model.py

import numpy as np
import pandas as pd
import requests
from io import StringIO
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
import speech_recognition as sr
import pyttsx3
from googlesearch import search
from bs4 import BeautifulSoup
import urllib.request
from urllib.parse import quote

class HybridChatBot:
    def __init__(self, dataset_url=None):
        self.dataset_url = dataset_url
        self.qa_pairs = {}
        self.vectorizer = TfidfVectorizer()
        self.X = None
        self.recognizer = sr.Recognizer()
        self.engine = pyttsx3.init()
        
        # Voice engine settings
        voices = self.engine.getProperty('voices')
        self.engine.setProperty('voice', voices[0].id)
        self.engine.setProperty('rate', 150)
        
        if dataset_url:
            self.load_dataset()
            self.train()

    def load_dataset(self):
        """Load dataset from web resource"""
        try:
            response = requests.get(self.dataset_url)
            response.raise_for_status()
            
            if self.dataset_url.endswith('.csv'):
                data = pd.read_csv(StringIO(response.text))
            elif self.dataset_url.endswith('.json'):
                data = pd.read_json(StringIO(response.text))
            else:
                print("File format not supported")
                return
                
            for _, row in data.iterrows():
                self.qa_pairs[row["question"].lower()] = row["answer"]
                
            print(f"Loaded {len(self.qa_pairs)} question-answer pairs")
            
        except Exception as e:
            print(f"Error loading dataset: {e}")

    def train(self):
        """Train the model on loaded data"""
        if not self.qa_pairs:
            print("No data available for training!")
            return
        
        questions = list(self.qa_pairs.keys())
        self.X = self.vectorizer.fit_transform(questions)
        print("Model trained on loaded data")

    def add_qa_pair(self, question, answer):
        """Add new question-answer pair"""
        self.qa_pairs[question.lower()] = answer
        self.train()

    def web_search(self, query, num_results=3):
        """Perform web search and extract information"""
        try:
            print(f"\nSearching the web: {query}")
            search_results = []
            
            # Perform Google search
            for url in search(query, num_results=num_results, lang='en'):
                try:
                    # Get page content
                    req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
                    with urllib.request.urlopen(req, timeout=5) as response:
                        html = response.read()
                    
                    # Parse HTML
                    soup = BeautifulSoup(html, 'html.parser')
                    
                    # Remove unwanted elements (scripts, styles, etc.)
                    for script in soup(["script", "style", "iframe", "nav", "footer"]):
                        script.extract()
                    
                    # Get page text
                    text = soup.get_text(separator=' ', strip=True)
                    text = ' '.join(text.split()[:200])  # Take first 200 words
                    
                    search_results.append({
                        'url': url,
                        'content': text
                    })
                    
                except Exception as e:
                    print(f"Error processing {url}: {e}")
                    continue
            
            return search_results
            
        except Exception as e:
            print(f"Search error: {e}")
            return None

    def get_response(self, user_input):
        """Get response to user input"""
        if not self.qa_pairs:
            return "I'm not trained yet. Please add questions and answers."
        
        # Check if user wants to perform web search
        if "search the web for" in user_input.lower() or "find online" in user_input.lower():
            query = user_input.replace("search the web for", "").replace("find online", "").strip()
            search_results = self.web_search(query)
            if search_results:
                response = "Here's what I found online:\n"
                for i, result in enumerate(search_results, 1):
                    response += f"\n{i}. {result['content']}\n(Source: {result['url']})\n"
                return response[:2000]  # Limit response length
            else:
                return "Couldn't find any information online."
        
        # Regular question-answer search
        user_vec = self.vectorizer.transform([user_input.lower()])
        similarities = cosine_similarity(user_vec, self.X)
        best_match_idx = np.argmax(similarities)
        best_match_score = similarities[0, best_match_idx]
        
        if best_match_score > 0.5:
            best_question = list(self.qa_pairs.keys())[best_match_idx]
            return self.qa_pairs[best_question]
        else:
            return "I don't know the answer to this question. Would you like me to search online? (Say 'search the web for...')"

    def text_to_speech(self, text):
        """Convert text to speech"""
        self.engine.say(text)
        self.engine.runAndWait()

    def speech_to_text(self):
        """Convert speech from microphone to text"""
        with sr.Microphone() as source:
            print("\nSpeak now...")
            self.recognizer.adjust_for_ambient_noise(source)
            try:
                audio = self.recognizer.listen(source, timeout=5)
                text = self.recognizer.recognize_google(audio, language="en-US")
                print(f"Recognized: {text}")
                return text
            except sr.UnknownValueError:
                print("Speech not recognized")
                return None
            except sr.RequestError:
                print("Recognition service error")
                return None
            except sr.WaitTimeoutError:
                print("Timeout expired")
                return None

    def run(self):
        """Improved interaction interface"""
        print("\n" + "="*50)
        print("WELCOME TO INTELLIGENT CHATBOT".center(50))
        print("="*50)
        
        current_mode = "text"
        while True:
            print("\n" + "-"*50)
            print(f"Current input mode: {current_mode.upper()}")
            print("[1] Send text message")
            print("[2] Speak to the bot")
            print("[3] Switch input mode")
            print("[4] Teach the bot a new answer")
            print("[5] Web search")
            print("[6] Exit")
            
            try:
                choice = input("Choose action (1-6): ").strip()
                
                if choice == "1":
                    user_input = input("\nYour message: ")
                    if user_input.lower() in ["exit", "stop"]:
                        break
                        
                    response = self.get_response(user_input)
                    if response:
                        print(f"\nBot: {response}")
                        self.text_to_speech(response)
                    else:
                        print("\nBot: I don't know what to say. Would you like to teach me?")
                
                elif choice == "2":
                    user_input = self.speech_to_text()
                    if user_input:
                        if user_input.lower() in ["exit", "stop"]:
                            break
                            
                        response = self.get_response(user_input)
                        if response:
                            print(f"\nBot: {response}")
                            self.text_to_speech(response)
                        else:
                            print("\nBot: I don't know how to respond to that.")
                            self.text_to_speech("I don't know how to respond to that")
                
                elif choice == "3":
                    current_mode = "voice" if current_mode == "text" else "text"
                    print(f"\nMode changed to: {current_mode.upper()}")
                
                elif choice == "4":
                    print("\nTeaching the bot:")
                    question = input("Enter question: ")
                    answer = input("Enter answer: ")
                    self.add_qa_pair(question, answer)
                    print("Bot successfully trained!")
                
                elif choice == "5":
                    query = input("\nEnter search query: ")
                    search_results = self.web_search(query)
                    if search_results:
                        print("\nSearch results:")
                        for i, result in enumerate(search_results, 1):
                            print(f"\n{i}. {result['content']}\n(Source: {result['url']})\n")
                    else:
                        print("\nNothing found.")
                
                elif choice == "6":
                    print("\nShutting down...")
                    break
                
                else:
                    print("\nPlease choose an option between 1 and 6")
            
            except KeyboardInterrupt:
                print("\nShutting down...")
                break

if __name__ == "__main__":
   
    DATASET_URL = "https://raw.githubusercontent.com/user/repo/main/qa_data.csv"
    
    bot = HybridChatBot(DATASET_URL)
    bot.run()