{"id":46248,"date":"2022-12-09T17:01:30","date_gmt":"2023-08-16T04:23:13","guid":{"rendered":"https:\/\/www.silicloud.com\/zh\/blog\/46248-2\/"},"modified":"2024-04-29T04:29:42","modified_gmt":"2024-04-28T20:29:42","slug":"46248-2","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/zh\/blog\/46248-2\/","title":{"rendered":""},"content":{"rendered":"

2023\/10\/09\u66f4\u65b0<\/p>\n

Jupyter AI\u304cAmazon Bedrock\u306b\u5bfe\u5fdc\u3057\u307e\u3057\u305f\u306e\u3067\u65e9\u901f\u8a66\u3057\u307e\u3057\u305f\u3002Jupyter AI\u81ea\u4f53\u3082\u5b8c\u6210\u5ea6\u304c\u5897\u3057\u3066\u3044\u308b\u5370\u8c61\u3067\u3059\u3002<\/p>\n

 <\/p>\n

\n

\u6765\u307e\u3057\u305f\uff01Jupyter\u306bAI\u304c\u6765\u307e\u3057\u305f\uff01<\/p>\n

 <\/p>\n

\n

AWS\u30d6\u30ed\u30b0\u3067\u3082\u7d39\u4ecb\u3055\u308c\u3066\u3044\u307e\u3059\u2192\u3053\u3061\u3089<\/p>\n<\/div>\n

\u65e9\u901f\u4f7f\u3063\u3066\u307f\u307e\u3057\u305f<\/p>\n

\u74b0\u5883\u69cb\u7bc9<\/h2>\n

docker\u3067\u30b5\u30af\u30c3\u3068\u884c\u304d\u307e\u3059\u3002
\njupyter_ai\u30d1\u30c3\u30b1\u30fc\u30b8\u304cJupyter AI\u3067\u3059\u3002OpenAI\u306eAPI\u304c\u547c\u3070\u308c\u308b\u305f\u3081\u3001openai\u3082\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n

