import os
import requests
from datetime import datetime
import json
import logging
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 Any, List, Optional
import httpx
logger = logging.getLogger("web_search")

async def call_improve_web_query(text: str, max_chars: int = 20000, objective: str = None, style: str = None):
    url = "http://localhost:8080/improve_web_query"
    params = {"text": text, "max_chars": max_chars}
    if objective:
        params["objective"] = objective
    if style:
        params["style"] = style

    async with httpx.AsyncClient() as client:
        response = await client.get(url, params=params)
        return response.json()

class HelpFunctions:
    def __init__(self):
        pass

    def get_base_url(self, url: str) -> str:
        parsed_url = urlparse(url)
        base_url = f"{parsed_url.scheme}://{parsed_url.netloc}"
        return base_url

    def generate_excerpt(self, content: str, max_length: int = 200) -> str:
        return content[:max_length] + "..." if len(content) > max_length else content

    def format_text(self, original_text: str) -> str:
        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: str) -> str:
        return "".join(c for c in text if not unicodedata.category(c).startswith("So"))

    def process_search_result(self, result: dict, valves: Any) -> Optional[dict]:
        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: str, token_limit: int) -> str:
        tokens = text.split()
        truncated_tokens = tokens[:token_limit]
        return " ".join(truncated_tokens)

class EventEmitter:
    def __init__(self, event_emitter: Optional[Any] = None):
        self.event_emitter = event_emitter

    async def emit(self, description: str = "Unknown State", status: str = "in_progress", done: bool = False):
        if self.event_emitter:
            await self.event_emitter(
                {
                    "type": "status",
                    "data": {
                        "status": status,
                        "description": description,
                        "done": done,
                    },
                }
            )

class Tools:
    class Valves(BaseModel):
        SEARXNG_ENGINE_API_BASE_URL: str = Field(
            default="http://192.168.100.1:8899/search",
            description="The base URL for SearXNG 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=False,
            description="If True, send custom citations with links",
        )

    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
    ) -> str:
        """
        Search the web using SearXNG and get the content of the relevant pages.
        :param query: Web Query used in search engine.
        :param __event_emitter__: Optional event emitter for status updates.
        :return: The content of the pages in json format.
        """
        logger.info(" in query: %s",query)
        try:
            #query=asyncio.run(call_improve_web_query(query))
            pass
        except Exception as e:
            logger.error("ERROR: %s",str(e))
        logger.info(" out query: %s",query)
        __event_emitter__=None
        functions = HelpFunctions()
        emitter = EventEmitter(__event_emitter__)

        await emitter.emit(description=f"Initiating web search for: {query}")

        search_engine_url = self.valves.SEARXNG_ENGINE_API_BASE_URL

        # Ensure RETURNED_SCRAPPED_PAGES_NO does not exceed SCRAPPED_PAGES_NO
        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,
            "format": "json",
            "number_of_results": self.valves.RETURNED_SCRAPPED_PAGES_NO,
        }

        try:
            await emitter.emit(description="Sending request to search engine")
            resp = requests.get(
                search_engine_url, params=params, headers=self.headers, timeout=120
            )
            logger.info("query : %s", query)
            logger.info("REQUEST URL: %s", resp.url)

            resp.raise_for_status()
            data = resp.json()

            results = data.get("results", [])
            limited_results = results[: self.valves.SCRAPPED_PAGES_NO]
            await emitter.emit(description=f"Retrieved {len(limited_results)} search results")

        except requests.exceptions.RequestException as e:
            await emitter.emit(
                status="error",
                description=f"Error during search: {str(e)}",
                done=True,
            )
            return json.dumps({"error": str(e)})

        results_json = []
        if limited_results:
            await emitter.emit(description=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
    ) -> str:
        """
        Web scrape the website provided and get the content of it.
        :param url: The URL of the website.
        :param __event_emitter__: Optional event emitter for status updates.
        :return: The content of the website in json format.
        """
        __event_emitter__=None
        functions = HelpFunctions()
        emitter = EventEmitter(__event_emitter__)
        if 'http' not in url:
            #assume that a https:// prepend is needed.
            url='https://'+url

        await emitter.emit(description=f"Fetching content from URL: {url}")

        results_json = []

        try:
            response_site = requests.get(url, headers=self.headers, timeout=120)
            response_site.raise_for_status()
            html_content = response_site.text

            await emitter.emit(description="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)