mirror of
https://github.com/open-webui/open-webui
synced 2025-04-23 15:55:23 +00:00
94 lines
4.0 KiB
Python
94 lines
4.0 KiB
Python
import requests
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import logging
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from typing import Iterator, List, Literal, Union
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from langchain_core.document_loaders import BaseLoader
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from langchain_core.documents import Document
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from open_webui.env import SRC_LOG_LEVELS
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log = logging.getLogger(__name__)
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log.setLevel(SRC_LOG_LEVELS["RAG"])
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class TavilyLoader(BaseLoader):
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"""Extract web page content from URLs using Tavily Extract API.
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This is a LangChain document loader that uses Tavily's Extract API to
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retrieve content from web pages and return it as Document objects.
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Args:
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urls: URL or list of URLs to extract content from.
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api_key: The Tavily API key.
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extract_depth: Depth of extraction, either "basic" or "advanced".
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continue_on_failure: Whether to continue if extraction of a URL fails.
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"""
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def __init__(
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self,
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urls: Union[str, List[str]],
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api_key: str,
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extract_depth: Literal["basic", "advanced"] = "basic",
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continue_on_failure: bool = True,
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) -> None:
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"""Initialize Tavily Extract client.
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Args:
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urls: URL or list of URLs to extract content from.
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api_key: The Tavily API key.
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include_images: Whether to include images in the extraction.
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extract_depth: Depth of extraction, either "basic" or "advanced".
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advanced extraction retrieves more data, including tables and
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embedded content, with higher success but may increase latency.
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basic costs 1 credit per 5 successful URL extractions,
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advanced costs 2 credits per 5 successful URL extractions.
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continue_on_failure: Whether to continue if extraction of a URL fails.
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"""
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if not urls:
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raise ValueError("At least one URL must be provided.")
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self.api_key = api_key
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self.urls = urls if isinstance(urls, list) else [urls]
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self.extract_depth = extract_depth
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self.continue_on_failure = continue_on_failure
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self.api_url = "https://api.tavily.com/extract"
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def lazy_load(self) -> Iterator[Document]:
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"""Extract and yield documents from the URLs using Tavily Extract API."""
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batch_size = 20
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for i in range(0, len(self.urls), batch_size):
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batch_urls = self.urls[i : i + batch_size]
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try:
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.api_key}",
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}
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# Use string for single URL, array for multiple URLs
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urls_param = batch_urls[0] if len(batch_urls) == 1 else batch_urls
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payload = {"urls": urls_param, "extract_depth": self.extract_depth}
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# Make the API call
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response = requests.post(self.api_url, headers=headers, json=payload)
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response.raise_for_status()
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response_data = response.json()
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# Process successful results
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for result in response_data.get("results", []):
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url = result.get("url", "")
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content = result.get("raw_content", "")
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if not content:
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log.warning(f"No content extracted from {url}")
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continue
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# Add URLs as metadata
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metadata = {"source": url}
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yield Document(
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page_content=content,
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metadata=metadata,
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)
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for failed in response_data.get("failed_results", []):
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url = failed.get("url", "")
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error = failed.get("error", "Unknown error")
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log.error(f"Failed to extract content from {url}: {error}")
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except Exception as e:
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if self.continue_on_failure:
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log.error(f"Error extracting content from batch {batch_urls}: {e}")
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else:
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raise e
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