FROM<\/span> jupyter\/minimal-notebook:lab-3.6.3<\/span>\r\n\r\nRUN <\/span>pip install<\/span> --no-cache-dir<\/span> \\\r\n<\/span>  jupyter_ai \\\r\n<\/span>  openai\r\n<\/code><\/pre>\n
\u30d3\u30eb\u30c9<\/p>\n
docker build -t<\/span> jupyter-ai .<\/span>\r\n<\/code><\/pre>\n
\u8d77\u52d5<\/p>\n
docker run -it<\/span> --rm<\/span> \\<\/span>\r\n  -p<\/span> 8888:8888 \\<\/span>\r\n  -e<\/span> \"OPENAI_API_KEY=<OPENAI_API_KEY>\"<\/span> \\<\/span>\r\n  jupyter-ai\r\n<\/code><\/pre>\n
\u30bf\u30fc\u30df\u30ca\u30eb\u306b\u30c8\u30fc\u30af\u30f3\u4ed8\u304d\u306eURL\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u306e\u3067\u3001\u30d6\u30e9\u30a6\u30b6\u3067\u30a2\u30af\u30bb\u30b9\u3057\u307e\u3059\u3002<\/p>\n
\"image.png\"<\/div>\n
\u8d77\u52d5\u3057\u307e\u3057\u305f\u3002<\/p>\n
\u30c1\u30e3\u30c3\u30c8\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30a4\u30b9<\/h2>\n
\u5de6\u30d1\u30cd\u30eb\u306b\u30c1\u30e3\u30c3\u30c8\u306e\u30dc\u30bf\u30f3\u304c\u8ffd\u52a0\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n
\"image.png\"<\/div>\n
Welcome\u30e1\u30c3\u30bb\u30fc\u30b8\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n
\"127.0.0.1_8888_lab_workspaces_auto-d(1280x720)<\/div>\n
language model\u3068embedding model\u3092\u9078\u629e\u3057\u307e\u3059\u3002<\/p>\n
\"127.0.0.1_8888_lab_workspaces_auto-d(1280x720)<\/div>\n
\u3053\u308c\u3067\u6e96\u5099\u5b8c\u4e86\u3067\u3059\u3002
\n\u30c1\u30e3\u30c3\u30c8\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
\"\"<\/div>\n
\u304a\u304a\uff01<\/p>\n
\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306b\u3064\u3044\u3066\u8cea\u554f\u3067\u304d\u308b<\/h3>\n
\u305f\u3060\u30c1\u30e3\u30c3\u30c8\u304c\u3067\u304d\u308b\u3060\u3051\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002\u30ce\u30fc\u30c8\u30d6\u30c3\u30af\u306e\u30bb\u30eb\u306b\u5bfe\u3057\u3066\u7bc4\u56f2\u9078\u629e\u3092\u3059\u308b\u3068\u3001\u30c1\u30e3\u30c3\u30c8\u30a8\u30ea\u30a2\u306e\u4e0b\u90e8\u306bInclude selection\u3068Replace selection\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/p>\n
\"\"<\/div>\n
Include selection\u3060\u3068\u9078\u629e\u3057\u305f\u30b3\u30fc\u30c9\u3092\u542b\u3093\u3060\u5f62\u3067\u8cea\u554f\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
\u3059\u3063\u3052\u30fc\uff01<\/p>\n
\"\"<\/div>\n
\n
\u30ed\u30b0\u3092\u78ba\u8a8d\u3057\u305f\u3068\u3053\u308d\u3001\u5185\u90e8\u3067\u306fLangChain\u3092\u4f7f\u3063\u3066API\u3092\u53e9\u3044\u3066\u3044\u308b\u3088\u3046\u306b\u898b\u3048\u307e\u3059\u3002
\n(DefaultActor pid=473)
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) > Entering new ConversationChain chain…
\n(DefaultActor pid=473) Prompt after formatting:
\n(DefaultActor pid=473) System: You are Jupyternaut, a conversational assistant living in JupyterLab to help users.
\n(DefaultActor pid=473) You are not a language model, but rather an application built on a foundation model from OpenAI called text-ada-001.
\n(DefaultActor pid=473) You are talkative and provides lots of specific details from its context.
\n(DefaultActor pid=473) You may use Markdown to format your response.
\n(DefaultActor pid=473) Code blocks must be formatted in Markdown.
\n(DefaultActor pid=473) Math should be rendered with inline TeX markup, surrounded by $.
\n(DefaultActor pid=473) If you do not know the answer to a question, answer truthfully by responding that you do not know.
\n(DefaultActor pid=473) The following is a friendly conversation between you and a human.
\n(DefaultActor pid=473) Human: Hello!
\n(DefaultActor pid=473) AI:
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) Hi there! How are you?
\n(DefaultActor pid=473) Human: what does this code do?
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) “`
\n(DefaultActor pid=473) from diffusers import DiffusionPipeline
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) pipeline = DiffusionPipeline.from_pretrained(“runwayml\/stable-diffusion-v1-5”)
\n(DefaultActor pid=473) pipeline.to(“cuda”)
