BackendFinal.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xbFqPv3QmW7h",
        "outputId": "9cf9bd80-4fdf-4bbd-c50b-d5cb8602b1d0"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting python-multipart\n",
            "  Downloading python_multipart-0.0.9-py3-none-any.whl (22 kB)\n",
            "Installing collected packages: python-multipart\n",
            "Successfully installed python-multipart-0.0.9\n"
          ]
        }
      ],
      "source": [
        "!pip install python-multipart"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JFiM_sunN6jb",
        "outputId": "78ba593e-3142-4234-a63c-be3021852c18"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting langchain\n",
            "  Downloading langchain-0.2.1-py3-none-any.whl (973 kB)\n",
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            "  Downloading langchain_core-0.2.1-py3-none-any.whl (308 kB)\n",
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            "\u001b[?25hCollecting langchain-text-splitters<0.3.0,>=0.2.0 (from langchain)\n",
            "  Downloading langchain_text_splitters-0.2.0-py3-none-any.whl (23 kB)\n",
            "Collecting langsmith<0.2.0,>=0.1.17 (from langchain)\n",
            "  Downloading langsmith-0.1.63-py3-none-any.whl (122 kB)\n",
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            "Collecting jsonpatch<2.0,>=1.33 (from langchain-core<0.3.0,>=0.2.0->langchain)\n",
            "  Downloading jsonpatch-1.33-py2.py3-none-any.whl (12 kB)\n",
            "Collecting packaging<24.0,>=23.2 (from langchain-core<0.3.0,>=0.2.0->langchain)\n",
            "  Downloading packaging-23.2-py3-none-any.whl (53 kB)\n",
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            "\u001b[?25hCollecting orjson<4.0.0,>=3.9.14 (from langsmith<0.2.0,>=0.1.17->langchain)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2024.2.2)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain) (3.0.3)\n",
            "Collecting jsonpointer>=1.9 (from jsonpatch<2.0,>=1.33->langchain-core<0.3.0,>=0.2.0->langchain)\n",
            "  Downloading jsonpointer-2.4-py2.py3-none-any.whl (7.8 kB)\n",
            "Installing collected packages: packaging, orjson, jsonpointer, jsonpatch, langsmith, langchain-core, langchain-text-splitters, langchain\n",
            "  Attempting uninstall: packaging\n",
            "    Found existing installation: packaging 24.0\n",
            "    Uninstalling packaging-24.0:\n",
            "      Successfully uninstalled packaging-24.0\n",
            "Successfully installed jsonpatch-1.33 jsonpointer-2.4 langchain-0.2.1 langchain-core-0.2.1 langchain-text-splitters-0.2.0 langsmith-0.1.63 orjson-3.10.3 packaging-23.2\n"
          ]
        }
      ],
      "source": [
        "!pip install langchain"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zwDiwsNhOB2j",
        "outputId": "a74aed85-91f6-42cd-bca2-f00c2a8a2e87"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.41.0)\n",
            "Collecting datasets\n",
            "  Downloading datasets-2.19.1-py3-none-any.whl (542 kB)\n",
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            "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n",
            "  Downloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
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            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.0.3)\n",
            "Collecting xxhash (from datasets)\n",
            "  Downloading xxhash-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting multiprocess (from datasets)\n",
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            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n",
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            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n",
            "Installing collected packages: xxhash, dill, multiprocess, datasets\n",
            "Successfully installed datasets-2.19.1 dill-0.3.8 multiprocess-0.70.16 xxhash-3.4.1\n"
          ]
        }
      ],
      "source": [
        "!pip install transformers datasets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Um-E5yYnOUxy",
        "outputId": "8df6cc00-cfeb-452f-9845-36e9f40bad13"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting fastapi\n",
            "  Downloading fastapi-0.111.0-py3-none-any.whl (91 kB)\n",
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            "  Downloading httpcore-1.0.5-py3-none-any.whl (77 kB)\n",
