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            "Collecting langchain-together\n",
            "  Downloading langchain_together-0.1.2-py3-none-any.whl (9.5 kB)\n",
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            "Collecting httpx<1,>=0.23.0 (from openai<2.0.0,>=1.26.0->langchain-openai<0.2.0,>=0.1.3->langchain-together)\n",
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            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken<1,>=0.7->langchain-openai<0.2.0,>=0.1.3->langchain-together) (2024.5.15)\n",
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            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai<2.0.0,>=1.26.0->langchain-openai<0.2.0,>=0.1.3->langchain-together)\n",
            "  Downloading httpcore-1.0.5-py3-none-any.whl (77 kB)\n",
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            "\u001b[?25hCollecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai<2.0.0,>=1.26.0->langchain-openai<0.2.0,>=0.1.3->langchain-together)\n",
            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: packaging, orjson, jsonpointer, h11, tiktoken, jsonpatch, httpcore, langsmith, httpx, openai, langchain-core, langchain-openai, langchain-together\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 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 jsonpatch-1.33 jsonpointer-2.4 langchain-core-0.2.3 langchain-openai-0.1.8 langchain-together-0.1.2 langsmith-0.1.65 openai-1.30.5 orjson-3.10.3 packaging-23.2 tiktoken-0.7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain_together.embeddings import TogetherEmbeddings\n",
        "Together_key = \"bf2664603dc659dc6f4c81c3ebee8edab35340390f39f8af6c450a2457214a5b\"\n",
        "embeddings = TogetherEmbeddings(model=\"togethercomputer/m2-bert-80M-8k-retrieval\", api_key=Together_key)\n",
        "index_name = \"mammogram-index\""
      ],
      "metadata": {
        "id": "zxTqVl5bVCVJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install langchain-pinecone"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ViX4UplRVFwr",
        "outputId": "304f2063-47aa-4acc-c2dd-e2f5f9ec5114",
        "collapsed": true
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting langchain-pinecone\n",
            "  Downloading langchain_pinecone-0.1.1-py3-none-any.whl (8.4 kB)\n",
            "Requirement already satisfied: langchain-core<0.3,>=0.1.52 in /usr/local/lib/python3.10/dist-packages (from langchain-pinecone) (0.2.3)\n",
            "Requirement already satisfied: numpy<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain-pinecone) (1.25.2)\n",
            "Collecting pinecone-client<4.0.0,>=3.2.2 (from langchain-pinecone)\n",
            "  Downloading pinecone_client-3.2.2-py3-none-any.whl (215 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m215.9/215.9 kB\u001b[0m \u001b[31m1.5 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-core<0.3,>=0.1.52->langchain-pinecone) (6.0.1)\n",
            "Requirement already satisfied: jsonpatch<2.0,>=1.33 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.3,>=0.1.52->langchain-pinecone) (1.33)\n",
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            "Requirement already satisfied: pydantic<3,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.3,>=0.1.52->langchain-pinecone) (2.7.1)\n",
            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain-core<0.3,>=0.1.52->langchain-pinecone) (8.3.0)\n",
            "Requirement already satisfied: certifi>=2019.11.17 in /usr/local/lib/python3.10/dist-packages (from pinecone-client<4.0.0,>=3.2.2->langchain-pinecone) (2024.2.2)\n",
            "Requirement already satisfied: tqdm>=4.64.1 in /usr/local/lib/python3.10/dist-packages (from pinecone-client<4.0.0,>=3.2.2->langchain-pinecone) (4.66.4)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4 in /usr/local/lib/python3.10/dist-packages (from pinecone-client<4.0.0,>=3.2.2->langchain-pinecone) (4.11.0)\n",
            "Requirement already satisfied: urllib3>=1.26.0 in /usr/local/lib/python3.10/dist-packages (from pinecone-client<4.0.0,>=3.2.2->langchain-pinecone) (2.0.7)\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,>=0.1.52->langchain-pinecone) (2.4)\n",
            "Requirement already satisfied: orjson<4.0.0,>=3.9.14 in /usr/local/lib/python3.10/dist-packages (from langsmith<0.2.0,>=0.1.65->langchain-core<0.3,>=0.1.52->langchain-pinecone) (3.10.3)\n",
