Before diving deeper into the **Dependency Injection** system, let's upgrade the previous example.

## A `dict` from the previous example

In the previous example, we where returning a `dict` from our dependency ("dependable"):

```Python hl_lines="7"
{!./tutorial/src/dependencies/tutorial001.py!}
```

But then we get a `dict` in the parameter `commons` of the path operation function.

And we know that `dict`s can't provide a lot of editor support because they can't know their keys and value types.

## Create a Pydantic model

But we are already using Pydantic models in other places and we have already seen all the benefits.

Let's use them here too.

Create a model for the common parameters (and don't pay attention to the rest, for now):

```Python hl_lines="10 11 12 13"
{!./tutorial/src/dependencies/tutorial002.py!}
```

## Return a Pydantic model

Now we can return a Pydantic model from the dependency ("dependable") with the same data as the dict before:

```Python hl_lines="17"
{!./tutorial/src/dependencies/tutorial002.py!}
```

## Declare the Pydantic model

We can now come back to the path operation function and declare the type of the `commons` parameter to be that Pydantic model:

```Python
commons: CommonQueryParams = Depends(common_parameters)
```

It won't be interpreted as a JSON request `Body` because we are using `Depends`:

```Python hl_lines="21"
{!./tutorial/src/dependencies/tutorial002.py!}
```

!!! info
    In the case of dependencies with `Depends`, the type of the parameter is only to get editor support.

    Your dependencies won't be enforced to return a specific type of data.

## Use the Pydantic model

And now we can use that model in our code, with all the lovable editor support:

```Python hl_lines="23 24 25"
{!./tutorial/src/dependencies/tutorial002.py!}
```

<img src="/img/tutorial/dependencies/image02.png">

## Recap

By using Pydantic models in your dependencies too you can keep all the editor support that **FastAPI** is designed to support.