\n(DefaultActor pid=473) pipeline(“An image of a squirrel in Picasso style”).images[0]
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) “`
\n(DefaultActor pid=473) AI:
\n(DefaultActor pid=473)
\n(DefaultActor pid=473) > Finished chain.<\/p>\n<\/div>\n
Replace selection\u306b\u30c1\u30a7\u30c3\u30af\u3092\u5165\u308c\u308b\u3068\u3001\u9078\u629e\u3057\u305f\u30b3\u30fc\u30c9\u90e8\u5206\u304c\u30c1\u30e3\u30c3\u30c8\u306e\u56de\u7b54\u3067\u4e0a\u66f8\u304d\u3055\u308c\u307e\u3059\u3002\u305f\u3060\u3057\u3001\u30c1\u30e3\u30c3\u30c8\u306e\u56de\u7b54\u304c\u6b63\u3057\u3044\u304b\u306f\u308f\u304b\u3089\u306a\u3044\u306e\u3067\u3001\u30c1\u30a7\u30c3\u30af\u3057\u3066\u304b\u3089\u66f4\u65b0\u3059\u308b\u307b\u3046\u304c\u826f\u3055\u305d\u3046\u3067\u3059\u3002\uff08\u305d\u3082\u305d\u3082\u3001\u30b3\u30fc\u30c9\u3067\u8fd4\u3063\u3066\u3053\u306a\u3044\u3053\u3068\u3082\u3042\u308a\u307e\u3059\u3057\u3002\uff09<\/p>\n
\u30ed\u30fc\u30ab\u30eb\u30c7\u30fc\u30bf\u306b\u3064\u3044\u3066\u5b66\u3076<\/h3>\n
\u3053\u308c\u3060\u3051\u3058\u3083\u3042\u308a\u307e\u305b\u3093\u3002\u30c1\u30e3\u30c3\u30c8\u304c\u8cea\u554f\u306b\u7b54\u3048\u308b\u969b\u306b\u30ed\u30fc\u30ab\u30eb\u30c7\u30fc\u30bf\u3092\u542b\u3081\u308b\u3088\u3046\u306b\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002embedding model\u304c\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/p>\n
\u8a66\u3057\u306bhuggingface\/diffusers\u306eREADME\u3092\u57cb\u3081\u8fbc\u3093\u3067\u307f\u307e\u3059\u3002<\/p>\n
mkdir <\/span>docs\r\ncd <\/span>docs\r\nwget https:\/\/raw.githubusercontent.com\/huggingface\/diffusers\/main\/README.md\r\n<\/code><\/pre>\n
\u6e96\u5099\u5b8c\u4e86\u3067\u3059\u3002<\/p>\n
\u30c1\u30e3\u30c3\u30c8\u6b04\u306b\/learn\u30b3\u30de\u30f3\u30c9\u3092\u5165\u529b\u3057\u3001\u899a\u3048\u3055\u305b\u307e\u3059\u3002<\/p>\n
\/learn docs\/\r\n<\/code><\/pre>\n
\u3046\u307e\u304f\u884c\u3063\u305f\u3088\u3046\u3067\u3059\u3002<\/p>\n
\"127.0.0.1_8888_lab_tree_docs(1280x720).png\"<\/div>\n
\u8cea\u554f\u3059\u308b\u969b\u306f\/ask\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n
\/ask \"Please tell me how to install Diffusers using pip.\"\r\n<\/code><\/pre>\n
\"\"<\/div>\n
You can install ? Diffusers in your virtual environment from PyPi using pip (the official package):
\npip install –upgrade diffusers[torch]<\/p><\/blockquote>\n
\u899a\u3048\u3055\u305b\u305f\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3067\u306f\u4ee5\u4e0b\u306e\u5185\u5bb9\u3067\u3059\u306e\u3067\u3001\u5c11\u3057\u8981\u7d04\u3055\u308c\u3066\u51fa\u3066\u3044\u308b\u3088\u3046\u3067\u3059\u3002<\/p>\n
\"\"<\/div>\n
%%ai\u30de\u30b8\u30c3\u30af\u30b3\u30de\u30f3\u30c9<\/h2>\n
Jupyter AI\u306f\u30c1\u30e3\u30c3\u30c8\u3060\u3051\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002%%ai\u30de\u30b8\u30c3\u30af\u30b3\u30de\u30f3\u30c9\u3082\u4f7f\u3048\u307e\u3059\u3002<\/p>\n
    \u62e1\u5f35\u306e\u30ed\u30fc\u30c9<\/ul>\n
    %<\/span>load_ext<\/span> jupyter_ai_magics<\/span>\r\n<\/code><\/pre>\n
    \u3053\u308c\u3060\u3051\u3067\u3059\u3002<\/p>\n
    \u4f7f\u3048\u308b\u30e2\u30c7\u30eb\u306e\u4e00\u89a7\u3092\u53d6\u5f97<\/h3>\n
    %<\/span>ai<\/span> list<\/span>\r\n<\/code><\/pre>\n
    \n
    ProviderEnvironment variableSet?Modelsai21AI21_API_KEY\u274cai21:j1-large, ai21:j1-grande, ai21:j1-jumbo, ai21:j1-grande-instruct, ai21:j2-large, ai21:j2-grande, ai21:j2-jumbo, ai21:j2-grande-instruct, ai21:j2-jumbo-instructanthropicANTHROPIC_API_KEY\u274canthropic:claude-v1, anthropic:claude-v1.0, anthropic:claude-v1.2, anthropic:claude-instant-v1, anthropic:claude-instant-v1.0cohereCOHERE_API_KEY\u274ccohere:medium, cohere:xlargehuggingface_hubHUGGINGFACEHUB_API_TOKEN\u274cThis provider does not define a list of models.openaiOPENAI_API_KEY\u2705openai:text-davinci-003, openai:text-davinci-002, openai:text-curie-001, openai:text-babbage-001, openai:text-ada-001, openai:davinci, openai:curie, openai:babbage, openai:adaopenai-chatOPENAI_API_KEY\u2705openai-chat:gpt-4, openai-chat:gpt-4-0314, openai-chat:gpt-4-32k, openai-chat:gpt-4-32k-0314, openai-chat:gpt-3.5-turbo, openai-chat:gpt-3.5-turbo-0301openai-chat-newOPENAI_API_KEY\u2705openai-chat-new:gpt-4, openai-chat-new:gpt-4-0314, openai-chat-new:gpt-4-32k, openai-chat-new:gpt-4-32k-0314, openai-chat-new:gpt-3.5-turbo, openai-chat-new:gpt-3.5-turbo-0301sagemaker-endpointNot applicable.N\/AThis provider does not define a list of models.<\/div>\n<\/div>\n
