HTML or clean text\n - Configure request headers and timeouts\n \"\"\"\n\n display_name = \"URL\"\n description = \"Fetch content from one or more web pages, following links recursively.\"\n documentation: str = \"https://docs.langflow.org/components-data#url\"\n icon = \"layout-template\"\n name = \"URLComponent\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs to crawl recursively, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n placeholder=\"Enter a URL...\",\n list_add_label=\"Add URL\",\n input_types=[],\n ),\n SliderInput(\n name=\"max_depth\",\n display_name=\"Depth\",\n info=(\n \"Controls how many 'clicks' away from the initial page the crawler will go:\\n\"\n \"- depth 1: only the initial page\\n\"\n \"- depth 2: initial page + all pages linked directly from it\\n\"\n \"- depth 3: initial page + direct links + links found on those direct link pages\\n\"\n \"Note: This is about link traversal, not URL path depth.\"\n ),\n value=DEFAULT_MAX_DEPTH,\n range_spec=RangeSpec(min=1, max=5, step=1),\n required=False,\n min_label=\" \",\n max_label=\" \",\n min_label_icon=\"None\",\n max_label_icon=\"None\",\n # slider_input=True\n ),\n BoolInput(\n name=\"prevent_outside\",\n display_name=\"Prevent Outside\",\n info=(\n \"If enabled, only crawls URLs within the same domain as the root URL. \"\n \"This helps prevent the crawler from going to external websites.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"use_async\",\n display_name=\"Use Async\",\n info=(\n \"If enabled, uses asynchronous loading which can be significantly faster \"\n \"but might use more system resources.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output Format\",\n info=\"Output Format. Use 'Text' to extract the text from the HTML or 'HTML' for the raw HTML content.\",\n options=[\"Text\", \"HTML\"],\n value=DEFAULT_FORMAT,\n advanced=True,\n ),\n IntInput(\n name=\"timeout\",\n display_name=\"Timeout\",\n info=\"Timeout for the request in seconds.\",\n value=DEFAULT_TIMEOUT,\n required=False,\n advanced=True,\n ),\n TableInput(\n name=\"headers\",\n display_name=\"Headers\",\n info=\"The headers to send with the request\",\n table_schema=[\n {\n \"name\": \"key\",\n \"display_name\": \"Header\",\n \"type\": \"str\",\n \"description\": \"Header name\",\n },\n {\n \"name\": \"value\",\n \"display_name\": \"Value\",\n \"type\": \"str\",\n \"description\": \"Header value\",\n },\n ],\n value=[{\"key\": \"User-Agent\", \"value\": get_settings_service().settings.user_agent}],\n advanced=True,\n input_types=[\"DataFrame\"],\n ),\n BoolInput(\n name=\"filter_text_html\",\n display_name=\"Filter Text/HTML\",\n info=\"If enabled, filters out text/css content type from the results.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"continue_on_failure\",\n display_name=\"Continue on Failure\",\n info=\"If enabled, continues crawling even if some requests fail.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"check_response_status\",\n display_name=\"Check Response Status\",\n info=\"If enabled, checks the response status of the request.\",\n value=False,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"autoset_encoding\",\n display_name=\"Autoset Encoding\",\n info=\"If enabled, automatically sets the encoding of the request.\",\n value=True,\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Extracted Pages\", name=\"page_results\", method=\"fetch_content\"),\n Output(display_name=\"Raw Content\", name=\"raw_results\", method=\"fetch_content_as_message\", tool_mode=False),\n ]\n\n @staticmethod\n def validate_url(url: str) -> bool:\n \"\"\"Validates if the given string matches URL pattern.\n\n Args:\n url: The URL string to validate\n\n Returns:\n bool: True if the URL is valid, False otherwise\n \"\"\"\n return bool(URL_REGEX.match(url))\n\n def ensure_url(self, url: str) -> str:\n \"\"\"Ensures the given string is a valid URL.\n\n Args:\n url: The URL string to validate and normalize\n\n Returns:\n str: The normalized URL\n\n Raises:\n ValueError: If the URL is invalid\n \"\"\"\n url = url.strip()\n if not url.startswith((\"http://\", \"https://\")):\n url = \"https://\" + url\n\n if not self.validate_url(url):\n msg = f\"Invalid URL: {url}\"\n raise ValueError(msg)\n\n return url\n\n def _create_loader(self, url: str) -> RecursiveUrlLoader:\n \"\"\"Creates a RecursiveUrlLoader instance with the configured settings.\n\n Args:\n url: The URL to load\n\n Returns:\n RecursiveUrlLoader: Configured loader instance\n \"\"\"\n headers_dict = {header[\"key\"]: header[\"value\"] for header in self.headers}\n extractor = (lambda x: x) if self.format == \"HTML\" else (lambda x: BeautifulSoup(x, \"lxml\").get_text())\n\n return RecursiveUrlLoader(\n url=url,\n max_depth=self.max_depth,\n prevent_outside=self.prevent_outside,\n use_async=self.use_async,\n extractor=extractor,\n timeout=self.timeout,\n headers=headers_dict,\n check_response_status=self.check_response_status,\n continue_on_failure=self.continue_on_failure,\n base_url=url, # Add base_url to ensure consistent domain crawling\n autoset_encoding=self.autoset_encoding, # Enable automatic encoding detection\n exclude_dirs=[], # Allow customization of excluded directories\n link_regex=None, # Allow customization of link filtering\n )\n\n def fetch_url_contents(self) -> list[dict]:\n \"\"\"Load documents from the configured URLs.