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            "Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx>=0.23.0->fastapi)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
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            "Requirement already satisfied: pydantic-core==2.18.2 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi) (2.18.2)\n",
            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn[standard]>=0.12.0->fastapi) (8.1.7)\n",
            "Collecting httptools>=0.5.0 (from uvicorn[standard]>=0.12.0->fastapi)\n",
            "  Downloading httptools-0.6.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (341 kB)\n",
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            "\u001b[?25hCollecting python-dotenv>=0.13 (from uvicorn[standard]>=0.12.0->fastapi)\n",
            "  Downloading python_dotenv-1.0.1-py3-none-any.whl (19 kB)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from uvicorn[standard]>=0.12.0->fastapi) (6.0.1)\n",
            "Collecting uvloop!=0.15.0,!=0.15.1,>=0.14.0 (from uvicorn[standard]>=0.12.0->fastapi)\n",
            "  Downloading uvloop-0.19.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.4 MB)\n",
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            "\u001b[?25hCollecting watchfiles>=0.13 (from uvicorn[standard]>=0.12.0->fastapi)\n",
            "  Downloading watchfiles-0.21.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m62.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting websockets>=10.4 (from uvicorn[standard]>=0.12.0->fastapi)\n",
            "  Downloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m20.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio->httpx>=0.23.0->fastapi) (1.2.1)\n",
            "Collecting shellingham>=1.3.0 (from typer>=0.12.3->fastapi-cli>=0.0.2->fastapi)\n",
            "  Downloading shellingham-1.5.4-py2.py3-none-any.whl (9.8 kB)\n",
            "Requirement already satisfied: rich>=10.11.0 in /usr/local/lib/python3.10/dist-packages (from typer>=0.12.3->fastapi-cli>=0.0.2->fastapi) (13.7.1)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer>=0.12.3->fastapi-cli>=0.0.2->fastapi) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer>=0.12.3->fastapi-cli>=0.0.2->fastapi) (2.16.1)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer>=0.12.3->fastapi-cli>=0.0.2->fastapi) (0.1.2)\n",
            "Installing collected packages: websockets, uvloop, ujson, shellingham, python-dotenv, httptools, h11, dnspython, watchfiles, uvicorn, starlette, httpcore, email_validator, typer, httpx, fastapi-cli, fastapi\n",
            "  Attempting uninstall: typer\n",
            "    Found existing installation: typer 0.9.4\n",
            "    Uninstalling typer-0.9.4:\n",
            "      Successfully uninstalled typer-0.9.4\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",
            "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n",
            "weasel 0.3.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed dnspython-2.6.1 email_validator-2.1.1 fastapi-0.111.0 fastapi-cli-0.0.4 h11-0.14.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 python-dotenv-1.0.1 shellingham-1.5.4 starlette-0.37.2 typer-0.12.3 ujson-5.10.0 uvicorn-0.29.0 uvloop-0.19.0 watchfiles-0.21.0 websockets-12.0\n"
          ]
        }
      ],
      "source": [
        "!pip install fastapi"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H2ulRhSPOdYQ",
        "outputId": "8424be50-a439-44af-db77-cf7957bebd55"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: uvicorn in /usr/local/lib/python3.10/dist-packages (0.29.0)\n",
            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (8.1.7)\n",
            "Requirement already satisfied: h11>=0.8 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (0.14.0)\n",
            "Requirement already satisfied: typing-extensions>=4.0 in /usr/local/lib/python3.10/dist-packages (from uvicorn) (4.11.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install uvicorn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WpT9pUYfe6u2",
        "outputId": "638c067b-3f68-4d44-f093-8c1e7a27fc89"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            ">>> Downloading ollama...\n",
            "############################################################################################# 100.0%\n",
            ">>> Installing ollama to /usr/local/bin...\n",
            ">>> Creating ollama user...\n",
            ">>> Adding ollama user to video group...\n",
