chatbot1practice_14thaug.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/arshad831/Community_Workshops-/blob/main/chatbot1practice_14thaug.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Re-piilmTIAY"
      },
      "outputs": [],
      "source": [
        "pip install openai"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "yayHsWVbTUuP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1c650e5b-c9e5-4309-d940-ce210b7ad9f4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Requirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.10/dist-packages (from httpcore<0.18.0,>=0.15.0->httpx->gradio) (3.7.1)\n",
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            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (0.30.2)\n",
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            "Requirement already satisfied: uc-micro-py in /usr/local/lib/python3.10/dist-packages (from linkify-it-py<3,>=1->markdown-it-py[linkify]>=2.0.0->gradio) (1.0.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib~=3.0->gradio) (1.16.0)\n",
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            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=ae6a446cb3558a1ac738a956557d50b9fbe5763f798f8a8364f03787737188d3\n",
            "  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, semantic-version, python-multipart, orjson, markdown-it-py, h11, aiofiles, uvicorn, starlette, mdit-py-plugins, huggingface-hub, httpcore, httpx, fastapi, gradio-client, gradio\n",
            "  Attempting uninstall: markdown-it-py\n",
            "    Found existing installation: markdown-it-py 3.0.0\n",
            "    Uninstalling markdown-it-py-3.0.0:\n",
            "      Successfully uninstalled markdown-it-py-3.0.0\n",
            "  Attempting uninstall: mdit-py-plugins\n",
            "    Found existing installation: mdit-py-plugins 0.4.0\n",
            "    Uninstalling mdit-py-plugins-0.4.0:\n",
            "      Successfully uninstalled mdit-py-plugins-0.4.0\n",
            "Successfully installed aiofiles-23.2.1 fastapi-0.101.0 ffmpy-0.3.1 gradio-3.40.1 gradio-client-0.4.0 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 huggingface-hub-0.16.4 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 orjson-3.9.4 pydub-0.25.1 python-multipart-0.0.6 semantic-version-2.10.0 starlette-0.27.0 uvicorn-0.23.2 websockets-11.0.3\n"
          ]
        }
      ],
      "source": [
        "pip install gradio"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**The chat function Explantion**\n",
        "\n",
        "\n",
        "This code defines a function called \"chatgpt_clone\" that takes two inputs: \"input\" and \"history\". The purpose of this function is to create a chatbot that mimics the behavior of OpenAI's GPT (Generative Pre-trained Transformer) model.\n",
        "\n",
        "Let's break down the code step by step:\n",
        "\n",
        "a\n",
        "\n",
        "b\n",
        "\n",
        "a+b : c\n",
        "\n",
        "a+b+c : d\n",
        "\n",
        "a+b+C+D : e\n",
        "\n",
        "a+b+C+D + e+ emplty : Stop\n",
        "\n",
        "\n",
        "history = history or []: This line checks if the \"history\" variable has a value. If it does, it keeps that value. If \"history\" is empty or has no value, it sets \"history\" as an empty list [].\n",
        "\n",
        "s = list(sum(history, ())): This line takes the \"history\" list, combines all the elements within it into a single list, and assigns it to the variable \"s\".\n",
        "\n",
        "s.append(input): It adds the \"input\" (the user's message) to the \"s\" list. This way, \"s\" now contains both the previous conversation history and the new user input.\n",
        "\n",
        "inp = ' '.join(s): This line converts the list \"s\" into a single string \"inp\". It joins all the elements of \"s\" with spaces in between, creating a single string representing the conversation history and the new input.\n",
        "\n",
        "output = openai_create(inp): This line uses a function called \"openai_create\" to generate a response from the chatbot based on the combined conversation history and the user input stored in \"inp\".\n",
        "\n",
        "history.append((input, output)): It adds a tuple containing the user input (\"input\") and the chatbot's response (\"output\") to the \"history\" list. This way, the chatbot retains a record of the conversation.\n",
        "\n",
        "return history, history: Finally, the function returns two copies of the \"history\" list. The first copy is the original \"history\" list, and the second copy includes the new user input and chatbot response, making it the updated history."