\n\n Returns:\n List[Data]: List of Data objects containing the fetched content\n\n Raises:\n ValueError: If no valid URLs are provided or if there's an error loading documents\n \"\"\"\n try:\n urls = list({self.ensure_url(url) for url in self.urls if url.strip()})\n logger.info(f\"URLs: {urls}\")\n if not urls:\n msg = \"No valid URLs provided.\"\n raise ValueError(msg)\n\n all_docs = []\n for url in urls:\n logger.info(f\"Loading documents from {url}\")\n\n try:\n loader = self._create_loader(url)\n docs = loader.load()\n\n if not docs:\n logger.warning(f\"No documents found for {url}\")\n continue\n\n logger.info(f\"Found {len(docs)} documents from {url}\")\n all_docs.extend(docs)\n\n except requests.exceptions.RequestException as e:\n logger.exception(f\"Error loading documents from {url}: {e}\")\n continue\n\n if not all_docs:\n msg = \"No documents were successfully loaded from any URL\"\n raise ValueError(msg)\n\n # data = [Data(text=doc.page_content, **doc.metadata) for doc in all_docs]\n data = [\n {\n \"text\": safe_convert(doc.page_content, clean_data=True),\n \"url\": doc.metadata.get(\"source\", \"\"),\n \"title\": doc.metadata.get(\"title\", \"\"),\n \"description\": doc.metadata.get(\"description\", \"\"),\n \"content_type\": doc.metadata.get(\"content_type\", \"\"),\n \"language\": doc.metadata.get(\"language\", \"\"),\n }\n for doc in all_docs\n ]\n except Exception as e:\n error_msg = e.message if hasattr(e, \"message\") else e\n msg = f\"Error loading documents: {error_msg!s}\"\n logger.exception(msg)\n raise ValueError(msg) from e\n return data\n\n def fetch_content(self) -> DataFrame:\n \"\"\"Convert the documents to a DataFrame.\"\"\"\n return DataFrame(data=self.fetch_url_contents())\n\n def fetch_content_as_message(self) -> Message:\n \"\"\"Convert the documents to a Message.\"\"\"\n url_contents = self.fetch_url_contents()\n return Message(text=\"\\n\\n\".join([x[\"text\"] for x in url_contents]), data={\"data\": url_contents})\n" + "value": "import re\n\nimport requests\nfrom bs4 import BeautifulSoup\nfrom langchain_community.document_loaders import RecursiveUrlLoader\nfrom loguru import logger\n\nfrom langflow.custom.custom_component.component import Component\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.helpers.data import safe_convert\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SliderInput, TableInput\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.services.deps import get_settings_service\n\n# Constants\nDEFAULT_TIMEOUT = 30\nDEFAULT_MAX_DEPTH = 1\nDEFAULT_FORMAT = \"Text\"\nURL_REGEX = re.compile(\n r\"^(https?:\\/\\/)?\" r\"(www\\.)?\" r\"([a-zA-Z0-9.-]+)\" r\"(\\.[a-zA-Z]{2,})?\" r\"(:\\d+)?\" r\"(\\/[^\\s]*)?$\",\n re.IGNORECASE,\n)\n\n\nclass URLComponent(Component):\n \"\"\"A component that loads and parses content from web pages recursively.\n\n This component allows fetching content from one or more URLs, with options to:\n - Control crawl depth\n - Prevent crawling outside the root domain\n - Use async loading for better performance\n - Extract either raw HTML or clean text\n - Configure request headers and timeouts\n \"\"\"\n\n display_name = \"URL\"\n description = \"Fetch content from one or more web pages, following links recursively.\"\n documentation: str = \"https://docs.langflow.org/components-data#url\"\n icon = \"layout-template\"\n name = \"URLComponent\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs to crawl recursively, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n placeholder=\"Enter a URL...\",\n list_add_label=\"Add URL\",\n input_types=[],\n ),\n SliderInput(\n name=\"max_depth\",\n display_name=\"Depth\",\n info=(\n \"Controls how many 'clicks' away from the initial page the crawler will go:\\n\"\n \"- depth 1: only the initial page\\n\"\n \"- depth 2: initial page + all pages linked directly from it\\n\"\n \"- depth 3: initial page + direct links + links found on those direct link pages\\n\"\n \"Note: This is about link traversal, not URL path depth.\"\n ),\n value=DEFAULT_MAX_DEPTH,\n range_spec=RangeSpec(min=1, max=5, step=1),\n required=False,\n min_label=\" \",\n max_label=\" \",\n min_label_icon=\"None\",\n max_label_icon=\"None\",\n # slider_input=True\n ),\n BoolInput(\n name=\"prevent_outside\",\n display_name=\"Prevent Outside\",\n info=(\n \"If enabled, only crawls URLs within the same domain as the root URL. \"\n \"This helps prevent the crawler from going to external websites.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"use_async\",\n display_name=\"Use Async\",\n info=(\n \"If enabled, uses asynchronous loading which can be significantly faster \"\n \"but might use more system resources.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output Format\",\n info=\"Output Format. Use 'Text' to extract the text from the HTML or 'HTML' for the raw HTML content.\",\n options=[\"Text\", \"HTML\"],\n value=DEFAULT_FORMAT,\n advanced=True,\n ),\n IntInput(\n name=\"timeout\",\n display_name=\"Timeout\",\n info=\"Timeout for the request in seconds.