            ">>> Adding current user to ollama group...\n",
            ">>> Creating ollama systemd service...\n",
            "WARNING: Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies.\n",
            ">>> The Ollama API is now available at 127.0.0.1:11434.\n",
            ">>> Install complete. Run \"ollama\" from the command line.\n"
          ]
        }
      ],
      "source": [
        "!curl -fsSL https://ollama.com/install.sh | sh"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bwMH_n5kfDXM",
        "outputId": "3c83f92c-430a-40d4-f6ba-db5792d91136"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Popen: returncode: None args: 'ollama run llava:v1.6'>"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import subprocess\n",
        "subprocess.Popen(\"ollama serve\",shell=True)\n",
        "subprocess.Popen(\"ollama run llava:v1.6\",shell=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ad_mYbVSfxc_",
        "outputId": "71c85aa8-bffc-43de-aea5-46d605c007ff"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Popen: returncode: None args: 'ollama pull llava:v1.6'>"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "subprocess.Popen(\"ollama pull llava:v1.6\", shell=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KV6pCX6KRSCA",
        "outputId": "c47460a7-d061-4c1e-bffb-e323c1c73001"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting langchain-community\n",
            "  Downloading langchain_community-0.2.1-py3-none-any.whl (2.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.1/2.1 MB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: PyYAML>=5.3 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (6.0.1)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (2.0.30)\n",
            "Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (3.9.5)\n",
            "Collecting dataclasses-json<0.7,>=0.5.7 (from langchain-community)\n",
            "  Downloading dataclasses_json-0.6.6-py3-none-any.whl (28 kB)\n",
            "Requirement already satisfied: langchain<0.3.0,>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (0.2.1)\n",
            "Requirement already satisfied: langchain-core<0.3.0,>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (0.2.1)\n",
            "Requirement already satisfied: langsmith<0.2.0,>=0.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (0.1.63)\n",
            "Requirement already satisfied: numpy<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (1.25.2)\n",
            "Requirement already satisfied: requests<3,>=2 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (2.31.0)\n",
            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain-community) (8.3.0)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (1.3.1)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (23.2.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (1.4.1)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (6.0.5)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (1.9.4)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain-community) (4.0.3)\n",
            "Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses-json<0.7,>=0.5.7->langchain-community)\n",
            "  Downloading marshmallow-3.21.2-py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.3/49.3 kB\u001b[0m \u001b[31m87.9 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting typing-inspect<1,>=0.4.0 (from dataclasses-json<0.7,>=0.5.7->langchain-community)\n",
            "  Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)\n",
            "Requirement already satisfied: langchain-text-splitters<0.3.0,>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from langchain<0.3.0,>=0.2.0->langchain-community) (0.2.0)\n",
            "Requirement already satisfied: pydantic<3,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain<0.3.0,>=0.2.0->langchain-community) (2.7.1)\n",
            "Requirement already satisfied: jsonpatch<2.0,>=1.33 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.3.0,>=0.2.0->langchain-community) (1.33)\n",
            "Requirement already satisfied: packaging<24.0,>=23.2 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.3.0,>=0.2.0->langchain-community) (23.2)\n",
            "Requirement already satisfied: orjson<4.0.0,>=3.9.14 in /usr/local/lib/python3.10/dist-packages (from langsmith<0.2.0,>=0.1.0->langchain-community) (3.10.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain-community) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain-community) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain-community) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain-community) (2024.2.2)\n",
