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  1. docs/en/docs/release-notes.md

    `text/plain` containing JSON data would be accepted and the JSON data would be extracted.
    
    But requests with content type `text/plain` are exempt from [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) preflights, for being considered [Simple requests](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS#simple_requests). So, the browser would execute them right away including cookies, and the text content could be a JSON string that would be parsed and accepted by the FastAPI application....
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  2. docs/ja/docs/advanced/websockets.md

    # WebSocket
    
    **FastAPI**で<a href="https://developer.mozilla.org/en-US/docs/Web/API/WebSockets_API" class="external-link" target="_blank">WebSocket</a>が使用できます。
    
    ## `WebSockets`のインストール
    
    まず `WebSockets`のインストールが必要です。
    
    <div class="termy">
    
    ```console
    $ pip install websockets
    
    ---> 100%
    ```
    
    </div>
    
    ## WebSocket クライアント
    
    ### 本番環境
    
    本番環境では、React、Vue.js、Angularなどの最新のフレームワークで作成されたフロントエンドを使用しているでしょう。
    
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  3. docs/de/docs/tutorial/request-files.md

        Wenn Sie mehr über Formularfelder und ihre Kodierungen lesen möchten, besuchen Sie die <a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/Methods/POST" class="external-link" target="_blank"><abbr title="Mozilla Developer Network – Mozilla-Entwickler-Netzwerk">MDN</abbr>-Webdokumentation für <code>POST</code></a>.
    
    !!! warning "Achtung"
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  4. docs/en/data/external_links.yml

        link: https://developer.nvidia.com/blog/building-a-machine-learning-microservice-with-fastapi/
        title: Building a Machine Learning Microservice with FastAPI
      - author: Ravgeet Dhillon - Twilio
        link: https://www.twilio.com/en-us/blog/booking-appointments-twilio-notion-fastapi
        title: Booking Appointments with Twilio, Notion, and FastAPI
      - author: Abhinav Tripathi - Microsoft Blogs
    Others
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  5. docs/en/docs/how-to/sql-databases-peewee.md

        These Pydantic models define more or less a "schema" (a valid data shape).
    
        So this will help us avoiding confusion while using both.
    
    ### Create the Pydantic *models* / schemas
    
    Create all the same Pydantic models as in the SQLAlchemy tutorial:
    
    ```Python hl_lines="16-18  21-22  25-30  34-35  38-39  42-48"
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