            "Requirement already satisfied: requests<3,>=2 in /usr/local/lib/python3.10/dist-packages (from langsmith<0.2.0,>=0.1.65->langchain-core<0.3,>=0.1.52->langchain-pinecone) (2.31.0)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1->langchain-core<0.3,>=0.1.52->langchain-pinecone) (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-core<0.3,>=0.1.52->langchain-pinecone) (2.18.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langsmith<0.2.0,>=0.1.65->langchain-core<0.3,>=0.1.52->langchain-pinecone) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langsmith<0.2.0,>=0.1.65->langchain-core<0.3,>=0.1.52->langchain-pinecone) (3.7)\n",
            "Installing collected packages: pinecone-client, langchain-pinecone\n",
            "Successfully installed langchain-pinecone-0.1.1 pinecone-client-3.2.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pinecone import Pinecone\n",
        "from langchain_pinecone import PineconeVectorStore\n",
        "import os"
      ],
      "metadata": {
        "id": "YXEnnuiBriF8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# initialize connection to pinecone (get API key at app.pinecone.io)\n",
        "api_key = \"88e446de-82c0-4c76-b9c9-5fb56662f003\"\n",
        "os.environ['PINECONE_API_KEY'] = api_key\n",
        "\n",
        "# configure client\n",
        "pc = Pinecone(api_key=api_key)\n",
        "index = pc.Index(\"mammogram-index\")\n",
        "docsearch = PineconeVectorStore.from_existing_index(index_name, embeddings)"
      ],
      "metadata": {
        "id": "888V5dUwjvIP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "index.describe_index_stats()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O4tV8IzKkbwx",
        "outputId": "9e4db1a1-94a6-4a26-d01c-a4968709c413"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'dimension': 768,\n",
              " 'index_fullness': 0.0,\n",
              " 'namespaces': {'': {'vector_count': 1062}},\n",
              " 'total_vector_count': 1062}"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Based on the image, answer this query .\n",
        "# Query:\n",
        "# Here is some context 1:\n",
        "#"
      ],
      "metadata": {
        "id": "V3oNa7CceFaM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "query = \"Is dairy (milk) linked to a higher risk of breast cancer? \"\n",
        "docs = docsearch.similarity_search(query, k=2)\n",
        "for doc in docs:\n",
        "    print(str(doc.metadata[\"page\"]) + \":\", doc.page_content[:300])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Szrw5hw1VLRP",
        "outputId": "9f411128-d171-4a4a-a4bd-a1bc3d9d46a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "410.0: Unlike conventional hormone therapy (277) neither\n",
            "soyfoods nor isoflavones increase breast tissue density\n",
            "(39,40,225), and four studies have found that isoflavonesdo not affect breast cell proliferation; these studies wereconducted in healthy pre- (217) and postmenopausal (219)women and breast cance\n",
            "389.0: intraclass correlation was 0.6 (Zeleniuch-Jacquotte et al.,\n",
            "1998). However, in prospective studies we deal with muchlonger periods of time.\n",
            "As previously indicated an explanation for these con-\n",
            "troversial results may be confounding because of wine andtea. Intake of coffee and fruit juice (Horner et \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fullquery = f\"This is the input string: {query} \\n This is context 1: {docs[0].page_content[:300]} \\n This is context 2: {docs[1].page_content[:300]}\""
      ],
      "metadata": {
        "id": "UvP6q98aBSya"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fullquery"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "id": "QJHXcvkJd5m6",
        "outputId": "8181926c-f4cd-4226-d933-0dffe021969e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'This is the input string: Is dairy (milk) linked to a higher risk of breast cancer?  \\n This is context 1: Unlike conventional hormone therapy (277) neither\\nsoyfoods nor isoflavones increase breast tissue density\\n(39,40,225), and four studies have found that isoflavonesdo not affect breast cell proliferation; these studies wereconducted in healthy pre- (217) and postmenopausal (219)women and breast cance \\n This is context 2: intraclass correlation was 0.6 (Zeleniuch-Jacquotte et al.,\\n1998). However, in prospective studies we deal with muchlonger periods of time.\\nAs previously indicated an explanation for these con-\\ntroversial results may be confounding because of wine andtea. Intake of coffee and fruit juice (Horner et '"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install open-flamingo"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0EHkgpuMAomB",