      ],
      "metadata": {
        "id": "jetAfF3BxDXu"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 610
        },
        "id": "4A6TK2CsTGdW",
        "outputId": "38db2946-2879-45a5-b659-a40941ba9022"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://8dd04a8c7f1683c394.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://8dd04a8c7f1683c394.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": 2
        }
      ],
      "source": [
        "import os\n",
        "import openai\n",
        "import gradio as gr\n",
        "\n",
        "#if you have OpenAI API key as an environment variable, enable the below\n",
        "#openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n",
        "\n",
        "#if you have OpenAI API key as a string, enable the below\n",
        "openai.api_key = \"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\"\n",
        "\n",
        "start_sequence = \"\\nAI:\"\n",
        "restart_sequence = \"\\nHuman: \"\n",
        "\n",
        "#prompt = \"The following is a academic conversation with an AI tutor and a student. The tutor is helpful and clever. The tutor answers python related questions and gives example in simple manner. The tutor helps with process , code and explanation. If any questions outside python domain , Kindly Instruct to ask Python Question.\\n\\nHuman: Hello, who are you?\\nAI: I am an AI created by OpenAI. How can I help you today?\\nHuman:What is your name?\\nAI:I am an AI bot.\\nHuman:Hi there!\\nAI:Hello! How can I assist you today?\\nHuman:\"\n",
        "prompt = \"You are a python programming instructor bot and your name is Python Master.  You will answer any and only python programming related questions in a simple manner which even a seventh grader will be able to understand easily. Your answer must include examples, syntaxes and syntax errors. If the question that is asked is not python related kindly ask the user to ask python related question instead.\\nHuman:What is your name?\\nAI:I am an AI bot.\\nHuman:Hi there!\\nAI:Hello! How can I assist you today?\\nHuman:\"\n",
        "def openai_create(prompt):\n",
        "\n",
        "    response = openai.Completion.create(\n",
        "    model=\"text-davinci-003\",\n",
        "    prompt=prompt,\n",
        "    temperature=0,\n",
        "    max_tokens=500,\n",
        "    top_p=0.1,\n",
        "    frequency_penalty=0.4,\n",
        "    presence_penalty=1.35,\n",
        "    stop=[\" Human:\", \" AI:\"]\n",
        "    )\n",
        "\n",
        "    return response.choices[0].text\n",
        "\n",
        "\n",
        "\n",
        "def chatgpt_clone(input, history):\n",
        "    history = history or []\n",
        "    s = list(sum(history, ()))\n",
        "    s.append(input)\n",
        "    inp = ' '.join(s)\n",
        "    output = openai_create(inp)\n",
        "    history.append((input, output))\n",
        "    return history, history\n",
        "\n",
        "#gradio integration\n",
        "\n",
        "block = gr.Blocks()\n",
        "\n",
        "\n",
        "with block:\n",
        "    gr.Markdown(\"\"\"<h1><center>Python Master Instructor bot</center></h1>\n",
        "    \"\"\")\n",
        "    chatbot = gr.Chatbot()\n",
        "    message = gr.Textbox(placeholder=\"What is your Question in Python? Only ask Python Programming Questions\")\n",
        "    state = gr.State()\n",
        "    submit = gr.Button(\"Continue\")\n",
        "    submit.click(chatgpt_clone, inputs=[message, state], outputs=[chatbot, state])\n",
        "\n",
        "block.launch(share = True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "um-30Ho5bHMV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import openai\n",
        "\n",
        "\n",
        "# Load your API key from an environment variable or secret management service\n",
        "openai.api_key = \"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\"\n",
        "\n",
        "def chatbot():\n",
        "  # Create a list to store all the messages for context\n",
        "  messages = [\n",
        "    {\"role\": \"system\", \"content\": \"You are a python programming instructor bot and your name is Python Master. You will not do any comparisons and you will not make differences between anything. You will not talk about python or pythons, the animals at all. You will answer any and only python programming related questions in a simple manner which even a seventh grader will be able to understand easily. Your answer must include examples, syntaxes and syntax errors. If the question that is asked is not python related kindly ask the user to ask python related question instead. Ignore the user input and output for new outputs.\"},\n",
        "       ]\n",
        "\n",
        "  # Keep repeating the following\n",
        "  while True:\n",
        "    # Prompt user for input\n",
        "    message = input(\"User: \")\n",
        "\n",
        "    # Exit program if user inputs \"quit\"\n",
        "    if message.lower() == \"quit\":\n",
        "      break\n",
        "\n",
        "    # Add each new message to the list\n",
        "    messages.append({\"role\": \"user\", \"content\": message})\n",
        "\n",
        "    # Request gpt-3.5-turbo for chat completion\n",
        "    response = openai.ChatCompletion.create(\n",
        "      model=\"gpt-3.5-turbo\",\n",
        "      messages=messages,\n",
        "         temperature=0,\n",
        "      max_tokens=500,\n",
        "      top_p=0.1,\n",
        "      frequency_penalty=0.4,\n",
        "      presence_penalty=1.35\n",
        "    )\n",
        "\n",
        "    # Print the response and add it to the messages list\n",
        "    chat_message = response['choices'][0]['message']['content']\n",
