> ## Documentation Index > Fetch the complete documentation index at: https://apidoc.deerapi.com/llms.txt > Use this file to discover all available pages before exploring further. # Edit > Use DeerAPI to call the Edit endpoint with request details, response details, examples, and an OpenAPI playground. ## Overview Use this endpoint to call the Edit workflow through DeerAPI. The API reference on this page shows the request schema, response schema, authentication requirements, and runnable examples for the configured endpoint. ## Before you start Use the DeerAPI base URL and pass your API Key in the `Authorization` header: ```text theme={null} https://api.deerapi.com ``` ```text theme={null} Authorization: Bearer $DEERAPI_KEY ``` ## Model selection Choose a current model ID from the [live pricing page](https://api.deerapi.com/pricing). Model availability changes over time, so avoid copying a model ID from an old project without checking the live list first. ## Implementation notes * Use the OpenAPI playground for the exact request fields accepted by this endpoint. * Keep API Keys on the server side when you build production applications. * Log the request ID from failed calls so support can investigate the request. * Retry `429`, `500`, and `503` responses with exponential backoff. ## OpenAPI ````yaml /api/openapi/image/openai/post-image-edit.openapi.json POST /v1/images/edits openapi: 3.1.0 info: title: Image Editing API version: 1.0.0 description: >- Edit existing images through the OpenAI-compatible DeerAPI image edits route. GPT image edit models return inline base64 payloads in `data[].b64_json`, and `output_format` controls the encoded image type. servers: - url: https://api.deerapi.com security: - bearerAuth: [] paths: /v1/images/edits: post: summary: Edit images description: >- Upload one or more source images, optionally include a mask, and request an edited result with a text instruction. operationId: image_editing requestBody: required: true content: multipart/form-data: schema: type: object required: - image - prompt properties: image: type: string format: binary description: >- Source image file. Start with one PNG or JPG input for the simplest flow. prompt: type: string description: Edit instruction describing the change you want. example: Add a small red ribbon to the paper boat. model: type: string description: >- The image editing model to use. Choose a supported model from the [Models page](https://api.deerapi.com/pricing). default: gpt-image-2 mask: type: string format: binary description: >- Optional PNG mask. Transparent areas indicate regions that should be edited. 'n': type: string description: Number of edited images to return. default: '1' quality: type: string enum: - high - medium - low description: Quality setting for models that support it. response_format: type: string enum: - url - b64_json description: >- Requested response container when supported by the selected model. GPT image edit models return `data[].b64_json`; use `output_format` to choose the encoded image type. output_format: type: string description: >- Encoded image type for GPT image edit results returned in `data[].b64_json`. For example, use `jpeg` for a JPEG payload. example: jpeg size: type: string description: Requested output size when supported by the selected model. default: model: gpt-image-2 prompt: Add a small red ribbon to the paper boat. output_format: jpeg example: prompt: Add a small red ribbon to the paper boat. model: gpt-image-2 response_format: json image: '@/path/to/image.png' examples: Default: summary: Default request value: prompt: Add a small red ribbon to the paper boat. model: gpt-image-2 response_format: json image: '@/path/to/image.png' responses: '200': description: Edited image result. content: application/json: schema: type: object required: - created - data - usage properties: created: type: integer usage: type: object properties: prompt_tokens: type: integer completion_tokens: type: integer total_tokens: type: integer prompt_tokens_details: type: object properties: cached_tokens_details: type: object properties: {} completion_tokens_details: type: object properties: {} input_tokens: type: integer output_tokens: type: integer input_tokens_details: type: object properties: image_tokens: type: integer text_tokens: type: integer cached_tokens_details: type: object properties: {} claude_cache_creation_5_m_tokens: type: integer claude_cache_creation_1_h_tokens: type: integer data: type: array items: type: object properties: b64_json: type: string description: >- Base64-encoded image payload. Decode this value to get the edited image bytes. url: type: string description: >- Temporary image URL when the selected model supports URL output. revised_prompt: type: string description: Provider-rewritten prompt, when available. example: created: 1776836647 usage: prompt_tokens: 0 completion_tokens: 0 total_tokens: 981 prompt_tokens_details: cached_tokens_details: {} completion_tokens_details: {} input_tokens: 785 output_tokens: 196 input_tokens_details: image_tokens: 768 text_tokens: 17 cached_tokens_details: {} claude_cache_creation_5_m_tokens: 0 claude_cache_creation_1_h_tokens: 0 data: - b64_json: x-codeSamples: - lang: Shell label: cURL source: | curl -s 'https://api.deerapi.com/v1/images/edits' \ -H "Authorization: Bearer $DEERAPI_KEY" \ -F 'prompt=Add a small red ribbon to the paper boat.' \ -F 'model=gpt-image-2' \ -F 'response_format=json' \ -F 'image=@/path/to/image.png' - lang: Python label: requests source: > import os import requests url = "https://api.deerapi.com/v1/images/edits" headers = {"Authorization": "Bearer " + os.environ["DEERAPI_KEY"]} data = { "prompt": "Add a small red ribbon to the paper boat.", "model": "gpt-image-2", "response_format": "json" } files = {"image": open("/path/to/image.png", "rb")} response = requests.post(url, headers=headers, data=data, files=files) print(response.json()) - lang: JavaScript label: fetch source: > const form = new FormData(); form.append("prompt", "Add a small red ribbon to the paper boat."); form.append("model", "gpt-image-2"); form.append("response_format", "json"); form.append("image", new Blob(["replace with file bytes"]), "image.png"); const response = await fetch("https://api.deerapi.com/v1/images/edits", { method: "POST", headers: { Authorization: `Bearer ${process.env.DEERAPI_KEY}` }, body: form, }); console.log(await response.json()); components: securitySchemes: bearerAuth: type: http scheme: bearer description: Use a DeerAPI API Key as a Bearer token. ````