--- title: OpenResponses Images and PDFs with AI Gateway product: vercel url: /docs/ai-gateway/sdks-and-apis/openresponses/images canonical_url: "https://vercel.com/docs/ai-gateway/sdks-and-apis/openresponses/images" last_updated: 2026-09-08 type: reference prerequisites: - /docs/ai-gateway/sdks-and-apis/openresponses - /docs/ai-gateway/sdks-and-apis related: - /docs/ai-gateway/sdks-and-apis/openresponses - /docs/ai-gateway/sdks-and-apis/openresponses/text-generation - /docs/ai-gateway/sdks-and-apis/openresponses/tool-calling summary: Send images and PDF documents for analysis using the OpenResponses API through AI Gateway. install_vercel_plugin: npx plugins add vercel/vercel-plugin --- # OpenResponses Images and PDFs with AI Gateway The [OpenResponses API](/docs/ai-gateway/sdks-and-apis/openresponses) accepts images and PDFs alongside text. Replace the plain string in a message's `content` with an array of parts: `input_text` for the prompt, `input_image` for an image, `input_file` for a document. ## Related pages > **For AI agents:** Follow these links to understand how this page connects to the rest of the Vercel ecosystem. For the full cross-link map (inbound, outbound, prerequisites, and semantic neighbors), see the .graph.md link below. - [OpenAI Responses Images and PDFs with AI Gateway](https://vercel.com/docs/ai-gateway/sdks-and-apis/responses/images?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=related) — Send images and PDF documents for analysis using the OpenAI Responses API through AI Gateway. - [AI Gateway Vision and Image Input](https://vercel.com/docs/ai-gateway/inputs-and-tools/vision?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=related) — Analyze images with AI Gateway using AI SDK 7, the Python beta, Chat Completions, Messages, and Responses APIs. - [OpenAI Chat Completions Images and PDFs with AI Gateway](https://vercel.com/docs/ai-gateway/sdks-and-apis/openai-chat-completions/images?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=related) — Send images and PDF documents to a model using the OpenAI Chat Completions API through AI Gateway. - [AI Gateway File and PDF Input](https://vercel.com/docs/ai-gateway/inputs-and-tools/file-input?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=related) — Send PDFs and documents to AI Gateway models with examples for each supported SDK and API format. - [AI Gateway Video Input](https://vercel.com/docs/ai-gateway/inputs-and-tools/video-input?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=related) — Analyze video clips with AI Gateway using AI SDK 7, Python, Chat Completions, and Responses / OpenResponses. Full cross-link map for this page: [/docs/ai-gateway/sdks-and-apis/openresponses/images.graph.md](/docs/ai-gateway/sdks-and-apis/openresponses/images.graph.md?from=related&source_path=%2Fdocs%2Fai-gateway%2Fsdks-and-apis%2Fopenresponses%2Fimages&source_site=vercel-docs&relationship=graph) #### TypeScript ```typescript filename="image-input.ts" import fs from 'node:fs'; const apiKey = process.env.AI_GATEWAY_API_KEY; const imageBase64 = fs.readFileSync('./diagram.png').toString('base64'); const response = await fetch('https://ai-gateway.vercel.sh/v1/responses', { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${apiKey}`, }, body: JSON.stringify({ model: 'anthropic/claude-opus-5', input: [ { type: 'message', role: 'user', content: [ { type: 'input_text', text: 'Describe this image in one sentence.' }, { type: 'input_image', image_url: `data:image/png;base64,${imageBase64}`, detail: 'auto', }, ], }, ], }), }); const result = await response.json(); const message = result.output.find((item: { type: string }) => item.type === 'message'); for (const block of message.content) { if (block.type === 'output_text') console.log(block.text); } ``` #### Python ```python filename="image_input.py" import base64 import os from openai import OpenAI client = OpenAI( api_key=os.getenv('AI_GATEWAY_API_KEY'), base_url='https://ai-gateway.vercel.sh/v1', ) with open('diagram.png', 'rb') as f: image_base64 = base64.b64encode(f.read()).decode() response = client.responses.create( model='anthropic/claude-opus-5', input=[ { 'type': 'message', 'role': 'user', 'content': [ {'type': 'input_text', 'text': 'Describe this image in one sentence.'