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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.

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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

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Configuration

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Constructor Parameters

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params
InputParams
default:"InputParams()"
Generation parameters configuration
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api_key
str
required
Google API key for authentication

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Input Parameters

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number_of_images
int
default:"1"
Number of images to generate (1-8)
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model
str
default:"imagen-3.0-generate-002"
Model identifier
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negative_prompt
str
default:"None"
Elements to exclude from generation

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Input

The service accepts text prompts through its image generation pipeline.

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Output Frames

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URLImageRawFrame

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url
string
Generated image URL (null for Google implementation as it returns raw bytes)
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image
bytes
Raw image data
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size
tuple
Image dimensions (width, height)
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format
string
Image format (e.g., ‘JPEG’)

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ErrorFrame

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error
string
Error information if generation fails

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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(),
    ]
)

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Frame Flow

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Metrics Support

The service supports metrics collection:
  • Time to First Byte (TTFB)
  • Processing duration
  • API response metrics

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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.

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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}")