Devika_Running_on_Colab

{
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/FunkusBangru/Access-Of-Devika-Ai-Using-Colab/blob/main/Devika_Running_on_Colab\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Welcome to Devika Setup Guide!\n",
        "\n",
        "This notebook will guide you through setting up Devika, an AI software engineer, on your system.\n",
        "\n",
        "Please follow each step carefully.\n",
        "\n",
        "Step 1: Installing Required Packages\n",
        "We'll start by installing the necessary packages for Devika."
      ],
      "metadata": {
        "id": "m6uwTqL8zjyr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install playwright uv"
      ],
      "metadata": {
        "id": "BgP_RgPwzloF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 2: Cloning Devika Repository\n",
        "Next, we'll clone the Devika repository from GitHub."
      ],
      "metadata": {
        "id": "59YIrinEzqFD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/stitionai/devika.git %cd devika"
      ],
      "metadata": {
        "id": "M4osJGKyzxGe"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 3: Installing Dependencies\n",
        "Now, let's install all the required dependencies for Devika"
      ],
      "metadata": {
        "id": "ZGRG2vo40D8x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r requirements.txt !playwright install --with-deps"
      ],
      "metadata": {
        "id": "Xr4ZGeM40HlO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 4: Configuring Devika\n",
        "We need to set up some configurations for Devika, including API keys and model settings."
      ],
      "metadata": {
        "id": "G_gkuJZ80LdH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Replace the placeholders with your actual API keys and endpoints\n",
        "\n",
        "Replace placeholder values with actual API endpoints and keys. Adjust parameters like 'MODEL_NAME' if needed. Save changes. Follow instructions provided by Devika for setup or configuration."
      ],
      "metadata": {
        "id": "TBWPPQDp0SeU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Set up Devika configurations\n",
        "configurations = {\n",
        "    'ENDPOINT_OΡΕΝΑΙ': 'YOUR_OΡΕΝΑΙ_ENDPOINT',\n",
        "    'OPENAI_ENDPOINT': 'YOUR_OPENAI_ENDPOINT',\n",
        "    'ΟΡΕΝΑΙ_ΑΡΙ_ΚΕΥ': 'YOUR_OΡΕΝΑΙ_API_KEY',\n",
        "    'CLAUDE_API_KEY': 'YOUR_CLAUDE_API_KEY',\n",
        "    'BING_API_KEY': 'YOUR_BING_API_KEY',\n",
        "    'AZURE_API_KEY': 'YOUR_AZURE_API_KEY',\n",
        "    'AZURE_ENDPOINT': 'YOUR_AZURE_ENDPOINT',\n",
        "    'OPENROUTER_API_KEY': 'YOUR_OPENROUTER_API_KEY',\n",
        "    'MODEL_NAME': 'gpt-3.5-turbo',\n",
        "    'MAX_TOKENS': 8192,\n",
        "    # Remove token values and gpt-pilot\n",
        "}\n",
        "\n",
        "# Write configurations to config.toml\n",
        "with open('config.toml', 'a') as f:\n",
        "    f.write('\\n')  # Add a new line before appending configurations\n",
        "    for key, value in configurations.items():\n",
        "        if isinstance(value, str):\n",
        "            f.write(f'{key} = \"{value}\"\\n')\n",
        "        else:\n",
        "            f.write(f'{key} = {value}\\n')"
      ],
      "metadata": {
        "id": "3i-6zp3n1LU_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 5: Starting Devika Server\n",
        "\n",
        "We'll now start the Devika server"
      ],
      "metadata": {
        "id": "gxFQXaFA1Txu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "import subprocess\n",
        "\n",
        "# Start Devika server\n",
        "devika_server_process = subprocess.Popen(['python', 'devika.py'])"
      ],
      "metadata": {
        "id": "Llb3sxrj2hpV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Step 6: Running UI Server with Improved Interface\n",
        "Finally, we'll run the UI server with the improved user interface."
      ],
      "metadata": {
        "id": "ce5ruu1F2s7m"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd ui\n",
        "!bun install\n",
        "!bun run dev"
      ],
      "metadata": {
        "id": "fCtWTC7Q2-3i"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
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    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": [],
      "authorship_tag": "ABX9TyO4fXSxWIJPkRMDABrrpyTg",
      "include_colab_link": true
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    "kernelspec": {
      "display_name": "Python 3",
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