\",\n value=DEFAULT_TIMEOUT,\n required=False,\n advanced=True,\n ),\n TableInput(\n name=\"headers\",\n display_name=\"Headers\",\n info=\"The headers to send with the request\",\n table_schema=[\n {\n \"name\": \"key\",\n \"display_name\": \"Header\",\n \"type\": \"str\",\n \"description\": \"Header name\",\n },\n {\n \"name\": \"value\",\n \"display_name\": \"Value\",\n \"type\": \"str\",\n \"description\": \"Header value\",\n },\n ],\n value=[{\"key\": \"User-Agent\", \"value\": get_settings_service().settings.user_agent}],\n advanced=True,\n input_types=[\"DataFrame\"],\n ),\n BoolInput(\n name=\"filter_text_html\",\n display_name=\"Filter Text/HTML\",\n info=\"If enabled, filters out text/css content type from the results.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"continue_on_failure\",\n display_name=\"Continue on Failure\",\n info=\"If enabled, continues crawling even if some requests fail.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"check_response_status\",\n display_name=\"Check Response Status\",\n info=\"If enabled, checks the response status of the request.\",\n value=False,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"autoset_encoding\",\n display_name=\"Autoset Encoding\",\n info=\"If enabled, automatically sets the encoding of the request.\",\n value=True,\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Extracted Pages\", name=\"page_results\", method=\"fetch_content\"),\n Output(display_name=\"Raw Content\", name=\"raw_results\", method=\"fetch_content_as_message\", tool_mode=False),\n ]\n\n @staticmethod\n def validate_url(url: str) -> bool:\n \"\"\"Validates if the given string matches URL pattern.\n\n Args:\n url: The URL string to validate\n\n Returns:\n bool: True if the URL is valid, False otherwise\n \"\"\"\n return bool(URL_REGEX.match(url))\n\n def ensure_url(self, url: str) -> str:\n \"\"\"Ensures the given string is a valid URL.\n\n Args:\n url: The URL string to validate and normalize\n\n Returns:\n str: The normalized URL\n\n Raises:\n ValueError: If the URL is invalid\n \"\"\"\n url = url.strip()\n if not url.startswith((\"http://\", \"https://\")):\n url = \"https://\" + url\n\n if not self.validate_url(url):\n msg = f\"Invalid URL: {url}\"\n raise ValueError(msg)\n\n return url\n\n def _create_loader(self, url: str) -> RecursiveUrlLoader:\n \"\"\"Creates a RecursiveUrlLoader instance with the configured settings.\n\n Args:\n url: The URL to load\n\n Returns:\n RecursiveUrlLoader: Configured loader instance\n \"\"\"\n headers_dict = {header[\"key\"]: header[\"value\"] for header in self.headers}\n extractor = (lambda x: x) if self.format == \"HTML\" else (lambda x: BeautifulSoup(x, \"lxml\").get_text())\n\n return RecursiveUrlLoader(\n url=url,\n max_depth=self.max_depth,\n prevent_outside=self.prevent_outside,\n use_async=self.use_async,\n extractor=extractor,\n timeout=self.timeout,\n headers=headers_dict,\n check_response_status=self.check_response_status,\n continue_on_failure=self.continue_on_failure,\n base_url=url, # Add base_url to ensure consistent domain crawling\n autoset_encoding=self.autoset_encoding, # Enable automatic encoding detection\n exclude_dirs=[], # Allow customization of excluded directories\n link_regex=None, # Allow customization of link filtering\n )\n\n def fetch_url_contents(self) -> list[dict]:\n \"\"\"Load documents from the configured URLs.\n\n Returns:\n List[Data]: List of Data objects containing the fetched content\n\n Raises:\n ValueError: If no valid URLs are provided or if there's an error loading documents\n \"\"\"\n try:\n urls = list({self.ensure_url(url) for url in self.urls if url.strip()})\n logger.debug(f\"URLs: {urls}\")\n if not urls:\n msg = \"No valid URLs provided.\"\n raise ValueError(msg)\n\n all_docs = []\n for url in urls:\n logger.debug(f\"Loading documents from {url}\")\n\n try:\n loader = self._create_loader(url)\n docs = loader.load()\n\n if not docs:\n logger.warning(f\"No documents found for {url}\")\n continue\n\n logger.debug(f\"Found {len(docs)} documents from {url}\")\n all_docs.extend(docs)\n\n except requests.exceptions.RequestException as e:\n logger.exception(f\"Error loading documents from {url}: {e}\")\n continue\n\n if not all_docs:\n msg = \"No documents were successfully loaded from any URL\"\n raise ValueError(msg)\n\n # data = [Data(text=doc.page_content, **doc.metadata) for doc in all_docs]\n data = [\n {\n \"text\": safe_convert(doc.page_content, clean_data=True),\n \"url\": doc.metadata.get(\"source\", \"\"),\n \"title\": doc.metadata.get(\"title\", \"\"),\n \"description\": doc.metadata.get(\"description\", \"\"),\n \"content_type\": doc.metadata.get(\"content_type\", \"\"),\n \"language\": doc.metadata.get(\"language\", \"\"),\n }\n for doc in all_docs\n ]\n except Exception as e:\n error_msg = e.message if hasattr(e, \"message\") else e\n msg = f\"Error loading documents: {error_msg!s}\"\n logger.exception(msg)\n raise ValueError(msg) from e\n return data\n\n def fetch_content(self) -> DataFrame:\n \"\"\"Convert the documents to a DataFrame.\"\"\"\n return DataFrame(data=self.fetch_url_contents())\n\n def fetch_content_as_message(self) -> Message:\n \"\"\"Convert the documents to a Message.