    \u74b0\u5883\u5909\u6570\u306b\u30ad\u30fc\u3092\u30bb\u30c3\u30c8\u3057\u305f\u9805\u76ee\u304cSet?\u304c\u2705\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n
    \u30de\u30b8\u30c3\u30af\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u3046\u969b\u306bmodel ID\u3092\u4e00\u7dd2\u306b\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n
    %%<\/span>ai<\/span> openai<\/span>:<\/span>text<\/span>-<\/span>ada<\/span>-<\/span>001<\/span>\r\nWrite<\/span> some<\/span> JavaScript<\/span> code<\/span> that<\/span> prints<\/span> \"<\/span>hello world<\/span>\"<\/span> to<\/span> the<\/span> console<\/span>.<\/span>\r\n<\/code><\/pre>\n
    \"\"<\/div>\n
    \u307b\u30fc<\/p>\n
    \u30c7\u30d5\u30a9\u30eb\u30c8\u3067\u306fMarkdown\u3067\u306e\u51fa\u529b\u3068\u306a\u308a\u307e\u3059\u304c\u3001-f\u307e\u305f\u306f–format\u30aa\u30d7\u30b7\u30e7\u30f3\u3067\u66f8\u5f0f\u3092\u6307\u5b9a\u3067\u304d\u307e\u3059\u3002<\/p>\n
    %%<\/span>ai<\/span> openai<\/span>:<\/span>text<\/span>-<\/span>ada<\/span>-<\/span>001<\/span> -<\/span>f<\/span> code<\/span>\r\nWrite<\/span> some<\/span> Java<\/span> code<\/span> that<\/span> prints<\/span> \"<\/span>hello world<\/span>\"<\/span> to<\/span> the<\/span> console<\/span>.<\/span>\r\n<\/code><\/pre>\n
    \"\"<\/div>\n
    \u307b\u30fc\u307b\u30fc
    \n\uff08\u3042\u308c\uff1fJava\u3063\u3066\u3053\u3093\u306a\u66f8\u304d\u65b9\u3067\u3057\u305f\u3063\u3051\uff1f\uff1f\uff09<\/p>\n
    \u4ed6\u306e\u30bb\u30eb\u306e\u5185\u5bb9\u3092\u53c2\u7167\u3059\u308b<\/h3>\n
    \u524d\u306e\u30bb\u30eb\u306e\u30a4\u30f3\u30d7\u30c3\u30c8\u3092\u53c2\u7167\u3055\u305b\u3089\u308c\u307e\u3059\u3002<\/p>\n
    %%<\/span>ai<\/span> openai<\/span>:<\/span>text<\/span>-<\/span>davinci<\/span>-<\/span>003<\/span>\r\nHere<\/span>'<\/span>s a detailed explanation of the following code, simplified for elementary school students:\r\n--\r\n{In[5]}\r\n<\/span><\/code><\/pre>\n
    \"\"<\/div>\n
    \u304a\u304a\uff01<\/p>\n
    \u30a4\u30f3\u30d7\u30c3\u30c8\u3060\u3051\u3067\u306a\u304f\u30a2\u30a6\u30c8\u30d7\u30c3\u30c8\u3082\u4f7f\u3048\u307e\u3059\u3002
    \n\u66f4\u306b\u30a8\u30e9\u30fc\u3082\u4f7f\u3048\u307e\u3059\u306e\u3067\u3001\u3053\u3093\u306a\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/p>\n
    %%<\/span>ai<\/span> openai<\/span>:<\/span>text<\/span>-<\/span>davinci<\/span>-<\/span>003<\/span> --<\/span>format<\/span> code<\/span>\r\nThe<\/span> following<\/span> Python<\/span> code<\/span>:<\/span>\r\n--<\/span>\r\n{<\/span>In<\/span>[<\/span>14<\/span>]}<\/span>\r\n--<\/span>\r\nproduced<\/span> the<\/span> following<\/span> Python<\/span> error<\/span>:<\/span>\r\n--<\/span>\r\n{<\/span>Err<\/span>[<\/span>14<\/span>]}<\/span>\r\n--<\/span>\r\nPlease<\/span> tell<\/span> me<\/span> the<\/span> cause<\/span> of<\/span> the<\/span> error<\/span>.<\/span>\r\n<\/code><\/pre>\n
    \"\"<\/div>\n
    \u3046\u304a\u304a\u304a\u304a\u304a\u304a\u304a\u304a\u304a\u304a\u304a\uff01<\/p>\n
    \u3059\u3063\u3054\u3044\uff01\uff01<\/p>\n
    \n
    \u307e\u3060\u65b0\u3057\u3044\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306a\u306e\u3067\u3001\u5c11\u3057\u52d5\u304b\u306a\u3044\u3068\u3053\u308d\u306f\u3042\u308a\u307e\u3059\u304c\u3001\u4eca\u5f8c\u306b\u671f\u5f85\u3067\u3059\u306d\u3002<\/p>\n
    \n
    \u7d9a\u7de8\u66f8\u304d\u307e\u3057\u305f<\/h2>\n
    \u3088\u304b\u3063\u305f\u3089\u898b\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
     <\/p>\n","protected":false},"excerpt":{"rendered":"
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