bot.ipynb

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    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'numpy'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnumpy\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnltk\u001b[39;00m\n\u001b[0;32m      3\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mstring\u001b[39;00m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'numpy'"
     ]
    }
   ],
   "source": [
    "import nltk\n",
    "import string\n",
    "import random\n",
    "\n",
    "nltk.download('punkt')\n",
    "nltk.download('wordnet')\n",
    "\n",
    "# Predefined chatbot responses\n",
    "GREET_INPUTS = (\"hello\", \"hi\", \"greetings\", \"sup\", \"what's up\", \"hey\")\n",
    "GREET_RESPONSES = [\"hi\", \"hello\", \"*nods*\", \"hi there\", \"hello\", \"I am glad! You are talking to me\"]\n",
    "\n",
    "# Define your responses here\n",
    "RESPONSES = {\n",
    "    \"what is data science\": \"Data science is the field that deals with analyzing and interpreting data to extract valuable insights and knowledge.\",\n",
    "    \"how does the algorithm work\": \"Algorithms are step-by-step instructions that guide the computer in performing specific tasks or calculations.\",\n",
    "    # Add more responses here\n",
    "}\n",
    "\n",
    "# Tokenization and normalization functions\n",
    "lemmer = nltk.stem.WordNetLemmatizer()\n",
    "\n",
    "def LemTokens(tokens):\n",
    "    return [lemmer.lemmatize(token) for token in tokens]\n",
    "\n",
    "remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)\n",
    "\n",
    "def LemNormalize(text):\n",
    "    return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))\n",
    "\n",
    "# Greeting function\n",
    "def greet(sentence):\n",
    "    for word in sentence.split():\n",
    "        if word.lower() in GREET_INPUTS:\n",
    "            return random.choice(GREET_RESPONSES)\n",
    "\n",
    "# Response function\n",
    "def response(user_response):\n",
    "    robo1_response = ''\n",
    "    TfidfVec = TfidfVectorizer(tokenizer=LemNormalize, stop_words='english')\n",
    "    tfidf = TfidfVec.fit_transform([user_response])\n",
    "    vals = cosine_similarity(tfidf[-1], tfidf)\n",
    "    idx = vals.argsort()[0][-2]\n",
    "    flat = vals.flatten()\n",
    "    flat.sort()\n",
    "    req_tfidf = flat[-2]\n",
    "    if req_tfidf == 0:\n",
    "        robo1_response = \"I am sorry! I don't understand you.\"\n",
    "        return robo1_response\n",
    "    else:\n",
    "        robo1_response = RESPONSES.get(user_response, \"I am sorry! I don't have an answer for that.\")\n",
    "        return robo1_response\n",
    "\n",
    "# Main chat loop\n",
    "flag = True\n",
    "print(\"BOT: My name is Strak. Let's have a conversation! Also, if you want to exit at any time, just type 'Bye!'\")\n",
    "while flag:\n",
    "    user_response = input()\n",
    "    user_response = user_response.lower()\n",
    "    if user_response != 'bye':\n",
    "        if user_response == 'thanks' or user_response == 'thank you':\n",
    "            flag = False\n",
    "            print(\"BOT: You are welcome.\")\n",
    "        else:\n",
    "            if greet(user_response) is not None:\n",
    "                print(\"BOT: \" + greet(user_response))\n",
    "            else:\n",
    "                print(\"BOT: \", end=\"\")\n",
    "                print(response(user_response))\n",
    "    else:\n",
    "        flag = False\n",
    "        print(\"BOT: Goodbye! Take care <3\")\n"
   ]
  }
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