Add ImageContent documentation page

docs-website/docs/concepts/data-classes.mdx

@@ -120,6 +120,12 @@ image = ByteStream.from_file_path("dog.jpg")
 
 Read the detailed documentation for the `ChatMessage` data class on a dedicated [ChatMessage](data-classes/chatmessage.mdx) page.
 
+### ImageContent
+
+`ImageContent` represents image-based content used in multimodal chat messages and vision-language pipelines.
+
+Read the detailed documentation for the `ImageContent` data class on the dedicated [ImageContent](./data-classes/imagecontent) page.
+
 ### Document
 
 #### Overview

docs-website/docs/concepts/data-classes/imagecontent.mdx

@@ -0,0 +1,213 @@
+---
+
+title: "ImageContent"
+id: imagecontent
+slug: "/imagecontent"
+description: "`ImageContent` represents image-based content in Haystack chat messages and multimodal pipelines."
+----------------------------------------------------------------------------------------------------------------
+
+# ImageContent
+
+`ImageContent` is a Haystack data class used to represent image-based content in chat messages and multimodal AI pipelines.
+
+It is commonly used with:
+
+* multimodal LLMs
+* vision-language models
+* image-aware chat applications
+* document/image processing workflows
+
+`ImageContent` stores images as base64-encoded strings together with metadata such as MIME type and image detail level.
+
+If you are looking for the full API reference, see the [API documentation](/reference/data-classes-api#imagecontent).
+
+---
+
+# Creating ImageContent
+
+You can create an `ImageContent` object directly from a base64 string:
+
+```python
+from haystack.dataclasses import ImageContent
+
+image = ImageContent(
+    base64_image="your_base64_encoded_image",
+    mime_type="image/png"
+)
+
+print(image)
+```
+
+---
+
+# Loading Images from a File Path
+
+The `from_file_path()` class method provides a convenient way to load local image files.
+
+```python
+from haystack.dataclasses import ImageContent
+
+image = ImageContent.from_file_path(
+    "sample.png",
+    detail="low"
+)
+
+print(image)
+```
+
+The optional `detail` parameter is currently supported by OpenAI vision models and accepts:
+
+* `"auto"`
+* `"high"`
+* `"low"`
+
+You can also resize images while loading:
+
+```python
+image = ImageContent.from_file_path(
+    "sample.png",
+    size=(512, 512)
+)
+```
+
+This helps reduce:
+
+* memory usage
+* processing time
+* payload size
+
+when working with multimodal LLM APIs.
+
+---
+
+# Loading Images from a URL
+
+You can also create an `ImageContent` object directly from an image URL:
+
+```python
+from haystack.dataclasses import ImageContent
+
+image = ImageContent.from_url(
+    "https://images.unsplash.com/photo-1546182990-dffeafbe841d",
+    detail="low"
+)
+
+print(image)
+```
+
+Internally, Haystack downloads the image and converts it into a base64 representation.
+
+---
+
+# Using ImageContent with ChatMessage
+
+`ImageContent` is commonly used together with `ChatMessage` for multimodal conversations.
+
+```python
+from haystack.dataclasses import ChatMessage, ImageContent
+
+image = ImageContent.from_url(
+    "https://images.unsplash.com/photo-1546182990-dffeafbe841d",
+    detail="low"
+)
+
+message = ChatMessage.from_user(
+    content_parts=[
+        "What does this image show?",
+        image
+    ]
+)
+
+print(message)
+```
+
+This allows multimodal LLMs to process both:
+
+* textual prompts
+* image inputs
+
+within the same message.
+
+---
+
+# Metadata
+
+The optional `meta` parameter allows you to attach custom metadata to the image.
+
+```python
+image = ImageContent.from_url(
+    "https://example.com/image.png",
+    meta={"source": "example-dataset"}
+)
+```
+
+This can be useful for:
+
+* tracing
+* dataset tracking
+* workflow metadata
+* custom application logic
+
+---
+
+# Validation
+
+By default, `ImageContent` validates:
+
+* base64 encoding
+* MIME type correctness
+* image MIME compatibility
+
+Validation can be disabled to improve performance:
+
+```python
+image = ImageContent(
+    base64_image="your_base64_encoded_image",
+    mime_type="image/png",
+    validation=False
+)
+```
+
+---
+
+# Serialization
+
+`ImageContent` supports dictionary serialization.
+
+```python
+image_dict = image.to_dict()
+
+restored_image = ImageContent.from_dict(image_dict)
+```
+
+---
+
+# Displaying Images
+
+The `show()` method can display images directly in:
+
+* Jupyter notebooks
+* local desktop environments
+
+```python
+image.show()
+```
+
+This requires the `Pillow` package:
+
+```bash
+pip install pillow
+```
+
+---
+
+# Related Components
+
+`ImageContent` is frequently used with:
+
+* `ChatMessage`
+* multimodal chat generators
+* image converters
+* vision-language pipelines
+* `PDFToImageContent`
+* `ImageFileToImageContent`