        "outputId": "3350a556-cfba-4b50-e904-338fa8eb5612"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting open-flamingo\n",
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            "\u001b[?25hCollecting einops (from open-flamingo)\n",
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            "\u001b[?25hCollecting einops-exts (from open-flamingo)\n",
            "  Downloading einops_exts-0.0.4-py3-none-any.whl (3.9 kB)\n",
            "Requirement already satisfied: transformers>=4.28.1 in /usr/local/lib/python3.10/dist-packages (from open-flamingo) (4.41.1)\n",
            "Collecting torch==2.0.1 (from open-flamingo)\n",
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            "Collecting open-clip-torch>=2.16.0 (from open-flamingo)\n",
            "  Downloading open_clip_torch-2.24.0-py3-none-any.whl (1.5 MB)\n",
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            "\u001b[?25hCollecting sentencepiece==0.1.98 (from open-flamingo)\n",
            "  Downloading sentencepiece-0.1.98-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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            "Collecting nvidia-cuda-nvrtc-cu11==11.7.99 (from torch==2.0.1->open-flamingo)\n",
            "  Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)\n",
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            "\u001b[?25hInstalling collected packages: sentencepiece, lit, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, ftfy, einops, nvidia-cusolver-cu11, nvidia-cudnn-cu11, einops-exts, triton, torch, torchvision, timm, open-clip-torch, open-flamingo\n",
            "  Attempting uninstall: sentencepiece\n",
            "    Found existing installation: sentencepiece 0.1.99\n",
            "    Uninstalling sentencepiece-0.1.99:\n",
            "      Successfully uninstalled sentencepiece-0.1.99\n",
            "  Attempting uninstall: triton\n",
            "    Found existing installation: triton 2.3.0\n",
            "    Uninstalling triton-2.3.0:\n",
            "      Successfully uninstalled triton-2.3.0\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 2.3.0+cu121\n",
            "    Uninstalling torch-2.3.0+cu121:\n",
            "      Successfully uninstalled torch-2.3.0+cu121\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.18.0+cu121\n",
            "    Uninstalling torchvision-0.18.0+cu121:\n",
            "      Successfully uninstalled torchvision-0.18.0+cu121\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",
            "torchaudio 2.3.0+cu121 requires torch==2.3.0, but you have torch 2.0.1 which is incompatible.\n",
            "torchtext 0.18.0 requires torch>=2.3.0, but you have torch 2.0.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed einops-0.8.0 einops-exts-0.0.4 ftfy-6.2.0 lit-18.1.6 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 open-clip-torch-2.24.0 open-flamingo-2.0.1 sentencepiece-0.1.98 timm-1.0.3 torch-2.0.1 torchvision-0.15.2 triton-2.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from open_flamingo import create_model_and_transforms\n",
        "\n",
        "model, image_processor, tokenizer = create_model_and_transforms(\n",
        "    clip_vision_encoder_path=\"ViT-L-14\",\n",
        "    clip_vision_encoder_pretrained=\"openai\",\n",
        "    lang_encoder_path=\"anas-awadalla/mpt-1b-redpajama-200b\",\n",
        "    tokenizer_path=\"anas-awadalla/mpt-1b-redpajama-200b\",\n",
        "    cross_attn_every_n_layers=1,\n",
        "    cache_dir=\"PATH/TO/CACHE/DIR\"  # Defaults to ~/.cache\n",
        ")\n",
        "from huggingface_hub import hf_hub_download\n",
        "import torch\n",
        "\n",
        "checkpoint_path = hf_hub_download(\"openflamingo/OpenFlamingo-3B-vitl-mpt1b\", \"checkpoint.pt\")\n",
        "model.load_state_dict(torch.load(checkpoint_path), strict=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 997,
          "referenced_widgets": [
            "8747a8abf28446db85c1d1bc3fd0c264",
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        },
        "id": "S11aPyoVAvy9",
