​
Overview

GoogleImageGenService provides high-quality image generation capabilities using Google’s Imagen models. It supports generating multiple images from text prompts with various customization options.

​
Installation

To use GoogleImageGenService, install the required dependencies:

pip install "pipecat-ai[google]"

You’ll also need to set up your Google API key as an environment variable: GOOGLE_API_KEY

​
Configuration

​
Constructor Parameters

​
params
InputParams
default:"InputParams()"

Generation parameters configuration

​
api_key
str
required

Google API key for authentication

​
Input Parameters

​
number_of_images
int
default:"1"

Number of images to generate (1-8)

​
model
str
default:"imagen-3.0-generate-002"

Model identifier

​
negative_prompt
str
default:"None"

Elements to exclude from generation

​
Input

The service accepts text prompts through its image generation pipeline.

​
Output Frames

​
URLImageRawFrame

​
url
string

Generated image URL (null for Google implementation as it returns raw bytes)

​
image
bytes

Raw image data

​
size
tuple

Image dimensions (width, height)

​
format
string

Image format (e.g., ‘JPEG’)

​
ErrorFrame

​
error
string

Error information if generation fails

​
Usage Example

from pipecat.services.google.image import GoogleImageGenService

# Configure service
image_gen = GoogleImageGenService(
    api_key="your-google-api-key",
    params=GoogleImageGenService.InputParams(
        number_of_images=2,
        model="imagen-3.0-generate-002",
        negative_prompt="blurry, distorted, low quality"
    )
)

# Use in pipeline
main_pipeline = Pipeline(
    [
        transport.input(),
        context_aggregator.user(),
        llm_service,
        image_gen,
        tts_service,
        transport.output(),
        context_aggregator.assistant(),
    ]
)

​
Frame Flow

​
Metrics Support

The service supports metrics collection:

  • Time to First Byte (TTFB)
  • Processing duration
  • API response metrics

​
Model Support

Google’s Imagen service offers different model variants:

Model IDDescription
imagen-3.0-generate-002Latest Imagen model with high-quality outputs

See other available models in Google’s Imagen documentation.

​
Error Handling

try:
    async for frame in service.run_image_gen(prompt):
        if isinstance(frame, ErrorFrame):
            handle_error(frame.error)
except Exception as e:
    logger.error(f"Image generation error: {e}")

​
Overview

GoogleImageGenService provides high-quality image generation capabilities using Google’s Imagen models. It supports generating multiple images from text prompts with various customization options.

​
Installation

To use GoogleImageGenService, install the required dependencies:

pip install "pipecat-ai[google]"

You’ll also need to set up your Google API key as an environment variable: GOOGLE_API_KEY

​
Configuration

​
Constructor Parameters

​
params
InputParams
default:"InputParams()"

Generation parameters configuration

​
api_key
str
required

Google API key for authentication

​
Input Parameters

​
number_of_images
int
default:"1"

Number of images to generate (1-8)

​
model
str
default:"imagen-3.0-generate-002"

Model identifier

​
negative_prompt
str
default:"None"

Elements to exclude from generation

​
Input

The service accepts text prompts through its image generation pipeline.

​
Output Frames

​
URLImageRawFrame

​
url
string

Generated image URL (null for Google implementation as it returns raw bytes)

​
image
bytes

Raw image data

​
size
tuple

Image dimensions (width, height)

​
format
string

Image format (e.g., ‘JPEG’)

​
ErrorFrame

​
error
string

Error information if generation fails

​
Usage Example

from pipecat.services.google.image import GoogleImageGenService

# Configure service
image_gen = GoogleImageGenService(
    api_key="your-google-api-key",
    params=GoogleImageGenService.InputParams(
        number_of_images=2,
        model="imagen-3.0-generate-002",
        negative_prompt="blurry, distorted, low quality"
    )
)

# Use in pipeline
main_pipeline = Pipeline(
    [
        transport.input(),
        context_aggregator.user(),
        llm_service,
        image_gen,
        tts_service,
        transport.output(),
        context_aggregator.assistant(),
    ]
)

​
Frame Flow

​
Metrics Support

The service supports metrics collection:

  • Time to First Byte (TTFB)
  • Processing duration
  • API response metrics

​
Model Support

Google’s Imagen service offers different model variants:

Model IDDescription
imagen-3.0-generate-002Latest Imagen model with high-quality outputs

See other available models in Google’s Imagen documentation.

​
Error Handling

try:
    async for frame in service.run_image_gen(prompt):
        if isinstance(frame, ErrorFrame):
            handle_error(frame.error)
except Exception as e:
    logger.error(f"Image generation error: {e}")