docs: Add documentation for Milvus/Zilliz database integration (#1203)

This integration is similar to Pinecone/Qdrant. I'm writing a tutorial
on how to use Apify with Milvus/Zilliz, and it would be good to
reference our documentation in the tutorial.

Just a note: Milvus is an open-source vector database, and Zilliz offers
a managed solution based on Milvus.

@TC-MO, could you please review the English? I haven't included any
screenshots, as I believe the description should suffice to get started.
Also, maintain and update screenshot is a bit painful.

Additionally, I haven't added this integration to the
[cards](https://docs.apify.com/platform/integrations#data-pipelines-etls-and-aillm-tools).
Do you think it should be included there?

sources/platform/integrations/ai/milvus.md

@@ -0,0 +1,120 @@
+---
+title: Milvus integration
+description: Learn how to integrate Apify with Milvus (Zilliz) to save data scraped from the websites into the Milvus vector database.
+sidebar_label: Milvus
+sidebar_position: 4
+slug: /integrations/milvus
+toc_min_heading_level: 2
+toc_max_heading_level: 4
+---
+
+**Learn how to integrate Apify with Milvus (Zilliz) to save data scraped from websites into the Milvus vector database.**
+
+---
+
+[Milvus](https://milvus.io/) is an open-source vector database optimized for performing similarity searches on large datasets of high-dimensional vectors.
+Its focus on efficient vector similarity search allows for the creation of powerful and scalable retrieval systems.
+
+The Apify integration for Milvus allows exporting results from Apify Actors and Dataset items into a Milvus collection.
+It can also be connected to a managed Milvus instance on [Zilliz Cloud](https://cloud.zilliz.com).
+
+## Prerequisites
+
+Before you begin, ensure that you have the following:
+
+- A Milvus database URL and API token. Optionally, you can use a username and password. You can run Milvus on Docker or Kubernetes, but in this example, we'll use the hosted Milvus service at [Zilliz Cloud](https://cloud.zilliz.com).
+- An [OpenAI API key](https://openai.com/index/openai-api/) to compute text embeddings.
+- An [Apify API token](https://docs.apify.com/platform/integrations/api#api-token) to access [Apify Actors](https://apify.com/store).
+
+### How to set up Milvus database
+
+1. Sign up or log in to your Zilliz account and create a new cluster.
+
+1. Download the created credentials: user name and password.
+
+Once the cluster is ready and you have the URL, API key, and credentials, you can set up the integration with Apify.
+
+
+### Integration Methods
+
+You can integrate Apify with Milvus using either the Apify Console or the Apify Python SDK.
+
+:::note Website Content Crawler usage
+
+These examples use the Website Content Crawler Actor, which performs deep website crawling, cleans HTML by removing modals and navigation elements, and converts the content into Markdown.
+
+:::
+
+#### Apify Console
+
+1. Set up the [Website Content Crawler](https://apify.com/apify/website-content-crawler) Actor in the [Apify Console](https://console.apify.com). Refer to this guide on how to set up [website content crawl for your project](https://blog.apify.com/talk-to-your-website-with-large-language-models/).
+
+1. After setting up the crawler, go to the **integration** section, select **Connect Actor or Task**, and search for the Milvus integration.
+
+1. Select when to trigger this integration (typically when a run succeeds) and fill in all the required fields. If you haven't created a collection, it will be created automatically. You can learn more about the input parameters at the [Milvus integration input schema](https://apify.com/apify/milvus-integration/input-schema).
+
+- For a detailed explanation of the input parameters, including dataset settings, incremental updates, and examples, see the [Milvus integration description](https://apify.com/apify/milvus-integration).
+
+- For an explanation on how to combine Actors to accomplish more complex tasks, refer to the guide on [Actor-to-Actor](https://blog.apify.com/connecting-scrapers-apify-integration/) integrations.
+
+#### Python
+
+Another way to interact with Milvus is through the [Apify Python SDK](https://docs.apify.com/sdk/python/).
+
+1. Install the Apify Python SDK by running the following command:
+
+    ```py
+    pip install apify-client
+    ```
+
+1. Create a Python script and import all the necessary modules:
+
+    ```python
+    from apify_client import ApifyClient
+
+    APIFY_API_TOKEN = "YOUR-APIFY-TOKEN"
+    OPENAI_API_KEY = "YOUR-OPENAI-API-KEY"
+
+    MILVUS_COLLECTION_NAME = "YOUR-MILVUS-COLLECTION-NAME"
+    MILVUS_URL = "YOUR-MILVUS-URL"
+    MILVUS_API_KEY = "YOUR-MILVUS-API-KEY"
+    MILVUS_USER = "YOUR-MILVUS-USER"
+    MILVUS_PASSWORD = "YOUR-MILVUS-PASSWORD"
+
+    client = ApifyClient(APIFY_API_TOKEN)
+    ```
+
+1. Call the [Website Content Crawler](https://apify.com/apify/website-content-crawler) Actor to crawl the Milvus documentation and Zilliz website and extract text content from the web pages:
+
+    ```python
+    actor_call = client.actor("apify/website-content-crawler").call(
+        run_input={"maxCrawlPages": 10, "startUrls": [{"url": "https://milvus.io/"}, {"url": "https://zilliz.com/"}]}
+    )
+    ```
+
+1. Call Apify's Milvus integration and store all data in the Milvus Vector Database:
+
+    ```python
+    milvus_integration_inputs = {
+        "milvusUrl": MILVUS_URL,
+        "milvusApiKey": MILVUS_API_KEY,
+        "milvusCollectionName": MILVUS_COLLECTION_NAME,
+        "milvusUser": MILVUS_USER,
+        "milvusPassword": MILVUS_PASSWORD,
+        "datasetFields": ["text"],
+        "datasetId": actor_call["defaultDatasetId"],
+        "deltaUpdatesPrimaryDatasetFields": ["url"],
+        "expiredObjectDeletionPeriodDays": 30,
+        "embeddingsApiKey": OPENAI_API_KEY,
+        "embeddingsProvider": "OpenAI",
+    }
+    actor_call = client.actor("apify/milvus-integration").call(run_input=milvus_integration_inputs)
+
+    ```
+
+Congratulations! You've successfully integrated Apify with Milvus, and the scraped data is now stored in your Milvus database.
+
+## Additional Resources
+
+- [Apify Milvus Integration](https://apify.com/apify/milvus-integration)
+- [Milvus documentation](https://milvus.io/docs)

sources/platform/integrations/index.mdx

@@ -179,6 +179,12 @@ If you are working on an AI/LLM-related project, we recommend you look into the
         imageUrl="/img/platform/integrations/qdrant.svg"
         smallImage
     />
+    <Card
+        title="Milvus"
+        to="./integrations/milvus"
+        imageUrl="/img/platform/integrations/milvus.svg"
+        smallImage
+    />
 </CardGrid>
 
 ## Other Actors