\"\"\"\n url_contents = self.fetch_url_contents()\n return Message(text=\"\\n\\n\".join([x[\"text\"] for x in url_contents]), data={\"data\": url_contents})\n" }, "continue_on_failure": { "_input_type": "BoolInput", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json index 61ded67ecf77..ea523620cd9c 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json @@ -1593,7 +1593,7 @@ "show": true, "title_case": false, "type": "code", - "value": "import re\n\nimport requests\nfrom bs4 import BeautifulSoup\nfrom langchain_community.document_loaders import RecursiveUrlLoader\nfrom loguru import logger\n\nfrom langflow.custom.custom_component.component import Component\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.helpers.data import safe_convert\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SliderInput, TableInput\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.services.deps import get_settings_service\n\n# Constants\nDEFAULT_TIMEOUT = 30\nDEFAULT_MAX_DEPTH = 1\nDEFAULT_FORMAT = \"Text\"\nURL_REGEX = re.compile(\n r\"^(https?:\\/\\/)?\"\n r\"(www\\.)?\"\n r\"([a-zA-Z0-9.-]+)\"\n r\"(\\.[a-zA-Z]{2,})?\"\n r\"(:\\d+)?\"\n r\"(\\/[^\\s]*)?$\",\n re.IGNORECASE,\n)\n\n\nclass URLComponent(Component):\n \"\"\"A component that loads and parses content from web pages recursively.\n\n This component allows fetching content from one or more URLs, with options to:\n - Control crawl depth\n - Prevent crawling outside the root domain\n - Use async loading for better performance\n - Extract either raw HTML or clean text\n - Configure request headers and timeouts\n \"\"\"\n\n display_name = \"URL\"\n description = \"Fetch content from one or more web pages, following links recursively.\"\n documentation: str = \"https://docs.langflow.org/components-data#url\"\n icon = \"layout-template\"\n name = \"URLComponent\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs to crawl recursively, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n placeholder=\"Enter a URL...\",\n list_add_label=\"Add URL\",\n input_types=[],\n ),\n SliderInput(\n name=\"max_depth\",\n display_name=\"Depth\",\n info=(\n \"Controls how many 'clicks' away from the initial page the crawler will go:\\n\"\n \"- depth 1: only the initial page\\n\"\n \"- depth 2: initial page + all pages linked directly from it\\n\"\n \"- depth 3: initial page + direct links + links found on those direct link pages\\n\"\n \"Note: This is about link traversal, not URL path depth.\"\n ),\n value=DEFAULT_MAX_DEPTH,\n range_spec=RangeSpec(min=1, max=5, step=1),\n required=False,\n min_label=\" \",\n max_label=\" \",\n min_label_icon=\"None\",\n max_label_icon=\"None\",\n # slider_input=True\n ),\n BoolInput(\n name=\"prevent_outside\",\n display_name=\"Prevent Outside\",\n info=(\n \"If enabled, only crawls URLs within the same domain as the root URL. \"\n \"This helps prevent the crawler from going to external websites.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"use_async\",\n display_name=\"Use Async\",\n info=(\n \"If enabled, uses asynchronous loading which can be significantly faster \"\n \"but might use more system resources.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output Format\",\n info=\"Output Format. Use 'Text' to extract the text from the HTML or 'HTML' for the raw HTML content.\",\n options=[\"Text\", \"HTML\"],\n value=DEFAULT_FORMAT,\n advanced=True,\n ),\n IntInput(\n name=\"timeout\",\n display_name=\"Timeout\",\n info=\"Timeout for the request in seconds.\",\n value=DEFAULT_TIMEOUT,\n required=False,\n advanced=True,\n ),\n TableInput(\n name=\"headers\",\n display_name=\"Headers\",\n info=\"The headers to send with the request\",\n table_schema=[\n {\n \"name\": \"key\",\n \"display_name\": \"Header\",\n \"type\": \"str\",\n \"description\": \"Header name\",\n },\n {\n \"name\": \"value\",\n \"display_name\": \"Value\",\n \"type\": \"str\",\n \"description\": \"Header value\",\n },\n ],\n value=[{\"key\": \"User-Agent\", \"value\": get_settings_service().settings.user_agent}],\n advanced=True,\n input_types=[\"DataFrame\"],\n ),\n BoolInput(\n name=\"filter_text_html\",\n display_name=\"Filter Text/HTML\",\n info=\"If enabled, filters out text/css content type from the results.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"continue_on_failure\",\n display_name=\"Continue on Failure\",\n info=\"If enabled, continues crawling even if some requests fail.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"check_response_status\",\n display_name=\"Check Response Status\",\n info=\"If enabled, checks the response status of the request.\",\n value=False,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"autoset_encoding\",\n display_name=\"Autoset Encoding\",\n info=\"If enabled, automatically sets the encoding of the request.\",\n value=True,\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Extracted Pages\", name=\"page_results\", method=\"fetch_content\"),\n Output(display_name=\"Raw Content\", name=\"raw_results\", method=\"fetch_content_as_message\", tool_mode=False),\n ]\n\n @staticmethod\n def validate_url(url: str) -> bool:\n \"\"\"Validates if the given string matches URL pattern.