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---
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title: "OpenAIImageGenerator"
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id: openaiimagegenerator
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slug: "/openaiimagegenerator"
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description: "Generate images using OpenAI's image generation models such as `gpt-image-2`."
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---
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# OpenAIImageGenerator
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Generate images using OpenAI's image generation models such as `gpt-image-2`.
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<div className="key-value-table">
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| | |
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| --- | --- |
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| **Most common position in a pipeline** | After a [`PromptBuilder`](../builders/promptbuilder.mdx), flexible |
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| **Mandatory init variables** | `api_key`: An OpenAI API key. Can be set with `OPENAI_API_KEY` env var. |
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| **Mandatory run variables** | `prompt`: A string containing the prompt for the model |
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| **Output variables** | `images`: A list of generated images <br /> <br />`revised_prompt`: A string containing the prompt that was used to generate the image, if there was any revision to the prompt made by OpenAI |
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| **API reference** | [Generators](/reference/generators-api) |
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| **GitHub link** | https://github.com/deepset-ai/haystack/blob/main/haystack/components/generators/openai_image_generator.py |
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| **Package name** | `haystack-ai` |
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</div>
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## Overview
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The `OpenAIImageGenerator` component generates images using OpenAI's image generation models (such as `gpt-image-2`).
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By default, the component uses the `gpt-image-2` model, `"auto"` quality, and 1024x1024 resolution. You can change these parameters using `model` (during component initialization), `quality`, and `size` (during component initialization or run) parameters.
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`OpenAIImageGenerator` needs an OpenAI key to work. It uses an `OPENAI_API_KEY` environment variable by default. Otherwise, you can pass an API key at initialization with `api_key`:
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```
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image_generator = OpenAIImageGenerator(api_key=Secret.from_token("<your-api-key>"))
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```
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Check our [API reference](/reference/generators-api#openaiimagegenerator) for the detailed component parameters description, or the [OpenAI documentation](https://developers.openai.com/api/reference/resources/images/methods/generate) for the details on OpenAI API parameters.
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## Usage
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### On its own
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```python
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from haystack.components.generators import OpenAIImageGenerator
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image_generator = OpenAIImageGenerator()
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response = image_generator.run("Show me a picture of a black cat.")
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print(response)
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```
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### In a pipeline
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In the following pipeline, we first set up a `PromptBuilder` that will structure the image description with a detailed template describing various artistic elements. The pipeline then passes this structured prompt into an `OpenAIImageGenerator` to generate the image based on this detailed description.
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```python
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from haystack import Pipeline
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from haystack.components.generators import OpenAIImageGenerator
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from haystack.components.builders import PromptBuilder
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prompt_builder = PromptBuilder(
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template="""Create a {style} image with the following details:
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Main subject: {prompt}
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Artistic style: {art_style}
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Lighting: {lighting}
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Color palette: {colors}
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Composition: {composition}
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Additional details: {details}""",
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)
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image_generator = OpenAIImageGenerator()
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pipeline = Pipeline()
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pipeline.add_component("prompt_builder", prompt_builder)
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pipeline.add_component("image_generator", image_generator)
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pipeline.connect("prompt_builder.prompt", "image_generator.prompt")
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results = pipeline.run(
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{
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"prompt": "a mystical treehouse library",
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"style": "photorealistic",
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"art_style": "fantasy concept art with intricate details",
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"lighting": "dusk with warm lantern light glowing from within",
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"colors": "rich earth tones, deep greens, and golden accents",
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"composition": "wide angle view showing the entire structure nestled in an ancient oak tree",
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"details": "spiral staircases wrapping around branches, stained glass windows, floating books, and magical fireflies providing ambient illumination",
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},
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)
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generated_images = results["image_generator"]["images"]
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revised_prompt = results["image_generator"]["revised_prompt"]
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print(f"Generated image (base64-encoded): {generated_images[0]}")
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print(f"Revised prompt: {revised_prompt}")
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```
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