HuggingFace_Story.ipynb

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          "text": [
            "Collecting transformers\n",
            "  Downloading transformers-4.31.0-py3-none-any.whl (7.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.4/7.4 MB\u001b[0m \u001b[31m14.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
            "  Downloading safetensors-0.3.1-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[31m39.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.65.0)\n",
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            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.16.4 safetensors-0.3.1 tokenizers-0.13.3 transformers-4.31.0\n"
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      "execution_count": null,
      "outputs": [
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          "text": [
            "Collecting langchain\n",
            "  Downloading langchain-0.0.248-py3-none-any.whl (1.4 MB)\n",
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            "Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (4.0.2)\n",
            "Collecting dataclasses-json<0.6.0,>=0.5.7 (from langchain)\n",
            "  Downloading dataclasses_json-0.5.14-py3-none-any.whl (26 kB)\n",
            "Collecting langsmith<0.1.0,>=0.0.11 (from langchain)\n",
            "  Downloading langsmith-0.0.16-py3-none-any.whl (29 kB)\n",
            "Requirement already satisfied: numexpr<3.0.0,>=2.8.4 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.8.4)\n",
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            "Collecting openapi-schema-pydantic<2.0,>=1.2 (from langchain)\n",
            "  Downloading openapi_schema_pydantic-1.2.4-py3-none-any.whl (90 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m90.0/90.0 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pydantic<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain) (1.10.12)\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install openai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QxCym1PGjN1-",
        "outputId": "99470a39-a86a-4838-ab04-1dfb0a2a1213"
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        {
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            "Installing collected packages: openai\n",
            "Successfully installed openai-0.27.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
        "os.environ[\"HUGGINGFACEHUB_API_TOKEN\"] = \"\""
      ],
      "metadata": {
        "id": "ObAuIApWg6ih"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline\n",
        "from langchain import PromptTemplate, LLMChain, OpenAI\n",
        "import requests\n",
        "\n",
        "#img to text\n",
        "def img2text(url):\n",
        "    image_to_text = pipeline(\"image-to-text\", model=\"Salesforce/blip-image-captioning-base\")\n",
        "\n",
        "    text = image_to_text(url)[0][\"generated_text\"]\n",
        "\n",
        "\n",
        "    print(text)\n",
        "    return text\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "#llm\n",
        "\n",
        "def generate_story(scenario):\n",
        "\n",
        "    template = \"\"\"\n",
        "    你是一位很会讲故事的老人，下面Context中的内容是一个外国人说的一句英文，请你根据这句话延展出一个中文的故事。最好还能有一点小幽默，字数在100个字以内。\n",
        "\n",
        "    CONTEXT: {scenario}\n",
        "    STORY:\n",
        "    \"\"\"\n",
        "    prompt = PromptTemplate(template=template, input_variables=[\"scenario\"])\n",
        "\n",
        "    story_llm = LLMChain(llm=OpenAI(\n",
        "        model_name=\"gpt-3.5-turbo\", temperature=1),prompt=prompt,verbose=True)\n",
        "\n",
        "    story = story_llm.predict(scenario=scenario)\n",
        "\n",
        "    print(story)\n",
        "    return story\n",
        "\n",
        "\n",
        "\n",
        "# text to speech\n",
        "def text2speech(message):\n",
        "\n",
        "  API_URL = \"https://api-inference.huggingface.co/models/espnet/kan-bayashi_ljspeech_vits\"\n",
        "  headers = {\"Authorization\": \"Bearer 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\"}\n",
        "\n",
        "  payloads = {\n",
        "      \"inputs\": message\n",
        "  }\n",
        "\n",
        "  response = requests.post(API_URL, headers=headers, json=payloads)\n",
        "  with open('audio.flac','wb') as file:\n",
        "    file.write(response.content)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "scenario = img2text(\"pic.jpg\")\n",
        "story = generate_story(scenario)\n",
        "text2speech(story)"
      ],
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1369: UserWarning: Using `max_length`'s default (20) to control the generation length. This behaviour is deprecated and will be removed from the config in v5 of Transformers -- we recommend using `max_new_tokens` to control the maximum length of the generation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a man is smiling while he sits on a pile of gold coins\n",
            "\n",
            "\n",
            "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
            "Prompt after formatting:\n",
            "\u001b[32;1m\u001b[1;3m\n",
            "    你是一位很会讲故事的老人，下面Context中的内容是一个外国人说的一句英文，请你根据这句话延展出一个中文的故事。最好还能有一点小幽默，字数在100个字以内。\n",
            " \n",
            "    CONTEXT: a man is smiling while he sits on a pile of gold coins\n",
            "    STORY:\n",
            "    \u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/langchain/llms/openai.py:200: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain.chat_models import ChatOpenAI`\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/langchain/llms/openai.py:801: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain.chat_models import ChatOpenAI`\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\u001b[1m> Finished chain.\u001b[0m\n",
            "从前有个人，非常贪婪。他与一位仙人相遇，仙人给了他一堆金币，并告诉他：“这是你唯一的一次机会，只要你在一个小时内笑得不停，这些金币就会一直属于你。”\n",
            "\n",
            "这个人非常兴奋，坐在金币堆上开始傻笑。然而，时间一分一秒过去，他的笑声越来越虚弱。最后，一小时结束，金币全都消失了。\n",
            "\n",
            "仙人问他：“为什么你停止了笑？”\n",
            "这个人气喘吁吁地说：“那都是真金，我笑着笑着把它们吞下去了！”\n"
          ]
        }
      ]
    }
  ]
}