}, { 'type': 'input_image', 'image_url': f'data:image/png;base64,{image_base64}', 'detail': 'auto', }, ], }, ], ) message = next(item for item in response.output if item.type == 'message') for block in message.content: if block.type == "output_text": print(block.text) ``` #### cURL ```bash filename="image-input.sh" IMAGE_B64=$(base64 -i diagram.png) curl https://ai-gateway.vercel.sh/v1/responses \ -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "anthropic/claude-opus-5", "input": [ { "type": "message", "role": "user", "content": [ { "type": "input_text", "text": "Describe this image in one sentence." }, { "type": "input_image", "image_url": "data:image/png;base64,'"$IMAGE_B64"'", "detail": "auto" } ] } ] }' ``` ## Public image URLs `image_url` also takes a plain URL, as long as the host serves it without authentication: ```typescript ({ type: 'input_image', image_url: 'https://example.com/diagram.png', detail: 'auto', }); ``` If the host blocks the request, the gateway returns a 400 naming the upstream status rather than falling back. Use base64 for anything behind a login or a signed URL. ## PDF documents Send a PDF with an `input_file` part. The document is passed to the model as a document, not rasterized, so the model reads its text directly: #### TypeScript ```typescript filename="pdf-input.ts" import fs from 'node:fs'; const pdfBase64 = fs.readFileSync('./report.pdf').toString('base64'); const response = await fetch('https://ai-gateway.vercel.sh/v1/responses', { method: 'POST', headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`, }, body: JSON.stringify({ model: 'anthropic/claude-opus-5', input: [ { type: 'message', role: 'user', content: [ { type: 'input_text', text: 'What total does this document state?' }, { type: 'input_file', filename: 'report.pdf', file_data: `data:application/pdf;base64,${pdfBase64}`, }, ], }, ], }), }); const result = await response.json(); const message = result.output.find((item: { type: string }) => item.type === 'message'); for (const block of message.content) { if (block.type === 'output_text') console.log(block.text); } ``` #### Python ```python filename="pdf_input.py" import base64 import os from openai import OpenAI client = OpenAI( api_key=os.getenv('AI_GATEWAY_API_KEY'), base_url='https://ai-gateway.vercel.sh/v1', ) with open('report.pdf', 'rb') as f: pdf_base64 = base64.b64encode(f.read()).decode() response = client.responses.create( model='anthropic/claude-opus-5', input=[ { 'type': 'message', 'role': 'user', 'content': [ {'type': 'input_text', 'text': 'What total does this document state?'}, { 'type': 'input_file', 'filename': 'report.pdf', 'file_data': f'data:application/pdf;base64,{pdf_base64}', }, ], }, ], ) message = next(item for item in response.output if item.type == 'message') for block in message.content: if block.type == "output_text": print(block.text) ``` #### cURL ```bash filename="pdf-input.sh" PDF_B64=$(base64 -i report.pdf) curl https://ai-gateway.vercel.sh/v1/responses \ -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "anthropic/claude-opus-5", "input": [ { "type": "message", "role": "user", "content": [ { "type": "input_text", "text": "What total does this document state?" }, { "type": "input_file", "filename": "report.pdf", "file_data": "data:application/pdf;base64,'"$PDF_B64"'" } ] } ] }' ``` ## Detail parameter `detail` controls the resolution the model analyzes an image at: - `auto` - Let the model decide - `low` - Lower resolution, fewer input tokens, faster - `high` - Higher resolution, more input tokens, better for small text and fine detail ## Next steps - [Text generation](/docs/ai-gateway/sdks-and-apis/openresponses/text-generation) - Request and response shapes for text - [Tool calling](/docs/ai-gateway/sdks-and-apis/openresponses/tool-calling) - Let the model call your functions --- [View full sitemap](/docs/sitemap)