Human: create a svelte app whit material ui components that sends a graphql query for getting anime titles and anime rating to anilist then display that info to the user in a clean way
Assistant: To create a Svelte app with Material UI components that sends a GraphQL query for getting anime titles and ratings from AniList and displays that information to the user, you can follow these steps:

1. Create a new Svelte app using the Svelte template in your preferred development environment.

2. Install the following dependencies:
``` 
npm install @material-ui/core @material-ui/icons apollo-boost graphql graphql-tag svelte-apollo
``` 
3. Create a new GraphQL client using Apollo Boost:
```
import ApolloClient from "apollo-boost";

const client = new ApolloClient({
  uri: "https://graphql.anilist.co",
});
```
4. Create a GraphQL query to fetch anime titles and ratings:
```
import gql from "graphql-tag";

const ANIME_QUERY = gql`
  query ($perPage: Int!, $page: Int!) {
    Page(perPage: $perPage, page: $page) {
      media(type: ANIME, sort: POPULARITY_DESC) {
        id
        title {
          romaji
          english
        }
        averageScore
      }
    }
  }
`;
```
5. Create a Svelte component to render the anime titles and ratings using Material UI components:
```
<script>
  import { query } from "svelte-apollo";
  import { ANIME_QUERY } from "./queries";

  const { loading, error, data } = query(ANIME_QUERY, {
    variables: {
      perPage: 10,
      page: 1,
    },
  });
</script>

{#if loading}
  <p>Loading...</p>
{:else if error}
  <p>Error: {error.message}</p>
{:else}
  <ul>
    {#each data.Page.media as anime}
      <li>
        <h2>{anime.title.english || anime.title.romaji}</h2>
        <p>Rating: {anime.averageScore}</p>
      </li>
    {/each}
  </ul>
{/if}
```
6. Style the component using Material UI:
```
<slot></slot>

<style>
  :global(body) {
    margin: 0;
    font-family: "Roboto", sans-serif;
  }
  ul {
    list-style: none;
    padding: 0;
  }
  li {
    padding: 16px;
    border-bottom: 1px solid #eee;
  }
  h2 {
    margin: 0;
    font-size: 18px;
    font-weight: 500;
    color: #333;
  }
  p {
    margin: 0;
    font-size: 14px;
    font-weight: 400;
    color: #666;
  }
</style>
```
7. Render the component in your main app component:
```
<template>
  <div class="container">
    <h1>Anime Titles and Ratings</h1>
    <AnimeList />
  </div>
</template>

<script>
  import AnimeList from "./AnimeList.svelte";
</script>

<style>
  .container {
    display: flex;
    flex-direction: column;
    align-items: center;
    padding: 32px;
  }
  h1 {
    margin-bottom: 16px;
    font-size: 24px;
    font-weight: 500;
    color: #333;
  }
</style>
```
That's it! You should now have a Svelte app that fetches anime titles and ratings from AniList using GraphQL and displays them using Material UI components.
Human: Thank you! Exactly what I needed, Can you add some more complications?
Assistant: Sure, I can suggest a few ways to make this app more complicated and challenging:

1. Add pagination: By default, the AniList API returns only 10 results per page. You can add pagination to your app so that users can view more results.

2. Add search functionality: Allow users to search for specific anime titles by adding a search bar and updating the GraphQL query to filter results based on search terms.

3. Add user authentication: If you want to create a more robust app, you can add user authentication using a third-party service like Auth0 or Firebase. This will allow users to sign up, log in, and save their favorite anime titles.

4. Add animations and transitions: You can use Svelte's built-in animation features to add smooth transitions and animations to your app. For example, you can add a fade-in effect when new anime titles are loaded.

5. Add additional data and functionality: The AniList API provides a wealth of data beyond just titles and ratings, including synopses, episode counts, and more. You can add additional data to your app and use it to provide more functionality, such as a "watchlist" feature or recommendations based on a user's viewing history.
Human: Thank you, can you modify the first code to implement the second and the fifth proposition ?