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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() |