\n\n Args:\n url: The URL string to validate\n\n Returns:\n bool: True if the URL is valid, False otherwise\n \"\"\"\n return bool(URL_REGEX.match(url))\n\n def ensure_url(self, url: str) -> str:\n \"\"\"Ensures the given string is a valid URL.\n\n Args:\n url: The URL string to validate and normalize\n\n Returns:\n str: The normalized URL\n\n Raises:\n ValueError: If the URL is invalid\n \"\"\"\n url = url.strip()\n if not url.startswith((\"http://\", \"https://\")):\n url = \"https://\" + url\n\n if not self.validate_url(url):\n msg = f\"Invalid URL: {url}\"\n raise ValueError(msg)\n\n return url\n\n def _create_loader(self, url: str) -> RecursiveUrlLoader:\n \"\"\"Creates a RecursiveUrlLoader instance with the configured settings.\n\n Args:\n url: The URL to load\n\n Returns:\n RecursiveUrlLoader: Configured loader instance\n \"\"\"\n headers_dict = {header[\"key\"]: header[\"value\"] for header in self.headers}\n extractor = (lambda x: x) if self.format == \"HTML\" else (lambda x: BeautifulSoup(x, \"lxml\").get_text())\n\n return RecursiveUrlLoader(\n url=url,\n max_depth=self.max_depth,\n prevent_outside=self.prevent_outside,\n use_async=self.use_async,\n extractor=extractor,\n timeout=self.timeout,\n headers=headers_dict,\n check_response_status=self.check_response_status,\n continue_on_failure=self.continue_on_failure,\n base_url=url, # Add base_url to ensure consistent domain crawling\n autoset_encoding=self.autoset_encoding, # Enable automatic encoding detection\n exclude_dirs=[], # Allow customization of excluded directories\n link_regex=None, # Allow customization of link filtering\n )\n\n def fetch_url_contents(self) -> list[dict]:\n \"\"\"Load documents from the configured URLs.\n\n Returns:\n List[Data]: List of Data objects containing the fetched content\n\n Raises:\n ValueError: If no valid URLs are provided or if there's an error loading documents\n \"\"\"\n try:\n urls = list({self.ensure_url(url) for url in self.urls if url.strip()})\n logger.info(f\"URLs: {urls}\")\n if not urls:\n msg = \"No valid URLs provided.\"\n raise ValueError(msg)\n\n all_docs = []\n for url in urls:\n logger.info(f\"Loading documents from {url}\")\n\n try:\n loader = self._create_loader(url)\n docs = loader.load()\n\n if not docs:\n logger.warning(f\"No documents found for {url}\")\n continue\n\n logger.info(f\"Found {len(docs)} documents from {url}\")\n all_docs.extend(docs)\n\n except requests.exceptions.RequestException as e:\n logger.exception(f\"Error loading documents from {url}: {e}\")\n continue\n\n if not all_docs:\n msg = \"No documents were successfully loaded from any URL\"\n raise ValueError(msg)\n\n # data = [Data(text=doc.page_content, **doc.metadata) for doc in all_docs]\n data = [\n {\n \"text\": safe_convert(doc.page_content, clean_data=True),\n \"url\": doc.metadata.get(\"source\", \"\"),\n \"title\": doc.metadata.get(\"title\", \"\"),\n \"description\": doc.metadata.get(\"description\", \"\"),\n \"content_type\": doc.metadata.get(\"content_type\", \"\"),\n \"language\": doc.metadata.get(\"language\", \"\"),\n }\n for doc in all_docs\n ]\n except Exception as e:\n error_msg = e.message if hasattr(e, \"message\") else e\n msg = f\"Error loading documents: {error_msg!s}\"\n logger.exception(msg)\n raise ValueError(msg) from e\n return data\n\n def fetch_content(self) -> DataFrame:\n \"\"\"Convert the documents to a DataFrame.\"\"\"\n return DataFrame(data=self.fetch_url_contents())\n\n def fetch_content_as_message(self) -> Message:\n \"\"\"Convert the documents to a Message.\"\"\"\n url_contents = self.fetch_url_contents()\n return Message(text=\"\\n\\n\".join([x[\"text\"] for x in url_contents]), data={\"data\": url_contents})\n" + "value": "import re\n\nimport requests\nfrom bs4 import BeautifulSoup\nfrom langchain_community.document_loaders import RecursiveUrlLoader\nfrom loguru import logger\n\nfrom langflow.custom.custom_component.component import Component\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.helpers.data import safe_convert\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SliderInput, TableInput\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.services.deps import get_settings_service\n\n# Constants\nDEFAULT_TIMEOUT = 30\nDEFAULT_MAX_DEPTH = 1\nDEFAULT_FORMAT = \"Text\"\nURL_REGEX = re.compile(\n r\"^(https?:\\/\\/)?\" r\"(www\\.)?\" r\"([a-zA-Z0-9.-]+)\" r\"(\\.[a-zA-Z]{2,})?\" r\"(:\\d+)?\" r\"(\\/[^\\s]*)?$\",\n re.IGNORECASE,\n)\n\n\nclass URLComponent(Component):\n \"\"\"A component that loads and parses content from web pages recursively.\n\n This component allows fetching content from one or more URLs, with options to:\n - Control crawl depth\n - Prevent crawling outside the root domain\n - Use async loading for better performance\n - Extract either raw HTML or clean text\n - Configure request headers and timeouts\n \"\"\"\n\n display_name = \"URL\"\n description = \"Fetch content from one or more web pages, following links recursively.\"\n documentation: str = \"https://docs.langflow.org/components-data#url\"\n icon = \"layout-template\"\n name = \"URLComponent\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs to crawl recursively, by clicking the '+' button.