""" title: Better Web Search Tool ! PUT web_wearch ID TO WORK WITH AUTO WEBSEARCH TOOL ! description: Web Search using SearXNG and Scraper for first pages with messages and citations. author: TRUC Yoann """ 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["title"]) url_site = result["url"] snippet = result.get("content", "") # Check if the website is in the ignored list, but only if IGNORED_WEBSITES is not empty 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, step_number=None, ): if self.event_emitter: message = { "type": "status", "data": { "status": status, "description": description, "done": done, }, } if step_number: message["data"]["step"] = step_number await self.event_emitter(message) class Tools: class Valves(BaseModel): SEARXNG_ENGINE_API_BASE_URL: str = Field( default="http://host.docker.internal:8080/search", description="The base URL for Search Engine", ) 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=True, # Changé à True par défaut description="If True, send custom citations with links and metadata", ) def __init__(self): self.valves = self.Valves() self.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" } 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("🔍 Démarrage de la recherche web", step_number=1) await emitter.emit(f"📝 Recherche pour la requête: {query}", step_number=2) search_engine_url = self.valves.SEARXNG_ENGINE_API_BASE_URL if self.valves.RETURNED_SCRAPPED_PAGES_NO > self.valves.SCRAPPED_PAGES_NO: self.valves.RETURNED_SCRAPPED_PAGES_NO = self.valves.SCRAPPED_PAGES_NO await emitter.emit( "⚙️ Ajustement des paramètres de recherche", step_number=3 ) params = { "q": query, "format": "json", "number_of_results": self.valves.RETURNED_SCRAPPED_PAGES_NO, } try: await emitter.emit("🌐 Connexion au moteur de recherche", step_number=4) resp = requests.get( search_engine_url, params=params, headers=self.headers, timeout=120 ) resp.raise_for_status() data = resp.json() results = data.get("results", []) limited_results = results[: self.valves.SCRAPPED_PAGES_NO] await emitter.emit( f"📊 {len(limited_results)} résultats trouvés", step_number=5 ) except requests.exceptions.RequestException as e: await emitter.emit( status="error", description=f"❌ Erreur lors de la recherche: {str(e)}", done=True, ) return json.dumps({"error": str(e)}) results_json = [] if limited_results: await emitter.emit( "🔄 Traitement des résultats de recherche", step_number=6 ) with concurrent.futures.ThreadPoolExecutor() as executor: futures = [ executor.submit( functions.process_search_result, result, self.valves ) for result in limited_results ] processed_count = 0 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) processed_count += 1 await emitter.emit( f"📄 Traitement de la page {processed_count}/{len(limited_results)}", step_number=7, ) 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__: await emitter.emit( "📚 Génération des citations et références", step_number=8 ) for result in results_json: await __event_emitter__( { "type": "citation", "data": { "document": [result["content"]], "metadata": [ { "source": result["url"], "date_accessed": datetime.now().isoformat(), "title": result["title"], } ], "source": { "name": result["title"], "url": result["url"], }, }, } ) await emitter.emit( status="complete", description=f"✅ Recherche terminée - {len(results_json)} pages analysées", done=True, step_number=9, ) 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"🔍 Accès à l'URL: {url}", step_number=1) results_json = [] try: await emitter.emit("🌐 Téléchargement du contenu", step_number=2) response_site = requests.get(url, headers=self.headers, timeout=120) response_site.raise_for_status() html_content = response_site.text await emitter.emit("📑 Analyse du contenu de la page", step_number=3) 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 await emitter.emit("📝 Extraction et formatage du texte", step_number=4) 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 ) await emitter.emit("📊 Création du résumé", step_number=5) result_site = { "title": title_site, "url": url_site, "content": truncated_content, "excerpt": functions.generate_excerpt(content_site), "date_accessed": datetime.now().isoformat(), } results_json.append(result_site) if self.valves.CITATION_LINKS and __event_emitter__: await emitter.emit("📚 Génération des citations", step_number=6) await __event_emitter__( { "type": "citation", "data": { "document": [truncated_content], "metadata": [ { "source": url_site, "date_accessed": datetime.now().isoformat(), "title": title_site, } ], "source": { "name": title_site, "url": url_site, "type": "webpage", }, }, } ) await emitter.emit( status="complete", description="✅ Contenu du site web extrait et traité avec succès", done=True, step_number=7, ) except requests.exceptions.RequestException as e: await emitter.emit( status="error", description=f"❌ Erreur lors de l'accès à la page: {str(e)}", done=True, ) results_json.append( { "url": url, "content": f"Échec de la récupération de la page. Erreur: {str(e)}", "error": True, "date_accessed": datetime.now().isoformat(), } ) return json.dumps(results_json, ensure_ascii=False)