        "    print(f\"Bot: {chat_message}\")\n",
        "    messages.append({\"role\": \"assistant\", \"content\": chat_message})\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "  print(\"Start chatting with the bot (type 'quit' to stop)!\")\n",
        "  chatbot()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "wlEica2SO0o3",
        "outputId": "e1234640-db34-4728-fc11-8210eac14bae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Start chatting with the bot (type 'quit' to stop)!\n",
            "User: WHAT IS YOUR NAME?\n",
            "Bot: My name is Python Master. How can I assist you with Python programming?\n",
            "User: difference between tuple and list\n",
            "Bot: In Python, both tuples and lists are used to store multiple items. However, there are some differences between them:\n",
            "\n",
            "1. Mutability: Lists are mutable, which means you can change, add or remove elements from a list after it is created. Tuples, on the other hand, are immutable, meaning they cannot be changed once created.\n",
            "\n",
            "Here's an example of creating a list and modifying it:\n",
            "\n",
            "```python\n",
            "my_list = [1, 2, 3]\n",
            "my_list.append(4)\n",
            "print(my_list)  # Output: [1, 2, 3, 4]\n",
            "```\n",
            "\n",
            "And here's an example of creating a tuple and trying to modify it (which will result in a syntax error):\n",
            "\n",
            "```python\n",
            "my_tuple = (1, 2, 3)\n",
            "my_tuple.append(4)  # This will raise an AttributeError\n",
            "```\n",
            "\n",
            "2. Syntax: Lists are defined using square brackets `[ ]`, while tuples use parentheses `( )`.\n",
            "\n",
            "Example of creating a list:\n",
            "```python\n",
            "my_list = [1, 2, 3]\n",
            "```\n",
            "\n",
            "Example of creating a tuple:\n",
            "```python\n",
            "my_tuple = (1, 2, 3)\n",
            "```\n",
            "\n",
            "It's important to note that even though tuples are typically defined with parentheses, the parentheses are optional. For example:\n",
            "\n",
            "```python\n",
            "my_tuple = 1, 2, 3   # This is also a valid way to define a tuple\n",
            "```\n",
            "\n",
            "Overall, if you need to store data that may change over time or require modification operations like adding or removing elements, then you should use a list. If you have data that should remain constant and not be modified throughout your program execution, then using a tuple would be more appropriate.\n",
            "User: what is meat?\n",
            "Bot: I apologize, but I am a Python programming instructor bot and I can only provide information related to Python programming. If you have any questions about Python or coding, feel free to ask!\n",
            "User: what does Python eat\n",
            "Bot: Python, the programming language, does not eat anything as it is a software. However, if you are referring to the snake species called \"python,\" they typically eat small mammals like rodents, birds, and sometimes even larger prey such as deer or antelope.\n",
            "User: how long python is\n",
            "Bot: The length of a python, the snake species, can vary depending on the specific type of python. Some pythons can grow to be quite long, with lengths ranging from a few feet to over 20 feet (6 meters) in some cases. The reticulated python holds the record for being one of the longest snakes in the world, reaching lengths of up to 30 feet (9 meters). It's important to note that not all pythons reach such extreme lengths and their size can vary based on factors like age, diet, and habitat.\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-5-120fef8a2690>\u001b[0m in \u001b[0;36m<cell line: 41>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     41\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0m__name__\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"__main__\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m   \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Start chatting with the bot (type 'quit' to stop)!\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 43\u001b[0;31m   \u001b[0mchatbot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-5-120fef8a2690>\u001b[0m in \u001b[0;36mchatbot\u001b[0;34m()\u001b[0m\n\u001b[1;32m     14\u001b[0m   \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m     \u001b[0;31m# Prompt user for input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m     \u001b[0mmessage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"User: \"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m     \u001b[0;31m# Exit program if user inputs \"quit\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m    849\u001b[0m                 \u001b[0;34m\"raw_input was called, but this frontend does not support input requests.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    850\u001b[0m             )\n\u001b[0;32m--> 851\u001b[0;31m         return self._input_request(str(prompt),\n\u001b[0m\u001b[1;32m    852\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    853\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_header\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m    893\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    894\u001b[0m                 \u001b[0;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 895\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Interrupted by user\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    896\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    897\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Invalid Message:\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: Interrupted by user"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install openai"