\",\n is_list=True,\n tool_mode=True,\n placeholder=\"Enter a URL...\",\n list_add_label=\"Add URL\",\n input_types=[],\n ),\n SliderInput(\n name=\"max_depth\",\n display_name=\"Depth\",\n info=(\n \"Controls how many 'clicks' away from the initial page the crawler will go:\\n\"\n \"- depth 1: only the initial page\\n\"\n \"- depth 2: initial page + all pages linked directly from it\\n\"\n \"- depth 3: initial page + direct links + links found on those direct link pages\\n\"\n \"Note: This is about link traversal, not URL path depth.\"\n ),\n value=DEFAULT_MAX_DEPTH,\n range_spec=RangeSpec(min=1, max=5, step=1),\n required=False,\n min_label=\" \",\n max_label=\" \",\n min_label_icon=\"None\",\n max_label_icon=\"None\",\n # slider_input=True\n ),\n BoolInput(\n name=\"prevent_outside\",\n display_name=\"Prevent Outside\",\n info=(\n \"If enabled, only crawls URLs within the same domain as the root URL. \"\n \"This helps prevent the crawler from going to external websites.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"use_async\",\n display_name=\"Use Async\",\n info=(\n \"If enabled, uses asynchronous loading which can be significantly faster \"\n \"but might use more system resources.\"\n ),\n value=True,\n required=False,\n advanced=True,\n ),\n DropdownInput(\n name=\"format\",\n display_name=\"Output Format\",\n info=\"Output Format. Use 'Text' to extract the text from the HTML or 'HTML' for the raw HTML content.\",\n options=[\"Text\", \"HTML\"],\n value=DEFAULT_FORMAT,\n advanced=True,\n ),\n IntInput(\n name=\"timeout\",\n display_name=\"Timeout\",\n info=\"Timeout for the request in seconds.\",\n value=DEFAULT_TIMEOUT,\n required=False,\n advanced=True,\n ),\n TableInput(\n name=\"headers\",\n display_name=\"Headers\",\n info=\"The headers to send with the request\",\n table_schema=[\n {\n \"name\": \"key\",\n \"display_name\": \"Header\",\n \"type\": \"str\",\n \"description\": \"Header name\",\n },\n {\n \"name\": \"value\",\n \"display_name\": \"Value\",\n \"type\": \"str\",\n \"description\": \"Header value\",\n },\n ],\n value=[{\"key\": \"User-Agent\", \"value\": get_settings_service().settings.user_agent}],\n advanced=True,\n input_types=[\"DataFrame\"],\n ),\n BoolInput(\n name=\"filter_text_html\",\n display_name=\"Filter Text/HTML\",\n info=\"If enabled, filters out text/css content type from the results.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"continue_on_failure\",\n display_name=\"Continue on Failure\",\n info=\"If enabled, continues crawling even if some requests fail.\",\n value=True,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"check_response_status\",\n display_name=\"Check Response Status\",\n info=\"If enabled, checks the response status of the request.\",\n value=False,\n required=False,\n advanced=True,\n ),\n BoolInput(\n name=\"autoset_encoding\",\n display_name=\"Autoset Encoding\",\n info=\"If enabled, automatically sets the encoding of the request.\",\n value=True,\n required=False,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Extracted Pages\", name=\"page_results\", method=\"fetch_content\"),\n Output(display_name=\"Raw Content\", name=\"raw_results\", method=\"fetch_content_as_message\", tool_mode=False),\n ]\n\n @staticmethod\n def validate_url(url: str) -> bool:\n \"\"\"Validates if the given string matches URL pattern.\n\n Args:\n url: The URL string to validate\n\n Returns:\n bool: True if the URL is valid, False otherwise\n \"\"\"\n return bool(URL_REGEX.match(url))\n\n def ensure_url(self, url: str) -> str:\n \"\"\"Ensures the given string is a valid URL.\n\n Args:\n url: The URL string to validate and normalize\n\n Returns:\n str: The normalized URL\n\n Raises:\n ValueError: If the URL is invalid\n \"\"\"\n url = url.strip()\n if not url.startswith((\"http://\", \"https://\")):\n url = \"https://\" + url\n\n if not self.validate_url(url):\n msg = f\"Invalid URL: {url}\"\n raise ValueError(msg)\n\n return url\n\n def _create_loader(self, url: str) -> RecursiveUrlLoader:\n \"\"\"Creates a RecursiveUrlLoader instance with the configured settings.\n\n Args:\n url: The URL to load\n\n Returns:\n RecursiveUrlLoader: Configured loader instance\n \"\"\"\n headers_dict = {header[\"key\"]: header[\"value\"] for header in self.headers}\n extractor = (lambda x: x) if self.format == \"HTML\" else (lambda x: BeautifulSoup(x, \"lxml\").get_text())\n\n return RecursiveUrlLoader(\n url=url,\n max_depth=self.max_depth,\n prevent_outside=self.prevent_outside,\n use_async=self.use_async,\n extractor=extractor,\n timeout=self.timeout,\n headers=headers_dict,\n check_response_status=self.check_response_status,\n continue_on_failure=self.continue_on_failure,\n base_url=url, # Add base_url to ensure consistent domain crawling\n autoset_encoding=self.autoset_encoding, # Enable automatic encoding detection\n exclude_dirs=[], # Allow customization of excluded directories\n link_regex=None, # Allow customization of link filtering\n )\n\n def fetch_url_contents(self) -> list[dict]:\n \"\"\"Load documents from the configured URLs.