            "Requirement already satisfied: typing-extensions>=4.6.0 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain-community) (4.11.0)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain-community) (3.0.3)\n",
            "Requirement already satisfied: jsonpointer>=1.9 in /usr/local/lib/python3.10/dist-packages (from jsonpatch<2.0,>=1.33->langchain-core<0.3.0,>=0.2.0->langchain-community) (2.4)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain<0.3.0,>=0.2.0->langchain-community) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.18.2 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain<0.3.0,>=0.2.0->langchain-community) (2.18.2)\n",
            "Collecting mypy-extensions>=0.3.0 (from typing-inspect<1,>=0.4.0->dataclasses-json<0.7,>=0.5.7->langchain-community)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Installing collected packages: mypy-extensions, marshmallow, typing-inspect, dataclasses-json, langchain-community\n",
            "Successfully installed dataclasses-json-0.6.6 langchain-community-0.2.1 marshmallow-3.21.2 mypy-extensions-1.0.0 typing-inspect-0.9.0\n"
          ]
        }
      ],
      "source": [
        "!pip install langchain-community"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "56-vB8IfNC47",
        "outputId": "daef0aa0-74f3-40c5-b96e-a568a9f25343"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: 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"
          ]
        }
      ],
      "source": [
        "from langchain_community.llms import Ollama\n",
        "import base64\n",
        "from typing import Dict\n",
        "from fastapi.middleware.cors import CORSMiddleware\n",
        "import uvicorn\n",
        "from fastapi import FastAPI , HTTPException\n",
        "from fastapi.responses import RedirectResponse\n",
        "from langchain_community.chat_models import ChatOllama\n",
        "from langchain_core.output_parsers import StrOutputParser\n",
        "import requests\n",
        "import torch\n",
        "from PIL import Image\n",
        "from transformers import *\n",
        "from tqdm import tqdm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jwP_HahJj_Yw",
        "outputId": "4b39521d-db27-44ae-8ca1-c69d3b03c844"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<Popen: returncode: None args: 'ollama run llava:v1.6'>"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "subprocess.Popen(\"ollama serve\", shell=True)\n",
        "subprocess.Popen(\"ollama run llava:v1.6\", shell=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ddO8oWQTHW7o",
        "outputId": "ec6aece6-30f4-4288-eab4-6d578c0ee540"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/langchain_core/_api/deprecation.py:119: LangChainDeprecationWarning: The method `BaseLLM.__call__` was deprecated in langchain-core 0.1.7 and will be removed in 0.3.0. Use invoke instead.\n",
            "  warn_deprecated(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " Hello! How can I help you today? \n"
          ]
        }
      ],
      "source": [
        "import time\n",
        "time.sleep(100)\n",
        "llava = Ollama(model=\"llava:v1.6\")\n",
        "print(llava(\"Hi\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "o-NWj-M4E4MZ"
      },
      "outputs": [],
      "source": [
        "app = FastAPI()\n",
        "origins = ['*']\n",
        "\n",
        "app.add_middleware(\n",
        "    CORSMiddleware,\n",
        "    allow_origins=origins,\n",
        "    allow_credentials=True,\n",
        "    allow_methods=[\"*\"],\n",
        "    allow_headers=[\"*\"],\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "l9QRluO1kD0m"
      },
      "outputs": [],
      "source": [
        "import urllib.parse as parse\n",
        "import requests\n",
        "\n",
        "@app.get(\"/\")\n",
        "async def redirect_root_to_docs():\n",
        "    return RedirectResponse(\"/docs\")\n",
        "\n",
        "def image_to_base64(image_path):\n",
        "    if image_path.startswith('http://') or image_path.startswith('https://'):\n",
        "        response = requests.get(image_path)\n",
        "        if response.status_code == 200:\n",
        "            encoded_string = base64.b64encode(response.content)\n",
        "            return encoded_string.decode(\"utf-8\")\n",
