--- title: Streaming product: vercel url: /docs/ai-gateway/sdks-and-apis/openai-chat-completions/streaming canonical_url: "https://vercel.com/docs/ai-gateway/sdks-and-apis/openai-chat-completions/streaming" last_updated: 2026-07-28 type: conceptual prerequisites: - /docs/ai-gateway/sdks-and-apis/openai-chat-completions - /docs/ai-gateway/sdks-and-apis related: - /docs/ai-gateway/sdks-and-apis/openai-chat-completions/chat-completions - /docs/ai-gateway/sdks-and-apis/openai-chat-completions/tool-calling - /docs/ai-gateway/sdks-and-apis/openai-chat-completions/reasoning - /docs/ai-gateway/sdks-and-apis/openai-chat-completions/advanced summary: Stream OpenAI Chat Completions responses token by token as they are generated. install_vercel_plugin: npx plugins add vercel/vercel-plugin --- # Streaming Set `stream: true` on a [chat completion](/docs/ai-gateway/sdks-and-apis/openai-chat-completions/chat-completions) request to receive tokens as the model produces them, instead of waiting for the complete response. ## 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. - [Streaming responses from LLMs](https://vercel.com/kb/guide/streaming-from-llm?from=related) — Learn how to use the AI SDK to stream LLM responses. - [Streaming in web applications](https://vercel.com/kb/guide/what-is-streaming?from=related) — Learn how streaming works in web applications. Explore benefits, use cases, and implementation details with Vercel Funct - [Create Chat (Streaming)](https://v0.app/docs/api/v2/reference/chats/create-chat-streaming?from=related) — Creates a new chat with a user message and returns a Server-Sent Events stream. Events include initial chat state, title - [Streaming](https://chat-sdk.dev/docs/streaming?from=related) — Stream real-time text responses from AI models and other async sources to chat platforms. - [Streaming](https://vercel.com/docs/ai-gateway/sdks-and-apis/anthropic-messages-api/streaming?from=related) — Stream Anthropic Messages API responses token by token as they are generated. - [Stream Protocols](https://ai-sdk.dev/docs/ai-sdk-ui/stream-protocol?from=related) - [Streaming](https://vercel.com/docs/ai-gateway/sdks-and-apis/openresponses/streaming?from=related) — Stream responses token by token using the OpenResponses API. - [Streaming](https://vercel.com/docs/ai-gateway/sdks-and-apis/responses/streaming?from=related) — Stream tokens as they are generated with the OpenAI Responses API. - [Streaming](https://vercel.com/docs/functions/streaming-functions?from=related) — Learn how to stream responses from Vercel Functions. - [Structured Outputs](https://vercel.com/docs/ai-gateway/sdks-and-apis/openai-chat-completions/structured-outputs?from=related) — Generate structured JSON responses that conform to a specific schema using the Chat Completions API. Full cross-link map for this page: [/docs/ai-gateway/sdks-and-apis/openai-chat-completions/streaming.graph.md](/docs/ai-gateway/sdks-and-apis/openai-chat-completions/streaming.graph.md) Create a streaming chat completion that streams tokens as they are generated. #### cURL ```bash filename="stream.sh" curl -X POST "https://ai-gateway.vercel.sh/v1/chat/completions" \ -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "anthropic/claude-opus-5", "messages": [ { "role": "user", "content": "Write a one-sentence bedtime story about a unicorn." } ], "stream": true }' ``` #### TypeScript ```typescript filename="streaming-chat.ts" import OpenAI from 'openai'; const apiKey = process.env.AI_GATEWAY_API_KEY || process.env.VERCEL_OIDC_TOKEN; const openai = new OpenAI({ apiKey, baseURL: 'https://ai-gateway.vercel.sh/v1', }); const stream = await openai.chat.completions.create({ model: 'anthropic/claude-opus-5', messages: [ { role: 'user', content: 'Write a one-sentence bedtime story about a unicorn.', }, ], stream: true, }); for await (const chunk of stream) { const content = chunk.choices[0]?.delta?.content; if (content) { process.stdout.write(content); } } ``` #### Python ```python filename="streaming-chat.py" import os from openai import OpenAI api_key = os.getenv('AI_GATEWAY_API_KEY') or os.getenv('VERCEL_OIDC_TOKEN') client = OpenAI( api_key=api_key, base_url='https://ai-gateway.vercel.sh/v1' ) stream = client.chat.completions.create( model='anthropic/claude-opus-5', messages=[ { 'role': 'user', 'content': 'Write a one-sentence bedtime story about a unicorn.' } ], stream=True, ) for chunk in stream: content = chunk.choices[0].delta.content if content: print(content, end='', flush=True) ``` ## Streaming response format Streaming responses are sent as [Server-Sent Events (SSE)](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events), a web standard for real-time data streaming over HTTP. Each event contains a JSON object with the partial response data. The response format follows the OpenAI streaming specification: ```http data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1677652288,"model":"anthropic/claude-opus-5","choices":[{"index":0,"delta":{"content":"Once"},"finish_reason":null}]} data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1677652288,"model":"anthropic/claude-opus-5","choices":[{"index":0,"delta":{"content":" upon"},"finish_reason":null}]} data: [DONE] ``` **Key characteristics:** - Each line starts with `data:` followed by JSON - Content is delivered incrementally in the `delta.content` field - The stream ends with `data: [DONE]` - Empty lines separate events **SSE Parsing Libraries:** If you're building custom SSE parsing (instead of using the OpenAI SDK), these libraries can help: - **JavaScript/TypeScript**: [`eventsource-parser`](https://www.npmjs.com/package/eventsource-parser) - Robust SSE parsing with support for partial events - **Python**: [`httpx-sse`](https://pypi.org/project/httpx-sse/) - SSE support for HTTPX, or [`sseclient-py`](https://pypi.org/project/sseclient-py/) for requests For more details about the SSE specification, see the [W3C specification](https://html.spec.whatwg.org/multipage/server-sent-events.html). ## Next steps - [Tool calling](/docs/ai-gateway/sdks-and-apis/openai-chat-completions/tool-calling) - Stream a response that calls your functions - [Reasoning](/docs/ai-gateway/sdks-and-apis/openai-chat-completions/reasoning) - Control how much a model thinks before answering - [Advanced](/docs/ai-gateway/sdks-and-apis/openai-chat-completions/advanced) - Provider options and prompt caching --- [View full sitemap](/docs/sitemap)