Bounty_Llama_Chatbot_with_Sentiment_Analysis_Integration_(Mental_Health_Assistant).ipynb

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      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyOdsND87PKSJH5ODgSq+cqi",
      "include_colab_link": true
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      "name": "python3",
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    "language_info": {
      "name": "python"
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    "accelerator": "GPU"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/daviddprtma/Llama-Chatbot-with-Sentiment-Analysis-Integration/blob/main/Bounty_Llama_Chatbot_with_Sentiment_Analysis_Integration_(Mental_Health_Assistant).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Overview of Mental Health Assistant\n",
        "\n",
        "Mental Health Assistant is a compassionate and supportive chatbot designed to provide users with emotional support and encouragement. Utilizing advanced sentiment analysis powered by Hugging Face's AI models, this assistant can detect when users are feeling down or expressing negative emotions.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Key Features:\n",
        "\n",
        "\n",
        "* Sentiment Detection: The assistant analyzes user input to identify emotional states, allowing it to respond appropriately to feelings of sadness, anxiety, or distress.\n",
        "\n",
        "* Uplifting Responses: When negative sentiments are detected, the chatbot offers comforting and encouraging messages, reminding users that they are not alone and that it's okay to seek help.\n",
        "\n",
        "* Positive Reinforcement: For users expressing positive feelings, the assistant reinforces this positivity with affirmations and encouragement to maintain a healthy mindset.\n",
        "\n",
        "* User-Friendly Interface: Built with Gradio, the chatbot features an intuitive interface that makes it easy for users to interact with the assistant in a conversational manner.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Purpose:\n",
        "\n",
        "Mental Health Assistant aims to provide immediate emotional support, promote mental well-being, and foster a sense of connection. It serves as a helpful resource for individuals seeking comfort, guidance, or simply a friendly conversation about their feelings. This tool is particularly beneficial in applications focused on mental health support, making it accessible to anyone who may need a listening ear.\n",
        "\n",
        "In here, I will assist step by step about how you can talk to Mental Health Assistant by ask to the bot according to your mood and the Chatbot will give you the answer according to your mood."
      ],
      "metadata": {
        "id": "UEsvGgb9OM6k"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Install Required Libraries\n",
        "\n",
        "  Run the following code to install the necessary libraries:"
      ],
      "metadata": {
        "id": "5NDaadv4PYQG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers torch gradio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fu_CmpnBJyni",
        "outputId": "ba0d6bdd-7832-4f69-e4e3-3eacf7ce4b7c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. Import Libraries\n",
        "\n",
        "  Import the required libraries:"
      ],
      "metadata": {
        "id": "Csr4PhOyPyZC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from transformers import pipeline\n",
        "import gradio as gr\n"
      ],
      "metadata": {
        "id": "ss1ib6OgKIHr"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "3. Load the Sentiment Analysis Model\n",
        "\n",
        "  Load a pre-trained sentiment analysis model from Hugging Face:"
      ],
      "metadata": {
        "id": "IGizTmezQcka"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Load sentiment analysis pipeline\n",
        "sentiment_analysis = pipeline(\"sentiment-analysis\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JbZSpHnIKN_B",
        "outputId": "23e1ac5a-9295-4ad9-dd11-24a2b36c4c76"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "No model was supplied, defaulted to distilbert/distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
            "  warnings.warn(\n",
            "Hardware accelerator e.g. GPU is available in the environment, but no `device` argument is passed to the `Pipeline` object. Model will be on CPU.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "4. Define the Chatbot Logic\n",
        "\n",
        "  Create a function that detects the user's sentiment and provides uplifting messages:\n",
        "\n"
      ],
      "metadata": {
        "id": "xIKHnqpWQkuD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def mental_health_chatbot(user_input):\n",
        "    # Analyze the sentiment of the user input\n",
        "    result = sentiment_analysis(user_input)[0]\n",
        "\n",
        "    # Check the sentiment\n",
        "    if result['label'] == 'NEGATIVE' and result['score'] > 0.5:\n",
        "        response = \"I'm really sorry to hear that you're feeling this way. Remember, it's okay to ask for help. You're not alone!\"\n",
        "    elif result['label'] == 'POSITIVE':\n",
        "        response = \"That's great to hear! Keep up the positive mindset. Remember to take care of yourself!\"\n",
        "    else:\n",
        "        response = \"Thank you for sharing your thoughts. I'm here to listen if you want to talk more.\"\n",
        "\n",
        "    return response\n"
      ],
      "metadata": {
        "id": "6ihATmXlKTBI"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "5. Create Gradio Interface\n",
        "\n",
        "  Set up the Gradio interface for user interaction:\n",
        "\n"
      ],
      "metadata": {
        "id": "KNB1b1IYQsvH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def chat_interface(user_input):\n",
        "    return mental_health_chatbot(user_input)\n",
        "\n",
        "# Create the Gradio interface\n",
        "iface = gr.Interface(\n",
        "    fn=chat_interface,\n",
        "    inputs=\"text\",\n",
        "    outputs=\"text\",\n",
        "    title=\"Mental Health Assistant\",\n",
        "    description=\"A chatbot that detects when you are feeling down and provides uplifting and supportive messages.\"\n",
        ")\n",
        "\n",
        "# Launch the interface\n",
        "iface.launch()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "uQ2t4DdCKcxp",
        "outputId": "01455361-125e-4724-f79c-4f640fb1553a"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://9156350666492b5f7d.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://9156350666492b5f7d.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    }
  ]
}