        "        else:\n",
        "            print(\"Failed to fetch image from URL:\", image_path)\n",
        "            return None\n",
        "    else:\n",
        "        with open(image_path, \"rb\") as image_file:\n",
        "            encoded_string = base64.b64encode(image_file.read())\n",
        "            return encoded_string.decode(\"utf-8\")\n",
        "\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "\n",
        "  # a function to determine whether a string is a URL or not\n",
        "def is_url(string):\n",
        "    try:\n",
        "        result = parse.urlparse(string)\n",
        "        return all([result.scheme, result.netloc, result.path])\n",
        "    except:\n",
        "        return False\n",
        "\n",
        "# a function to load an image\n",
        "def load_image(image_path):\n",
        "    if is_url(image_path):\n",
        "        return Image.open(requests.get(image_path, stream=True).raw)\n",
        "    elif os.path.exists(image_path):\n",
        "        return Image.open(image_path)\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7imz46IqMxPH"
      },
      "outputs": [],
      "source": [
        "from fastapi import UploadFile,File\n",
        "@app.post(\"/caption1\")\n",
        "async def UploadImage(file: bytes = File(...)):\n",
        "  with open('image.jpg','wb') as image:\n",
        "    image.write(file)\n",
        "    image.close()\n",
        "  title = llava(prompt=\"If the provided image is clear and of good quality, generate a vivid, engaging title that captures the essence of the image. The title should be short and to the point, giving a general view of the main scene depicted without mentioning quantities or numbers. Focus on providing an impactful description of the primary subject or action in the image. However, if the image is blurred, distorted, or of poor quality, respond by saying 'The image quality is too low to generate an accurate title.\",images=[str(image_to_base64(str(\"/content/image.jpg\")))])\n",
        "  return {\"title\":title}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "drhpgC7eYx1p"
      },
      "outputs": [],
      "source": [
        "\n",
        "import requests\n",
        "import json\n",
        "from fastapi import UploadFile,File\n",
        "\n",
        "@app.post(\"/caption\")\n",
        "async def UploadImage(file: bytes = File(...)):\n",
        "  with open('image.jpg','wb') as image:\n",
        "    image.write(file)\n",
        "    image.close()\n",
        "\n",
        "  params = {\n",
        "    'models': 'quality',\n",
        "    'api_user': '1276533234',\n",
        "    'api_secret': 'fLqocaoDSMvC7BvwdFZbeJbfmq3KP4Gk'\n",
        "  }\n",
        "\n",
        "  files = {'media': open('/content/image.jpg', 'rb')}\n",
        "  r = requests.post('https://api.sightengine.com/1.0/check.json', files=files, data=params)\n",
        "\n",
        "  score = json.loads(r.text)['quality']['score']\n",
        "  print(score)\n",
        "  if score <= 0.45:\n",
        "    return {\"title\":\"Quality issues are too severe to recognize visual content.\"}\n",
        "\n",
        "  title = llava(prompt=\"Generate a vivid, engaging title that captures the essence of the provided image. The title should be short and to the point that give a general view of the image. Do not mention quantities or numbers. Focus on providing an impactful description of the main scene depicted.\",images=[str(image_to_base64(str(\"/content/image.jpg\")))])\n",
        "  return {\"title\":title}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GWke9X3tKLkv"
      },
      "outputs": [],
      "source": [
        "@app.post(\"/chat\")\n",
        "async def Chat(prompt:str,file: bytes = File(...)):\n",
        "  with open('image.jpg','wb') as image:\n",
        "    image.write(file)\n",
        "    image.close()\n",
        "  RES = llava(prompt=prompt,images=[str(image_to_base64(str(\"/content/image.jpg\")))]  )\n",
        "  return {\"content\":RES}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1zxa26AqJe3X"
      },
      "outputs": [],
      "source": [
        "from huggingface_hub import login\n",
        "import os\n",
        "os.environ[\"HF_TOKEN\"] = \"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\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AWMcYpSCNx7O"
      },
      "outputs": [],
      "source": [
        "\n",
