Content Types

Types for representing multi-part messages and content

Overview

Content types represent messages exchanged with the model. Each message can contain multiple parts with different media types.

Content

Base class for multi-part message content.

Fields

parts · list[Part]

List of parts that constitute a single message. Each part may have a different IANA MIME type.

role · str

The producer of the content. Must be either ‘user’ or ‘model’. Defaults to ‘user’ if not set.

Example

from google.genai.types import Content, Part

content = Content(
    parts=[
        Part.from_text(text="What's in this image?"),
        Part.from_uri(file_uri="gs://bucket/image.jpg", mime_type="image/jpeg")
    ],
    role="user"
)

UserContent

Convenience class for creating user messages.

Constructor

UserContent(parts: Union[PartUnionDict, list[PartUnionDict], list[Part]])

Automatically sets role="user" and cannot be changed.

Examples

from google.genai.types import UserContent, Part

# Simple text
user_content = UserContent("Why is the sky blue?")

# Single Part
user_content = UserContent(
    Part.from_uri(file_uri="gs://bucket/file.txt", mime_type="text/plain")
)

# Multiple parts
user_content = UserContent([
    "Analyze this image:",
    Part.from_bytes(data=image_bytes, mime_type="image/png")
])

# List of Part objects
parts = [
    Part.from_text(text="Question 1"),
    Part.from_text(text="Question 2")
]
user_content = UserContent(parts)

ModelContent

Convenience class for creating model messages.

Constructor

ModelContent(parts: Union[PartUnionDict, list[PartUnionDict], list[Part]])

Automatically sets role="model" and cannot be changed.

Examples

from google.genai.types import ModelContent, Part

# Simple text response
model_content = ModelContent("The sky appears blue because...")

# Response with function call
model_content = ModelContent(
    Part.from_function_call(name="get_weather", args={"location": "London"})
)

# Multiple response parts
model_content = ModelContent([
    "Here's the code:",
    Part.from_executable_code(
        code="print('Hello')",
        language=Language.PYTHON
    )
])

Part Union Types

PartUnionDict

Accepts various input formats:

PartUnionDict = Union[
    str,                    # Text string
    Part,                   # Part object
    PartDict,              # Part dictionary
    File,                  # File object
    PIL.Image.Image,       # PIL Image
]

ContentUnion

ContentUnion = Union[
    str,                    # Simple text
    Content,               # Content object
    ContentDict,           # Content dictionary
    list[Part],            # List of parts
    list[PartUnionDict],   # List of part unions
]

Content Construction Patterns

Text Only

# All equivalent
content1 = UserContent("Hello")
content2 = Content(parts=[Part.from_text(text="Hello")], role="user")
content3 = Content(parts=[Part(text="Hello")], role="user")

Multimodal Content

from google.genai.types import UserContent, Part

# Image + text
content = UserContent([
    "What's in this image?",
    Part.from_uri(
        file_uri="gs://bucket/image.jpg",
        mime_type="image/jpeg"
    )
])

# Video + text with metadata
content = UserContent([
    "Describe this video",
    Part(
        file_data=FileData(
            file_uri="gs://bucket/video.mp4",
            mime_type="video/mp4"
        ),
        video_metadata=VideoMetadata(
            start_offset="00:00:10",
            end_offset="00:00:30",
            fps=1.0
        )
    )
])

# Audio + text
content = UserContent([
    "Transcribe this audio",
    Part.from_bytes(
        data=audio_bytes,
        mime_type="audio/wav"
    )
])

Function Calling

from google.genai.types import ModelContent, UserContent, Part

# Model makes function call
model_call = ModelContent(
    Part.from_function_call(
        name="get_weather",
        args={"location": "San Francisco", "unit": "celsius"}
    )
)

# User provides function response
user_response = UserContent(
    Part.from_function_response(
        name="get_weather",
        response={"temperature": 18, "condition": "sunny"}
    )
)

Chat History

from google.genai.types import UserContent, ModelContent

history = [
    UserContent("What is 2+2?"),
    ModelContent("2+2 equals 4."),
    UserContent("What about 3+3?"),
    ModelContent("3+3 equals 6."),
]

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=history + [UserContent("What about 4+4?")]
)

Dict Representations

ContentDict

from google.genai.types import ContentDict, PartDict

content_dict: ContentDict = {
    "parts": [
        {"text": "Hello"},
        {"inline_data": {"data": b"...", "mime_type": "image/png"}}
    ],
    "role": "user"
}

PartDict

from google.genai.types import PartDict

text_part: PartDict = {"text": "Hello"}

image_part: PartDict = {
    "inline_data": {
        "data": image_bytes,
        "mime_type": "image/jpeg"
    }
}

file_part: PartDict = {
    "file_data": {
        "file_uri": "gs://bucket/file.pdf",
        "mime_type": "application/pdf"
    }
}

Media Resolution

Control tokenization quality for media:

from google.genai.types import Part, PartMediaResolutionLevel

# Using enum
part = Part.from_uri(
    file_uri="gs://bucket/image.jpg",
    mime_type="image/jpeg",
    media_resolution=PartMediaResolutionLevel.MEDIA_RESOLUTION_HIGH
)

# Using string
part = Part.from_uri(
    file_uri="gs://bucket/image.jpg",
    mime_type="image/jpeg",
    media_resolution="MEDIA_RESOLUTION_HIGH"
)

# Using dict with num_tokens
part = Part.from_uri(
    file_uri="gs://bucket/video.mp4",
    mime_type="video/mp4",
    media_resolution={"num_tokens": 512}
)

See Also

• Part Class - Part factory methods and details
• Types Overview - Type system overview
• Client Reference - Using content with the client