""" title: Web Search using Bing and Scrape first N Pages author: velepost funding_url: https://github.com/open-webui version: 0.1.12 license: MIT """ import os import requests from datetime import datetime import json from requests import get from bs4 import BeautifulSoup import concurrent.futures from html.parser import HTMLParser from urllib.parse import urlparse, urljoin import re import unicodedata from pydantic import BaseModel, Field import asyncio from typing import Callable, Any class HelpFunctions: def __init__(self): pass def get_base_url(self, url): parsed_url = urlparse(url) base_url = f"{parsed_url.scheme}://{parsed_url.netloc}" return base_url def generate_excerpt(self, content, max_length=200): return content[:max_length] + "..." if len(content) > max_length else content def format_text(self, original_text): soup = BeautifulSoup(original_text, "html.parser") formatted_text = soup.get_text(separator=" ", strip=True) formatted_text = unicodedata.normalize("NFKC", formatted_text) formatted_text = re.sub(r"\s+", " ", formatted_text) formatted_text = formatted_text.strip() formatted_text = self.remove_emojis(formatted_text) return formatted_text def remove_emojis(self, text): return "".join(c for c in text if not unicodedata.category(c).startswith("So")) def process_search_result(self, result, valves): title_site = self.remove_emojis(result["name"]) url_site = result["url"] snippet = result.get("snippet", "") if valves.IGNORED_WEBSITES: base_url = self.get_base_url(url_site) if any( ignored_site.strip() in base_url for ignored_site in valves.IGNORED_WEBSITES.split(",") ): return None try: response_site = requests.get(url_site, timeout=20) response_site.raise_for_status() html_content = response_site.text soup = BeautifulSoup(html_content, "html.parser") content_site = self.format_text(soup.get_text(separator=" ", strip=True)) truncated_content = self.truncate_to_n_words( content_site, valves.PAGE_CONTENT_WORDS_LIMIT ) return { "title": title_site, "url": url_site, "content": truncated_content, "snippet": self.remove_emojis(snippet), } except requests.exceptions.RequestException as e: return None def truncate_to_n_words(self, text, token_limit): tokens = text.split() truncated_tokens = tokens[:token_limit] return " ".join(truncated_tokens) class EventEmitter: def __init__(self, event_emitter: Callable[[dict], Any] = None): self.event_emitter = event_emitter async def emit(self, description="Unknown State", status="in_progress", done=False): if self.event_emitter: await self.event_emitter( { "type": "status", "data": { "status": status, "description": description, "done": done, }, } ) class Tools: class Valves(BaseModel): BING_API_ENDPOINT: str = Field( default="https://api.bing.microsoft.com/v7.0/search", description="The endpoint for Bing Search API", ) BING_API_KEY: str = Field( default="YOUR_BING_API_KEY", description="Your Bing Search API key", ) IGNORED_WEBSITES: str = Field( default="", description="Comma-separated list of websites to ignore", ) RETURNED_SCRAPPED_PAGES_NO: int = Field( default=3, description="The number of Search Engine Results to Parse", ) SCRAPPED_PAGES_NO: int = Field( default=5, description="Total pages scapped. Ideally greater than one of the returned pages", ) PAGE_CONTENT_WORDS_LIMIT: int = Field( default=5000, description="Limit words content for each page.", ) CITATION_LINKS: bool = Field( default=False, description="If True, send custom citations with links", ) def __init__(self): self.valves = self.Valves() async def search_web( self, query: str, __event_emitter__: Callable[[dict], Any] = None, ) -> str: """ Search the web and get the content of the relevant pages. Search for unknown knowledge, news, info, public contact info, weather, etc. :params query: Web Query used in search engine. :return: The content of the pages in json format. """ functions = HelpFunctions() emitter = EventEmitter(__event_emitter__) await emitter.emit(f"Initiating web search for: {query}") search_engine_url = self.valves.BING_API_ENDPOINT if self.valves.RETURNED_SCRAPPED_PAGES_NO > self.valves.SCRAPPED_PAGES_NO: self.valves.RETURNED_SCRAPPED_PAGES_NO = self.valves.SCRAPPED_PAGES_NO params = { "q": query, "count": self.valves.RETURNED_SCRAPPED_PAGES_NO, } headers = {"Ocp-Apim-Subscription-Key": self.valves.BING_API_KEY} try: await emitter.emit("Sending request to Bing Search API") resp = requests.get( search_engine_url, params=params, headers=headers, timeout=120 ) resp.raise_for_status() data = resp.json() results = data.get("webPages", {}).get("value", []) limited_results = results[: self.valves.SCRAPPED_PAGES_NO] await emitter.emit(f"Retrieved {len(limited_results)} search results") except requests.exceptions.RequestException as e: error_details = {"error": str(e), "headers": headers, "params": params} await emitter.emit( status="error", description=f"Error during search: {json.dumps(error_details, indent=2)}", done=True, ) return json.dumps(error_details) results_json = [] if limited_results: await emitter.emit(f"Processing search results") with concurrent.futures.ThreadPoolExecutor() as executor: futures = [ executor.submit( functions.process_search_result, result, self.valves ) for result in limited_results ] for future in concurrent.futures.as_completed(futures): result_json = future.result() if result_json: try: json.dumps(result_json) results_json.append(result_json) except (TypeError, ValueError): continue if len(results_json) >= self.valves.RETURNED_SCRAPPED_PAGES_NO: break results_json = results_json[: self.valves.RETURNED_SCRAPPED_PAGES_NO] if self.valves.CITATION_LINKS and __event_emitter__: for result in results_json: await __event_emitter__( { "type": "citation", "data": { "document": [result["content"]], "metadata": [{"source": result["url"]}], "source": {"name": result["title"]}, }, } ) await emitter.emit( status="complete", description=f"Web search completed. Retrieved content from {len(results_json)} pages", done=True, ) return json.dumps(results_json, ensure_ascii=False) async def get_website( self, url: str, __event_emitter__: Callable[[dict], Any] = None ) -> str: """ Web scrape the website provided and get the content of it. :params url: The URL of the website. :return: The content of the website in json format. """ functions = HelpFunctions() emitter = EventEmitter(__event_emitter__) await emitter.emit(f"Fetching content from URL: {url}") results_json = [] try: headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3" } response_site = requests.get(url, headers=headers, timeout=120) response_site.raise_for_status() html_content = response_site.text await emitter.emit("Parsing website content") soup = BeautifulSoup(html_content, "html.parser") page_title = soup.title.string if soup.title else "No title found" page_title = unicodedata.normalize("NFKC", page_title.strip()) page_title = functions.remove_emojis(page_title) title_site = page_title url_site = url content_site = functions.format_text( soup.get_text(separator=" ", strip=True) ) truncated_content = functions.truncate_to_n_words( content_site, self.valves.PAGE_CONTENT_WORDS_LIMIT ) result_site = { "title": title_site, "url": url_site, "content": truncated_content, "excerpt": functions.generate_excerpt(content_site), } results_json.append(result_site) if self.valves.CITATION_LINKS and __event_emitter__: await __event_emitter__( { "type": "citation", "data": { "document": [truncated_content], "metadata": [{"source": url_site}], "source": {"name": title_site}, }, } ) await emitter.emit( status="complete", description="Website content retrieved and processed successfully", done=True, ) except requests.exceptions.RequestException as e: results_json.append( { "url": url, "content": f"Failed to retrieve the page. Error: {str(e)}", } ) await emitter.emit( status="error", description=f"Error fetching website content: {str(e)}", done=True, ) return json.dumps(results_json, ensure_ascii=False)