--- title: "Image Generation in Chat Completions, Responses API" description: "import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';" type: skill canonical_url: https://claudary.paisolsolutions.com/skills/image-generation-chat source: "Claudary" difficulty: intermediate author: "Claude Code Knowledge Pack" date: 2026-07-10T11:25:17.039Z license: CC-BY-4.0 attribution: "Image Generation in Chat Completions, Responses API — Claudary (https://claudary.paisolsolutions.com/skills/image-generation-chat)" --- # Image Generation in Chat Completions, Responses API import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; ## Overview import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; # Image Generation in Chat Completions, Responses API This guide covers how to generate images when using the `chat/completions`. Note - if you want this on Responses API please file a Feature Request [here](https://github.com/BerriAI/litellm/issues/new). :::info Requires LiteLLM v1.76.1+ ::: Supported Providers: - Google AI Studio (`gemini`) - Vertex AI (`vertex_ai/`) LiteLLM will standardize the `images` response in the assistant message for models that support image generation during chat completions. ```python title="Example response from litellm" "message": { ... "content": "Here's the image you requested:", "images": [ { "image_url": { "url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...", "detail": "auto" }, "index": 0, "type": "image_url" } ] } ``` ## Quick Start ```python showLineNumbers title="Image generation with chat completion" from litellm import completion import os os.environ["GEMINI_API_KEY"] = "your-api-key" response = completion( model="gemini/gemini-2.5-flash-image-preview", messages=[ {"role": "user", "content": "Generate an image of a banana wearing a costume that says LiteLLM"} ], ) print(response.choices[0].message.content) # Text response print(response.choices[0].message.images) # List of image objects ``` 1. Setup config.yaml ```yaml showLineNumbers title="config.yaml" model_list: - model_name: gemini-image-gen litellm_params: model: gemini/gemini-2.5-flash-image-preview api_key: os.environ/GEMINI_API_KEY ``` 2. Run proxy server ```bash showLineNumbers title="Start the proxy" litellm --config config.yaml # RUNNING on http://0.0.0.0:4000 ``` 3. Test it! ```bash showLineNumbers title="Make request" curl http://0.0.0.0:4000/v1/chat/completions \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $LITELLM_KEY" \\ -d '{ "model": "gemini-image-gen", "messages": [ { "role": "user", "content": "Generate an image of a banana wearing a costume that says LiteLLM" } ] }' ``` **Expected Response** ```bash { "id": "chatcmpl-3b66124d79a708e10c603496b363574c", "choices": [ { "finish_reason": "stop", "index": 0, "message": { "content": "Here's the image you requested:", "role": "assistant", "images": [ { "image_url": { "url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...", "detail": "auto" }, "index": 0, "type": "image_url" } ] } } ], "created": 1723323084, "model": "gemini/gemini-2.5-flash-image-preview", "object": "chat.completion", "usage": { "completion_tokens": 12, "prompt_tokens": 16, "total_tokens": 28 } } ``` ## Streaming Support ```python showLineNumbers title="Streaming image generation" from litellm import completion import os os.environ["GEMINI_API_KEY"] = "your-api-key" response = completion( model="gemini/gemini-2.5-flash-image-preview", messages=[ {"role": "user", "content": "Generate an image of a banana wearing a costume that says LiteLLM"} ], stream=True, ) for chunk in response: if hasattr(chunk.choices[0].delta, "images") and chunk.choices[0].delta.images is not None: print("Generated image:", chunk.choices[0].delta.images[0]["image_url"]["url"]) break ``` ```bash showLineNumbers title="Streaming request" curl http://0.0.0.0:4000/v1/chat/completions \\ -H "Content-Type: application/json" \\ -H "Authorization: Bearer $LITELLM_KEY" \\ -d '{ "model": "gemini-image-gen", "messages": [ { "role": "user", "content": "Generate an image of a banana wearing a costume that says LiteLLM" } ], "stream": true }' ``` **Expected Streaming Response** ```bash data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1723323084,"model":"gemini/gemini-2.5-flash-image-preview","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}]} data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1723323084,"model":"gemini/gemini-2.5-flash-image-preview","choices":[{"index":0,"delta":{"content":"Here's the image you requested:"},"finish_reason":null}]} data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1723323084,"model":"gemini/gemini-2.5-flash-image-preview","choices":[{"index":0,"delta":{"images":[{"image_url":{"url":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...","detail":"auto"},"index":0,"type":"image_url"}]},"finish_reason":null}]} data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1723323084,"model":"gemini/gemini-2.5-flash-image-preview","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]} data: [DONE] ``` ## Async Support ```python showLineNumbers title="Async image generation" from litellm import acompletion import asyncio import os os.environ["GEMINI_API_KEY"] = "your-api-key" async def generate_image(): response = await acompletion( model="gemini/gemini-2.5-flash-image-preview", messages=[ {"role": "user", "content": "Generate an image of a banana wearing a costume that says LiteLLM"} ], ) print(response.choices[0].message.content) # Text response print(response.choices[0].message.images) # List of image objects return response # Run the async function asyncio.run(generate_image()) ``` ## Supported Models | Provider | Model | |----------|--------| | Google AI Studio | `gemini/gemini-2.0-flash-preview-image-generation`, `gemini/gemini-2.5-flash-image-preview`, `gemini/gemini-3-pro-image-preview` | | Vertex AI | `vertex_ai/gemini-2.0-flash-preview-image-generation`, `vertex_ai/gemini-2.5-flash-image-preview`, `vertex_ai/gemini-3-pro-image-preview` | ## Spec The `images` field in the response follows this structure: ```python "images": [ { "image_url": { "url": "data:image/png;base64,", "detail": "auto" }, "index": 0, "type": "image_url" } ] ``` - `images` - List[ImageURLListItem]: Array of generated images - `image_url` - ImageURLObject: Container for image data - `url` - str: Base64 encoded image data in data URI format - `detail` - str: Image detail level (always "auto" for generated images) - `index` - int: Index of the image in the response - `type` - str: Type identifier (always "image_url") The images are returned as base64-encoded data URIs that can be directly used in HTML `` tags or saved to files. --- Source: [Claudary](https://claudary.paisolsolutions.com/skills/image-generation-chat) · https://claudary.paisolsolutions.com