\n\n Returns:\n List[Data]: List of Data objects containing the fetched content\n\n Raises:\n ValueError: If no valid URLs are provided or if there's an error loading documents\n \"\"\"\n try:\n urls = list({self.ensure_url(url) for url in self.urls if url.strip()})\n logger.debug(f\"URLs: {urls}\")\n if not urls:\n msg = \"No valid URLs provided.\"\n raise ValueError(msg)\n\n all_docs = []\n for url in urls:\n logger.debug(f\"Loading documents from {url}\")\n\n try:\n loader = self._create_loader(url)\n docs = loader.load()\n\n if not docs:\n logger.warning(f\"No documents found for {url}\")\n continue\n\n logger.debug(f\"Found {len(docs)} documents from {url}\")\n all_docs.extend(docs)\n\n except requests.exceptions.RequestException as e:\n logger.exception(f\"Error loading documents from {url}: {e}\")\n continue\n\n if not all_docs:\n msg = \"No documents were successfully loaded from any URL\"\n raise ValueError(msg)\n\n # data = [Data(text=doc.page_content, **doc.metadata) for doc in all_docs]\n data = [\n {\n \"text\": safe_convert(doc.page_content, clean_data=True),\n \"url\": doc.metadata.get(\"source\", \"\"),\n \"title\": doc.metadata.get(\"title\", \"\"),\n \"description\": doc.metadata.get(\"description\", \"\"),\n \"content_type\": doc.metadata.get(\"content_type\", \"\"),\n \"language\": doc.metadata.get(\"language\", \"\"),\n }\n for doc in all_docs\n ]\n except Exception as e:\n error_msg = e.message if hasattr(e, \"message\") else e\n msg = f\"Error loading documents: {error_msg!s}\"\n logger.exception(msg)\n raise ValueError(msg) from e\n return data\n\n def fetch_content(self) -> DataFrame:\n \"\"\"Convert the documents to a DataFrame.\"\"\"\n return DataFrame(data=self.fetch_url_contents())\n\n def fetch_content_as_message(self) -> Message:\n \"\"\"Convert the documents to a Message.\"\"\"\n url_contents = self.fetch_url_contents()\n return Message(text=\"\\n\\n\".join([x[\"text\"] for x in url_contents]), data={\"data\": url_contents})\n" }, "continue_on_failure": { "_input_type": "BoolInput", diff --git a/src/backend/base/langflow/utils/async_helpers.py b/src/backend/base/langflow/utils/async_helpers.py index 60628286c0ac..5a6513a74377 100644 --- a/src/backend/base/langflow/utils/async_helpers.py +++ b/src/backend/base/langflow/utils/async_helpers.py @@ -21,8 +21,22 @@ async def timeout_context(timeout_seconds): def run_until_complete(coro): try: - loop = asyncio.get_running_loop() + asyncio.get_running_loop() except RuntimeError: # If there's no event loop, create a new one and run the coroutine return asyncio.run(coro) - return loop.run_until_complete(coro) + # If there's already a running event loop, we can't call run_until_complete on it + # Instead, we need to run the coroutine in a new thread with a new event loop + import concurrent.futures + + def run_in_new_loop(): + new_loop = asyncio.new_event_loop() + asyncio.set_event_loop(new_loop) + try: + return new_loop.run_until_complete(coro) + finally: + new_loop.close() + + with concurrent.futures.ThreadPoolExecutor() as executor: + future = executor.submit(run_in_new_loop) + return future.result() diff --git a/src/backend/tests/unit/test_async_helpers.py b/src/backend/tests/unit/test_async_helpers.py new file mode 100644 index 000000000000..6b307eae0126 --- /dev/null +++ b/src/backend/tests/unit/test_async_helpers.py @@ -0,0 +1,195 @@ +"""Tests for async_helpers.py functions.""" + +import asyncio +import threading +import time +from unittest.mock import patch + +import pytest +from langflow.utils.async_helpers import run_until_complete + + +class TestRunUntilComplete: + """Test the run_until_complete function.""" + + def test_run_until_complete_no_running_loop(self): + """Test run_until_complete when no event loop is running.""" + + async def simple_coro(): + return "test_result" + + # Should work when no loop is running + result = run_until_complete(simple_coro()) + assert result == "test_result" + + def test_run_until_complete_simple_coro_with_running_loop(self): + """Test run_until_complete with a simple coroutine when loop is running.""" + + async def simple_coro(): + return "from_thread" + + async def main_test(): + # This should work with our fix - runs in separate thread + return run_until_complete(simple_coro()) + + result = asyncio.run(main_test()) + assert result == "from_thread" + + def test_run_until_complete_complex_coro_with_running_loop(self): + """Test run_until_complete with a complex async coroutine when loop is running.""" + + async def complex_coro(): + await asyncio.sleep(0.01) # This requires event loop cooperation + return "complex_result" + + async def main_test(): + # This would deadlock with old implementation that calls loop.run_until_complete + # using the running loop + return run_until_complete(complex_coro()) + + result = asyncio.run(main_test()) + assert result == "complex_result" + + def test_run_until_complete_with_exception_in_new_thread(self): + """Test that exceptions in the new thread are properly propagated.""" + + async def failing_coro(): + msg = "Test exception" + raise ValueError(msg) + + async def main_test(): + with pytest.raises(ValueError, match="Test exception"): + run_until_complete(failing_coro()) + + asyncio.run(main_test()) + + def