// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

GRADLE_TEMP="$(mktemp -d)"
trap 'rm -rf "${GRADLE_TEMP}"' EXIT

# The Gradle tests need the pom.xml only to read its version number.
# (And the file needs to be two directory levels up from the Gradle build file.)
# TODO(cpovirk): Find a better way to give them that information.
cp pom.xml "${GRADLE_TEMP}"

for version in 5.6.4 7.0.2; do

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python
images: list[Image]
```

as in:

{* ../../docs_src/body_nested_models/tutorial008_py39.py hl[13] *}

## Editor support everywhere { #editor-support-everywhere }

And you get editor support everywhere.

Check the in-code annotation tips above to see more specific details.

## Learn More { #learn-more }

You can also combine `dataclasses` with other Pydantic models, inherit from them, include them in your own models, etc.

To learn more, check the <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/" class="external-link" target="_blank">Pydantic docs about dataclasses</a>.

/// note

Keep in mind that you have to return the `JSONResponse` directly.

///

/// info

The `model` key is not part of OpenAPI.

**FastAPI** will take the Pydantic model from there, generate the JSON Schema, and put it in the correct place.

The correct place is:

* In the key `content`, that has as value another JSON object (`dict`) that contains:

---

Here's how to help others with questions (in discussions or issues):

### Understand the question { #understand-the-question }

* Check if you can understand what is the **purpose** and use case of the person asking.

It brings the same **developer experience** of building apps with FastAPI to **deploying** them to the cloud. 🎉

It will also take care of most of the things you would need when deploying an app, like:

* HTTPS
* Replication, with autoscaling based on requests
* etc.

FastAPI Cloud is the primary sponsor and funding provider for the *FastAPI and friends* open source projects. ✨

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/query-param-models/image01.png">
</div>

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

**FastAPI** will **extract** the data for **each field** from the **headers** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the required headers in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/header-param-models/image01.png">
</div>

- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```
(You can paste links or attach files by dragging & dropping them below)
- Include code to invoke the TFLite Converter Python API and the errors.