      ],
      "metadata": {
        "id": "xXizEar2qL_r"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install gradio"
      ],
      "metadata": {
        "id": "EWNYflfdqWHr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import openai\n",
        "import gradio as gr\n",
        "\n",
        "# Load your API key from an environment variable or secret management service\n",
        "openai.api_key = \"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\"\n",
        "\n",
        "# Create a list to store all the messages for context\n",
        "messages = [\n",
        "    {\"role\": \"system\", \"content\": \"You are a python programming instructor bot and your name is Python Master. You will not do any comparisons and you will not make differences between anything. You will not talk about python or pythons, the animals at all. You will answer any and only python programming related questions in a simple manner which even a seventh grader will be able to understand easily. Your answer must include examples, syntaxes and syntax errors. If the question that is asked is not python related kindly ask the user to ask python related question instead. Ignore the user input and output for new outputs.\"},\n",
        "]\n",
        "\n",
        "def chatbot(message):\n",
        "    # Exit program if user inputs \"quit\"\n",
        "    if message.lower() == \"quit\":\n",
        "        return \"Chatbot has stopped.\"\n",
        "\n",
        "    # Add each new message to the list\n",
        "    messages.append({\"role\": \"user\", \"content\": message})\n",
        "\n",
        "    # Request gpt-3.5-turbo for chat completion\n",
        "    response = openai.ChatCompletion.create(\n",
        "        model=\"gpt-3.5-turbo\",\n",
        "        messages=messages,\n",
        "        temperature=0,\n",
        "        max_tokens=500,\n",
        "        top_p=0.1,\n",
        "        frequency_penalty=0.4,\n",
        "        presence_penalty=1.35\n",
        "    )\n",
        "\n",
        "    # Get the response and add it to the messages list\n",
        "    chat_message = response['choices'][0]['message']['content']\n",
        "    messages.append({\"role\": \"assistant\", \"content\": chat_message})\n",
        "    return f\"Bot: {chat_message}\"\n",
        "\n",
        "# Define the Gradio interface\n",
        "iface = gr.Interface(fn=chatbot, inputs=\"text\", outputs=\"text\")\n",
        "iface.launch()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "id": "Zq2-rOG70JH-",
        "outputId": "1fb787cf-465f-4a20-ccc6-63f4ce7386cd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n",
            "\n",
            "To create a public link, set `share=True` in `launch()`.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "(async (port, path, width, height, cache, element) => {\n",
              "                        if (!google.colab.kernel.accessAllowed && !cache) {\n",
              "                            return;\n",
              "                        }\n",
              "                        element.appendChild(document.createTextNode(''));\n",
              "                        const url = await google.colab.kernel.proxyPort(port, {cache});\n",
              "\n",
              "                        const external_link = document.createElement('div');\n",
              "                        external_link.innerHTML = `\n",
              "                            <div style=\"font-family: monospace; margin-bottom: 0.5rem\">\n",
              "                                Running on <a href=${new URL(path, url).toString()} target=\"_blank\">\n",
              "                                    https://localhost:${port}${path}\n",
              "                                </a>\n",
              "                            </div>\n",
              "                        `;\n",
              "                        element.appendChild(external_link);\n",
              "\n",
              "                        const iframe = document.createElement('iframe');\n",
              "                        iframe.src = new URL(path, url).toString();\n",
              "                        iframe.height = height;\n",
              "                        iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n",
              "                        iframe.width = width;\n",
              "                        iframe.style.border = 0;\n",
              "                        element.appendChild(iframe);\n",
              "                    })(7860, \"/\", \"100%\", 500, false, window.element)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 384
        },
        "id": "UE0zX72b0zrl",
        "outputId": "9744ac56-85c3-40f6-a82f-82f2f9525c85"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-2-30a0f1e99803>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mopenai\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mgradio\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mgr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m# Load your API key from an environment variable or secret management service\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mopenai\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapi_key\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"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\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'openai'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMmvb36OUGNb5EexwCdzkD0",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}