french_chatbot.ipynb

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            "Building wheels for collected packages: googletrans\n",
            "  Building wheel for googletrans (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for googletrans: filename=googletrans-4.0.0rc1-py3-none-any.whl size=17397 sha256=0b5d83017c4f89614b534748094bce72de57071810160c90629bc9c3b1e62449\n",
            "  Stored in directory: /root/.cache/pip/wheels/c0/59/9f/7372f0cf70160fe61b528532e1a7c8498c4becd6bcffb022de\n",
            "Successfully built googletrans\n",
            "Installing collected packages: rfc3986, hyperframe, hpack, h11, chardet, idna, hstspreload, h2, httpcore, httpx, googletrans\n",
            "  Attempting uninstall: h11\n",
            "    Found existing installation: h11 0.14.0\n",
            "    Uninstalling h11-0.14.0:\n",
            "      Successfully uninstalled h11-0.14.0\n",
            "  Attempting uninstall: chardet\n",
            "    Found existing installation: chardet 5.2.0\n",
            "    Uninstalling chardet-5.2.0:\n",
            "      Successfully uninstalled chardet-5.2.0\n",
            "  Attempting uninstall: idna\n",
            "    Found existing installation: idna 3.10\n",
            "    Uninstalling idna-3.10:\n",
            "      Successfully uninstalled idna-3.10\n",
            "  Attempting uninstall: httpcore\n",
            "    Found existing installation: httpcore 1.0.7\n",
            "    Uninstalling httpcore-1.0.7:\n",
            "      Successfully uninstalled httpcore-1.0.7\n",
            "  Attempting uninstall: httpx\n",
            "    Found existing installation: httpx 0.28.1\n",
            "    Uninstalling httpx-0.28.1:\n",
            "      Successfully uninstalled httpx-0.28.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "langsmith 0.2.10 requires httpx<1,>=0.23.0, but you have httpx 0.13.3 which is incompatible.\n",
            "openai 1.59.3 requires httpx<1,>=0.23.0, but you have httpx 0.13.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed chardet-3.0.4 googletrans-4.0.0rc1 h11-0.9.0 h2-3.2.0 hpack-3.0.0 hstspreload-2025.1.1 httpcore-0.9.1 httpx-0.13.3 hyperframe-5.2.0 idna-2.10 rfc3986-1.5.0\n"
          ]
        }
      ],
      "source": [
        "!pip install transformers googletrans==4.0.0-rc1\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import MarianMTModel, MarianTokenizer\n",
        "from googletrans import Translator\n"
      ],
      "metadata": {
        "id": "QvSWMlhWNTtE"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Load translation model\n",
        "def load_translation_model():\n",
        "    model_name = \"Helsinki-NLP/opus-mt-en-fr\"\n",
        "    tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "    model = MarianMTModel.from_pretrained(model_name)\n",
        "    return tokenizer, model\n",
        "\n",
        "tokenizer, model = load_translation_model()\n",
        "translator = Translator()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 388,
          "referenced_widgets": [
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        "outputId": "da0160f0-6cc7-4596-a3e9-71d6ad31c8d2"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/42.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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        {
          "output_type": "display_data",
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            "text/plain": [
              "source.spm:   0%|          | 0.00/778k [00:00<?, ?B/s]"
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        {
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          "data": {
            "text/plain": [
              "vocab.json:   0%|          | 0.00/1.34M [00:00<?, ?B/s]"
            ],
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          "metadata": {}
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/1.42k [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/301M [00:00<?, ?B/s]"
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to translate English to French\n",
        "# def translate_to_french(text):\n",
        "#     translated = model.generate(**tokenizer.prepare_seq2seq_batch([text], return_tensors=\"pt\"))\n",
        "#     return tokenizer.decode(translated[0], skip_special_tokens=True)\n",
        "\n"
      ],
      "metadata": {
        "id": "uPxutAQrjaeE"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def translate_batch_to_french(texts):\n",
        "    inputs = tokenizer(texts, return_tensors=\"pt\", padding=True, truncation=True)\n",
        "    inputs = {key: val.to('cuda') for key, val in inputs.items()}  # Move inputs to GPU\n",
        "    model.to('cuda')  # Move model to GPU\n",
        "    translations = model.generate(**inputs)\n",
        "    return [tokenizer.decode(t, skip_special_tokens=True) for t in translations]\n"
      ],
      "metadata": {
        "id": "zKh1f9cCoMEo"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Chatbot interaction\n",
        "def chatbot():\n",
        "    print(\"Bonjour! I am your French Teaching Chatbot. Ask me anything!\")\n",
        "    print(\"Examples: \\n- 'Translate I love apples'\\n- 'Teach me vocabulary'\\n- 'Explain French grammar'\\nType 'exit' to quit.\")\n",
        "\n",
        "    while True:\n",
        "        user_input = input(\"You: \")\n",
        "        if user_input.lower() == \"exit\":\n",
        "            print(\"Au revoir! Have a great day learning French!\")\n",
        "            break\n",
        "        elif \"translate\" in user_input.lower():\n",
        "            # Translation feature\n",
        "            english_text = user_input.replace(\"translate\", \"\").strip()\n",
        "            french_translation = translate_batch_to_french(english_text)\n",
        "            print(f\"Bot: Translation: {french_translation}\")\n",
        "        elif \"vocabulary\" in user_input.lower():\n",
        "            # Vocabulary teaching\n",
        "            print(\"Bot: Here are some basic French words:\")\n",
        "            print(\"1. Bonjour - Hello\")\n",
        "            print(\"2. Merci - Thank you\")\n",
        "            print(\"3. Oui - Yes\")\n",
        "            print(\"4. Non - No\")\n",
        "            print(\"5. Pomme - Apple\")\n",
        "        elif \"grammar\" in user_input.lower():\n",
        "            # Grammar explanation\n",
        "            print(\"Bot: Basic French Grammar:\")\n",
        "            print(\"- In French, adjectives agree with the noun in gender and number.\")\n",
        "            print(\"- Example: 'une pomme verte' (a green apple) vs. 'un chat noir' (a black cat).\")\n",
        "        else:\n",
        "            print(\"Bot: I can translate, teach vocabulary, or explain grammar. Try asking again!\")\n",
        "\n"
      ],
      "metadata": {
        "id": "czo2lesIZwMW"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Run the chatbot\n",
        "chatbot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gu5sO8fJjpmL",
        "outputId": "503f7ce5-55ec-403b-997f-ce7bfc941892"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Bonjour! I am your French Teaching Chatbot. Ask me anything!\n",
            "Examples: \n",
            "- 'Translate I love apples'\n",
            "- 'Teach me vocabulary'\n",
            "- 'Explain French grammar'\n",
            "Type 'exit' to quit.\n",
            "You: Translate I want to go to the market\n",
            "Bot: Translation: ['Traduire Je veux aller au marché']\n",
            "You: Good\n",
            "Bot: I can translate, teach vocabulary, or explain grammar. Try asking again!\n",
            "You: quit\n",
            "Bot: I can translate, teach vocabulary, or explain grammar. Try asking again!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "GXKr_bWIkjLo"
      },
      "execution_count": 8,
      "outputs": []
    }
  ]
}