diff --git a/apify-api/openapi/openapi.yaml b/apify-api/openapi/openapi.yaml index 7ddfa96cf4..77a6922c32 100644 --- a/apify-api/openapi/openapi.yaml +++ b/apify-api/openapi/openapi.yaml @@ -122,7 +122,7 @@ info: ``` However, there are a few explicitly described exceptions, such as - Dataset [Get items](#/reference/datasets/item-collection/get-items) or + [Get dataset items](#/reference/datasets/item-collection/get-items) or Key-value store [Get record](#/reference/key-value-stores/record/get-record) API endpoints, which return data in other formats. In case of an error, the response has the HTTP status code in the range of diff --git a/apify-api/openapi/paths/actor-tasks/actor-tasks@{actorTaskId}@runs.yaml b/apify-api/openapi/paths/actor-tasks/actor-tasks@{actorTaskId}@runs.yaml index c9c9da4293..e6b3f0096e 100644 --- a/apify-api/openapi/paths/actor-tasks/actor-tasks@{actorTaskId}@runs.yaml +++ b/apify-api/openapi/paths/actor-tasks/actor-tasks@{actorTaskId}@runs.yaml @@ -153,7 +153,7 @@ post: To fetch the Actor run results that are typically stored in the default dataset, you'll need to pass the ID received in the `defaultDatasetId` field received in the response JSON to the - [Get items](#/reference/datasets/item-collection/get-items) API endpoint. + [Get dataset items](#/reference/datasets/item-collection/get-items) API endpoint. operationId: actorTask_runs_post parameters: - name: actorTaskId diff --git a/apify-api/openapi/paths/actors/acts@{actorId}@runs.yaml b/apify-api/openapi/paths/actors/acts@{actorId}@runs.yaml index d14dc6da63..0a37342939 100644 --- a/apify-api/openapi/paths/actors/acts@{actorId}@runs.yaml +++ b/apify-api/openapi/paths/actors/acts@{actorId}@runs.yaml @@ -145,7 +145,7 @@ post: To fetch the Actor run results that are typically stored in the default dataset, you'll need to pass the ID received in the `defaultDatasetId` field - received in the response JSON to the [Get items](#/reference/datasets/item-collection/get-items) + received in the response JSON to the [Get dataset items](#/reference/datasets/item-collection/get-items) API endpoint. operationId: act_runs_post parameters: diff --git a/apify-api/openapi/paths/datasets/datasets@{datasetId}@items.yaml b/apify-api/openapi/paths/datasets/datasets@{datasetId}@items.yaml index f2dda00bcc..24f86003e6 100644 --- a/apify-api/openapi/paths/datasets/datasets@{datasetId}@items.yaml +++ b/apify-api/openapi/paths/datasets/datasets@{datasetId}@items.yaml @@ -1,7 +1,7 @@ get: tags: - Storage/Datasets - summary: Get items + summary: Get dataset items description: | Returns data stored in the dataset in a desired format. diff --git a/sources/academy/tutorials/api/run_actor_and_retrieve_data_via_api.md b/sources/academy/tutorials/api/run_actor_and_retrieve_data_via_api.md index a11e82f121..d852059967 100644 --- a/sources/academy/tutorials/api/run_actor_and_retrieve_data_via_api.md +++ b/sources/academy/tutorials/api/run_actor_and_retrieve_data_via_api.md @@ -254,7 +254,7 @@ The **run info** JSON also contains the IDs of the default [dataset](/platform/s > If you are scraping products, or any list of items with similar fields, the [dataset](/platform/storage/dataset) should be your storage of choice. Don't forget though, that dataset items are immutable. This means that you can only add to the dataset, and not change the content that is already inside it. -To retrieve the data from a dataset, send a GET request to the [**Get items**](/api/v2/dataset-items-get) endpoint and pass the `defaultDatasetId` into the URL. For a GET request to the default dataset, no token is needed. +To retrieve the data from a dataset, send a GET request to the [**Get dataset items**](/api/v2/dataset-items-get) endpoint and pass the `defaultDatasetId` into the URL. For a GET request to the default dataset, no token is needed. ```cURL https://api.apify.com/v2/datasets/DATASET_ID/items diff --git a/sources/legal/index.mdx b/sources/legal/index.mdx index e437218dc0..41da1ed879 100644 --- a/sources/legal/index.mdx +++ b/sources/legal/index.mdx @@ -10,7 +10,7 @@ hide_table_of_contents: true -## Company details (Impressum) +## Legal info (Imprint) **Apify Technologies s.r.o.**
Registered seat: Vodickova 704/36, 110 00 Prague 1, Czech Republic
diff --git a/sources/legal/sidebars.js b/sources/legal/sidebars.js index 5e69718528..678a12caef 100644 --- a/sources/legal/sidebars.js +++ b/sources/legal/sidebars.js @@ -2,7 +2,7 @@ module.exports = { legal: [ { type: 'link', - label: 'Company details (Impressum)', + label: 'Legal info (Imprint)', href: '/legal', }, { diff --git a/sources/platform/actors/development/quick_start/build_with_ai.md b/sources/platform/actors/development/quick_start/build_with_ai.md index 904de4c8bc..1ea37732a3 100644 --- a/sources/platform/actors/development/quick_start/build_with_ai.md +++ b/sources/platform/actors/development/quick_start/build_with_ai.md @@ -1,19 +1,22 @@ --- -title: Build with AI +title: Building new Actors with AI sidebar_position: 3 -description: Learn how to set up your environment, choose the right tools, and establish workflows for effective vibe coding +sidebar_label: Build with AI +description: Learn how to build new Actors or improving existing ones using AI code generation and vibe coding tools. slug: /actors/development/quick-start/build-with-ai toc_max_heading_level: 4 --- -**Set up your environment, choose tools, and build workflows for effective AI development.