test_run_until_complete_preserves_return_value(self): + """Test that complex return values are preserved across threads.""" + + async def return_complex(): + return {"key": "value", "list": [1, 2, 3], "nested": {"inner": "data"}} + + async def main_test(): + return run_until_complete(return_complex()) + + result = asyncio.run(main_test()) + expected = {"key": "value", "list": [1, 2, 3], "nested": {"inner": "data"}} + assert result == expected + + def test_run_until_complete_thread_isolation(self): + """Test that thread-local data is properly isolated.""" + # Set up thread-local storage + local_data = threading.local() + local_data.value = "main_thread" + + async def check_thread_isolation(): + # This should NOT have access to main thread's local data + try: + return getattr(local_data, "value", "no_value") + except AttributeError: + return "no_value" + + async def main_test(): + # Confirm main thread has the value + assert getattr(local_data, "value", None) == "main_thread" + + # Check that new thread doesn't have access + return run_until_complete(check_thread_isolation()) + + result = asyncio.run(main_test()) + assert result == "no_value" # Thread isolation working + + def test_run_until_complete_concurrent_execution(self): + """Test that multiple concurrent calls work correctly.""" + + async def delayed_coro(delay, value): + await asyncio.sleep(delay) + return f"result_{value}" + + async def main_test(): + # Run multiple coroutines concurrently + import concurrent.futures + + with concurrent.futures.ThreadPoolExecutor() as executor: + futures = [executor.submit(run_until_complete, delayed_coro(0.01, i)) for i in range(3)] + + return [f.result() for f in futures] + + results = asyncio.run(main_test()) + expected = ["result_0", "result_1", "result_2"] + assert results == expected + + def test_run_until_complete_performance_impact(self): + """Test that the performance impact is reasonable.""" + + async def quick_coro(): + return "quick" + + async def main_test(): + # Time multiple executions + start_time = time.time() + + for _ in range(10): + result = run_until_complete(quick_coro()) + assert result == "quick" + + end_time = time.time() + return end_time - start_time + + duration = asyncio.run(main_test()) + + # Should complete 10 executions in reasonable time (less than 1 second) + assert duration < 1.0, f"Performance test took too long: {duration}s" + + def test_run_until_complete_nested_async_operations(self): + """Test with nested async operations that require event loop.""" + + async def inner_async(): + await asyncio.sleep(0.001) + return "inner" + + async def outer_async(): + # This creates tasks that need event loop scheduling + tasks = [asyncio.create_task(inner_async()) for _ in range(3)] + return await asyncio.gather(*tasks) + + async def main_test(): + # This would definitely deadlock with old implementation + return run_until_complete(outer_async()) + + result = asyncio.run(main_test()) + assert result == ["inner", "inner", "inner"] + + def test_run_until_complete_with_timeout(self): + """Test that timeouts work correctly in the new thread.""" + + async def slow_coro(): + await asyncio.sleep(10) # Very long delay + return "should_not_reach" + + async def timeout_coro(): + try: + await asyncio.wait_for(slow_coro(), timeout=0.01) + except asyncio.TimeoutError: + return "timeout_occurred" + return "no_timeout" + + async def main_test(): + return run_until_complete(timeout_coro()) + + result = asyncio.run(main_test()) + assert result == "timeout_occurred" + + def test_original_behavior_preserved_no_loop(self): + """Test that original behavior is preserved when no loop is running.""" + + async def test_coro(): + return "original_behavior" + + # Mock asyncio.run to verify it's called when no loop exists + with patch("asyncio.run", return_value="mocked_result") as mock_run: + result = run_until_complete(test_coro()) + + # Should have called asyncio.run (original behavior) + mock_run.assert_called_once() + assert result == "mocked_result" diff --git a/uv.lock b/uv.lock index 0433b71c7505..8a677c0d106e 100644 --- a/uv.lock +++ b/uv.lock @@ -2,22 +2,24 @@ version = 1 revision = 2 requires-python = ">=3.10, <3.14" resolution-markers = [ - "python_full_version >= '3.13' and sys_platform == 'darwin'", - "python_version < '0'", - "python_full_version >= '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'", - "(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')", - "python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform == 'darwin'", - "python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'", - "(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 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sys_platform == 'linux'", + "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'", + "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')", + "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')", "python_full_version == '3.11.*' and sys_platform == 'darwin'", "python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'", "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and sys_platform == 'linux') or 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