        "# \"\"\"# Using a Trained Model\"\"\"\n",
        "\n",
        "# model = VisionEncoderDecoderModel.from_pretrained(\"Stormbreakerr20/vit-gpt2-vizwiz\").to(device)\n",
        "# tokenizer = GPT2TokenizerFast.from_pretrained(\"Stormbreakerr20/vit-gpt2-vizwiz\")\n",
        "# image_processor = ViTImageProcessor.from_pretrained(\"Stormbreakerr20/vit-gpt2-vizwiz\")\n",
        "# torch.save(model.state_dict(), \"model.pth\")\n",
        "# a function to perform inference\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "o5Mu-e7rKfM_"
      },
      "outputs": [],
      "source": [
        "# @app.post(\"/captions\")\n",
        "# def UploadImage(file: bytes = File(...)):\n",
        "#     with open('image.jpg','wb') as image:\n",
        "#       image.write(file)\n",
        "#       image.close()\n",
        "\n",
        "#     params = {\n",
        "#     'models': 'quality',\n",
        "#     'api_user': '1276533234',\n",
        "#     'api_secret': 'fLqocaoDSMvC7BvwdFZbeJbfmq3KP4Gk'\n",
        "#     }\n",
        "#     files = {'media': open('/content/image.jpg', 'rb')}\n",
        "#     r = requests.post('https://api.sightengine.com/1.0/check.json', files=files, data=params)\n",
        "\n",
        "#     score = json.loads(r.text)['quality']['score']\n",
        "#     print(score)\n",
        "#     if score <= 0.45:\n",
        "#       return {\"title\":\"Quality issues are too severe to recognize visual content.\"}\n",
        "\n",
        "#     image = Image.open('/content/image.jpg')\n",
        "#     img = image_processor(image, return_tensors=\"pt\").to(device)\n",
        "#     model.to(device)\n",
        "#     with torch.no_grad():\n",
        "#         output = model.generate(**img)\n",
        "#     caption = tokenizer.batch_decode(output, skip_special_tokens=True)[0]\n",
        "\n",
        "\n",
        "#     title = llava(prompt=f\"here is the summary of the image provided: {caption}, Based on the given summary and image analyse both of these and Generate a vivid, engaging title that captures the essence of the provided image. The title should be short and to the point that give a general view of the image.\",images=[str(image_to_base64(str(\"/content/image.jpg\")))])\n",
        "#     return {\"title\":title}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g_xyX1ocb4Fk",
        "outputId": "6cb8c64c-423f-4dd5-85b3-1d643a3df538"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting pyngrok\n",
            "  Downloading pyngrok-7.1.6-py3-none-any.whl (22 kB)\n",
            "Requirement already satisfied: PyYAML>=5.1 in /usr/local/lib/python3.10/dist-packages (from pyngrok) (6.0.1)\n",
            "Installing collected packages: pyngrok\n",
            "Successfully installed pyngrok-7.1.6\n"
          ]
        }
      ],
      "source": [
        "!pip install pyngrok"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lbfqLl4mb5-Y"
      },
      "outputs": [],
      "source": [
        "import nest_asyncio\n",
        "from pyngrok import ngrok\n",
        "import uvicorn\n",
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/"
        },
        "id": "tLt7hwzoPJ6V",
        "outputId": "aaa77906-ed8b-4818-a2b1-6021bab1debc"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "INFO:     Started server process [399]\n",
            "INFO:     Waiting for application startup.\n",
            "INFO:     Application startup complete.\n",
            "INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Public URL: NgrokTunnel: \"https://2368-34-28-27-77.ngrok-free.app\" -> \"http://localhost:8000\"\n"
          ]
        }
      ],
      "source": [
        "# Get your authtoken from https://dashboard.ngrok.com/get-started/your-authtoken\n",
        "os.system(f\"ngrok authtoken 2fX4X2BATxalJmNiCutMXV1qR6k_4RXntzTaGfFuGwYpRuKcE\")\n",
        "\n",
        "# Connect to ngrok\n",
        "connection_string = ngrok.connect(8000,bind_tls = True)\n",
        "\n",
        "# Print the public URL\n",
        "print('Public URL:', connection_string)\n",
        "nest_asyncio.apply()\n",
        "uvicorn.run(app,port = 8000,reload = False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dWXzwH63bHR7"
      },
      "outputs": [],
      "source": [
        "ngrok.disconnect(public_url = connection_string)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "C3QFu-1tIUqT"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "gpuType": "T4",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}