** +**Learn how to develop new Actors or improve existing ones using AI code generation and vibe coding tools.** --- import { RULES_AND_INSTRUCTIONS_PROMPT } from "@site/src/utils/ai-prompts"; import PromptButton from "@site/src/components/PromptButton"; -This guide explains how to enhance your development workflow by leveraging `llms.txt` and `llms-full.txt` with an AI assistant. You will learn how to provide foundational context and further refine AI's behavior with specific rules and instruction files. +This guide provides best practices for building new Actors or improving existing ones using AI code generation +and vibe coding tools such as Cursor, Claude Code, or Visual Studio Code, +by providing the AI agents with the right instructions and context. ## `llms.txt` and `llms-full.txt` diff --git a/sources/platform/actors/development/quick_start/index.mdx b/sources/platform/actors/development/quick_start/index.mdx index 9063686d41..98ae32a08d 100644 --- a/sources/platform/actors/development/quick_start/index.mdx +++ b/sources/platform/actors/development/quick_start/index.mdx @@ -1,5 +1,6 @@ --- -title: Quick start +title: Actor development quick start +sidebar_label: Quick start sidebar_position: 1 description: Create your first Actor using the Apify Web IDE or locally in your IDE. slug: /actors/development/quick-start diff --git a/sources/platform/actors/development/quick_start/start_locally.md b/sources/platform/actors/development/quick_start/start_locally.md index 9839e9c55b..3cd77e754d 100644 --- a/sources/platform/actors/development/quick_start/start_locally.md +++ b/sources/platform/actors/development/quick_start/start_locally.md @@ -1,5 +1,6 @@ --- -title: Local development +title: Local Actor development +sidebar_label: Local development sidebar_position: 1 description: Create your first Actor locally on your machine, deploy it to the Apify platform, and run it in the cloud. slug: /actors/development/quick-start/locally diff --git a/sources/platform/actors/running/index.md b/sources/platform/actors/running/index.md index 56541d822d..88be596a39 100644 --- a/sources/platform/actors/running/index.md +++ b/sources/platform/actors/running/index.md @@ -118,4 +118,4 @@ print(dataset_items) The newly started Actor runs under the account associated with the provided `token`, and therefore all resources consumed are charged to this user account. -Internally, the `call()` function invokes the [Run Actor](/api/v2/#/reference/actors/run-collection/run-actor) API endpoint, waits for the Actor to finish, and reads its output using the [Get items](/api/v2/#/reference/datasets/item-collection/get-items) API endpoint. +Internally, the `call()` function invokes the [Run Actor](/api/v2/#/reference/actors/run-collection/run-actor) API endpoint, waits for the Actor to finish, and reads its output using the [Get dataset items](/api/v2/#/reference/datasets/item-collection/get-items) API endpoint. diff --git a/sources/platform/index.mdx b/sources/platform/index.mdx index 50204a168f..2886d8dc88 100644 --- a/sources/platform/index.mdx +++ b/sources/platform/index.mdx @@ -10,9 +10,10 @@ import Card from "@site/src/components/Card"; import CardGrid from "@site/src/components/CardGrid"; import homepageContent from "./homepage_content.json"; -> **Apify** is a cloud platform that helps you build reliable web scrapers, fast, and automate anything you can do manually in a web browser. + +> **Apify** is a cloud platform and marketplace of tools for web data extraction and automation. > -> **Actors** are serverless cloud programs running on the Apify platform that can easily crawl websites with millions of pages, but also perform arbitrary computing jobs such as sending emails or data transformations. They can be started manually, using our API or scheduler, and they can be easily integrated with other apps. +> **Actors** are serverless programs that run in the cloud. They can perform anything from simple actions such as filling out a web form or sending an email, to complex operations such as crawling a website with a million pages, or removing duplicates from a large dataset. Actors can persist their state and be restarted, and thus they can run as short or as long as necessary, from seconds to hours, even infinitely. ## Getting started diff --git a/sources/platform/integrations/ai/mcp.md b/sources/platform/integrations/ai/mcp.md index 422f58e5d6..cf324270f9 100644 --- a/sources/platform/integrations/ai/mcp.md +++ b/sources/platform/integrations/ai/mcp.md @@ -8,7 +8,8 @@ slug: /integrations/mcp -The _Apify Model Context Protocol (MCP) Server_ allows AI applications to connect to Apify's extensive library of Actors as tools to perform web scraping, data extraction, or other automation tasks in real time. +The Apify [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server allows AI applications and agents to search and run Actors from [Apify Store](https://apify.com/store) as tools for web scraping, data extraction, or automation, +as well as access Apify documentation and tutorials from your AI coding environments. ![Apify MCP Server](../../images/apify_mcp_server.png)