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docs/en/docs/deployment/manually.md
When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs. ## Install the Server Program When you install FastAPI, it comes with a production server, Uvicorn, and you can start it with the `fastapi run` command. But you can also install an ASGI server manually: === "Uvicorn"
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docs/en/docs/deployment/concepts.md
### Server Memory For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**. And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨
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docs/pt/docs/advanced/events.md
## Caso de uso Vamos iniciar com um exemplo de **caso de uso** e então ver como resolvê-lo com isso. Vamos imaginar que você tem alguns **modelos de _machine learning_** que deseja usar para lidar com as requisições. 🤖
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docs/pt/docs/async.md
* **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
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docs/fr/docs/tutorial/path-params.md
!!! tip "Astuce" Pour ceux qui se demandent, "AlexNet", "ResNet", et "LeNet" sont juste des noms de <abbr title="Techniquement, des architectures de modèles">modèles</abbr> de Machine Learning. ### Déclarer un paramètre de chemin Créez ensuite un *paramètre de chemin* avec une annotation de type désignant l'énumération créée précédemment (`ModelName`) : ```Python hl_lines="16"
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docs/en/docs/advanced/behind-a-proxy.md
server["Server on http://127.0.0.1:8000/app"] browser --> proxy proxy --> server ``` !!! tip The IP `0.0.0.0` is commonly used to mean that the program listens on all the IPs available in that machine/server. The docs UI would also need the OpenAPI schema to declare that this API `server` is located at `/api/v1` (behind the proxy). For example: ```JSON hl_lines="4-8" { "openapi": "3.1.0",
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docs/en/docs/tutorial/first-steps.md
In the output, there's a line with something like: ```hl_lines="4" INFO: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit) ``` That line shows the URL where your app is being served, in your local machine. ### Check it Open your browser at <a href="http://127.0.0.1:8000" class="external-link" target="_blank">http://127.0.0.1:8000</a>. You will see the JSON response as: ```JSON {"message": "Hello World"}
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docs/en/docs/advanced/events.md
## Use Case Let's start with an example **use case** and then see how to solve it with this. Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖
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docs/en/docs/async.md
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docs/en/docs/fastapi-cli.md
By default it will listen on the IP address `127.0.0.1`, which is the IP for your machine to communicate with itself alone (`localhost`). ## `fastapi run` When you run `fastapi run`, it will run on production mode by default. It will have **auto-reload disabled** by default.
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