[Imersão_IA_2ª_edição]_Código_Aula_04.ipynb

{
  "cells": [
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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rvelascop/Gemini/blob/main/%5BImers%C3%A3o_IA_2%C2%AA_edi%C3%A7%C3%A3o%5D_C%C3%B3digo_Aula_04.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": {
        "colab": {
          "background_save": true
        },
        "id": "nFQLKQ6hfXch"
      },
      "outputs": [],
      "source": [
        "#Instalando o SDK do Google\n",
        "!pip install -q -U google-generativeai"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IthzwfnAfcsi"
      },
      "outputs": [],
      "source": [
        "#Configurações iniciais\n",
        "import google.generativeai as genai\n",
        "\n",
        "GOOGLE_API_KEY=\"INSIRA_SUA_API_KEY\"\n",
        "genai.configure(api_key=GOOGLE_API_KEY)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 139
        },
        "id": "iD3ihugymWBt",
        "outputId": "bcc6314b-9e01-4e7c-fd0e-a86f093b49ae"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "models/gemini-1.0-pro\n",
            "models/gemini-1.0-pro-001\n",
            "models/gemini-1.0-pro-latest\n",
            "models/gemini-1.0-pro-vision-latest\n",
            "models/gemini-1.5-pro-latest\n",
            "models/gemini-pro\n",
            "models/gemini-pro-vision\n"
          ]
        }
      ],
      "source": [
        "#Listando os modelos disponíveis\n",
        "for m in genai.list_models():\n",
        "  if 'generateContent' in m.supported_generation_methods:\n",
        "    print(m.name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "O1ochaeyDn_o"
      },
      "outputs": [],
      "source": [
        "generation_config = {\n",
        "  \"candidate_count\": 1,\n",
        "  \"temperature\": 0.5,\n",
        "}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jwBv7DofDofw"
      },
      "outputs": [],
      "source": [
        "safety_settings={\n",
        "    'HATE': 'BLOCK_NONE',\n",
        "    'HARASSMENT': 'BLOCK_NONE',\n",
        "    'SEXUAL' : 'BLOCK_NONE',\n",
        "    'DANGEROUS' : 'BLOCK_NONE'\n",
        "    }"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NIiSs1R5mVJE"
      },
      "outputs": [],
      "source": [
        "model = genai.GenerativeModel(model_name='gemini-1.0-pro',\n",
        "                                  generation_config=generation_config,\n",
        "                                  safety_settings=safety_settings,)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "vrRjhT2rlrU_",
        "outputId": "608735d9-67fd-4f52-c6e1-20cd4234b703"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'Google'"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "response = model.generate_content(\"Que empresa criou o modelo de IA Gemini?\")\n",
        "response.text"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "KpaQ6hm5f2_J",
        "outputId": "ec22fb60-7f5b-43be-e693-4c906e757ebb"
      },
      "outputs": [
        {
          "ename": "KeyboardInterrupt",
          "evalue": "Interrupted by user",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-9-481ebd21a3b4>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mchat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_chat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\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[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mprompt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Esperando prompt: '\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      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0mprompt\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"fim\"\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;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"
          ]
        }
      ],
      "source": [
        "chat = model.start_chat(history=[])\n",
        "\n",
        "prompt = input('Esperando prompt: ')\n",
        "\n",
        "while prompt != \"fim\":\n",
        "  response = chat.send_message(prompt)\n",
        "  print(\"Resposta:\", response.text, '\\n\\n')\n",
        "  prompt = input('Esperando prompt: ')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XLAniTTDhHNW"
      },
      "outputs": [],
      "source": [
        "chat"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "sd8mvW9KghTf"
      },
      "outputs": [],
      "source": [
        "chat.history"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dAcbPBocgzeX"
      },
      "outputs": [],
      "source": [
        "#Melhorando a visualização\n",
        "#Código disponível em https://ai.google.dev/tutorials/python_quickstart#import_packages\n",
        "import textwrap\n",
        "from IPython.display import display\n",
        "from IPython.display import Markdown\n",
        "\n",
        "def to_markdown(text):\n",
        "  text = text.replace('•', '  *')\n",
        "  return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))\n",
        "\n",
        "#Imprimindo o histórico\n",
        "for message in chat.history:\n",
        "  display(to_markdown(f'**{message.role}**: {message.parts[0].text}'))\n",
        "  print('-------------------------------------------')"
      ]
    }
  ],
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    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
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