        "outputId": "251f3011-7b0f-4d3e-ddd0-904d034922a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|███████████████████████████████████████| 933M/933M [00:09<00:00, 94.8MiB/s]\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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8747a8abf28446db85c1d1bc3fd0c264"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bc7402764d9645bfa0bbf68339f8908b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "83bdd5eafac54d3f97a412feee135f2f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- configuration_mosaic_gpt.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d4e6b175682a4a728e2faffd8004bdaf"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bebe92519e9e42bea90966945ecfefb4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- low_precision_layernorm.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0429163a57274b87b12e2a23ed8fe32b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "073e20a62cda490ba42c19d9d20a3c1f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- attention.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- gpt_blocks.py\n",
            "- attention.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "param_init_fns.py:   0%|          | 0.00/15.9k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4ccc8dae325e44f1b0aa47b887790b58"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- param_init_fns.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
            "A new version of the following files was downloaded from https://huggingface.co/anas-awadalla/mpt-1b-redpajama-200b:\n",
            "- mosaic_gpt.py\n",
            "- low_precision_layernorm.py\n",
            "- gpt_blocks.py\n",
            "- param_init_fns.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/5.25G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bd9599c471c04e1fa24f2e734dff75eb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
            "  return self.fget.__get__(instance, owner)()\n",
            "/root/.cache/huggingface/modules/transformers_modules/anas-awadalla/mpt-1b-redpajama-200b/50d6bc94e17812873f39c36c5f815263fa71fb80/attention.py:289: UserWarning: Using `attn_impl: torch`. If your model does not use `alibi` or `prefix_lm` we recommend using `attn_impl: flash` otherwise we recommend using `attn_impl: triton`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "You are using config.init_device='cpu', but you can also use config.init_device=\"meta\" with Composer + FSDP for fast initialization.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tokenizer.padding_side = \"left\" # For generation padding tokens should be on the left\n",
        "lang_x = tokenizer(\n",
        "    [fullquery],\n",
        "    return_tensors=\"pt\",\n",
        ")\n",
        "\n",
        "\n",
        "\"\"\"\n",
        "Step 4: Generate text\n",
        "\"\"\"\n",
        "generated_text = model.generate(\n",
        "    vision_x=vision_x,\n",
        "    lang_x=lang_x[\"input_ids\"],\n",
        "    attention_mask=lang_x[\"attention_mask\"],\n",
        "    max_new_tokens=20,\n",
        "    num_beams=3,\n",
        ")\n",
        "\n",
        "print(\"Generated text: \", tokenizer.decode(generated_text[0]))"
      ],
      "metadata": {
        "id": "DLYX1ldGA0Kl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "We need to have access to the Llama weights"
      ],
      "metadata": {
        "id": "AAozQVHx7R94"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"\n",
        "python src/transformers/models/llama/convert_llama_weights_to_hf.py \\\n",
        "    --input_dir /path/to/downloaded/llama/weights --model_size 7B --output_dir /output/path --llama_version 3\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "O2BvGXdL7JWc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"/output/path\")\n",
        "model = AutoModelForCausalLM.from_pretrained(\"/output/path\")\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "neJyWSvd7KYT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# feed context and query into model\n"
      ],
      "metadata": {
        "id": "UsTnCunaV_Iy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "moCvQR-p0Zsb"
      },
      "outputs": [],
      "source": [
        "\"\"\"\n",
        "from langchain.chat_models import ChatOpenAI\n",
        "from langchain.chains import RetrievalQA\n",
        "\n",
        "# completion llm: replace this with our llm (OpenFlamingo?)\n",
        "llm = ChatOpenAI(\n",
        "    openai_api_key=OPENAI_API_KEY,\n",
        "    model_name='gpt-3.5-turbo',\n",
        "    temperature=0.0\n",
        ")\n",
        "\n",
        "qa = RetrievalQA.from_chain_type(\n",
        "    llm=llm,\n",
        "    chain_type=\"stuff\",\n",
        "    retriever=vectorstore.as_retriever()\n",
        ")\n",
        "qa.run(query)\n",
        "\"\"\""
      ]
    }
  ]
}