REST API

Call AI Gateway Chat Completions with REST

If you prefer to use the AI Gateway API directly without the OpenAI client libraries, you can make HTTP requests using any HTTP client. Here are examples using TypeScript's fetch, Python's standard library, and cURL:

List models

list-models.ts

const response = await fetch('https://ai-gateway.vercel.sh/v1/models', {
  method: 'GET',
  headers: {
    Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
    'Content-Type': 'application/json',
  },
});
 
const models = await response.json();
console.log(models);

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/models',
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

list-models.sh

curl -X GET "https://ai-gateway.vercel.sh/v1/models" \
  -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \
  -H "Content-Type: application/json"

Basic chat completion

chat-completion.ts

const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-opus-5',
      messages: [
        {
          role: 'user',
          content: 'Write a one-sentence bedtime story about a unicorn.',
        },
      ],
      stream: false,
    }),
  },
);
 
const result = await response.json();
console.log(result);

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-opus-5', 'messages': [{'role': 'user', 'content': 'Write a one-sentence bedtime story about a unicorn.'}], 'stream': False}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

chat-completion.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": false
  }'

Streaming chat completion

streaming-chat.ts

const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-opus-5',
      messages: [
        {
          role: 'user',
          content: 'Write a one-sentence bedtime story about a unicorn.',
        },
      ],
      stream: true,
    }),
  },
);
 
if (!response.ok || !response.body) throw new Error(await response.text());
const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
 
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
 
  buffer += decoder.decode(value, { stream: true });
  const lines = buffer.split('\n');
  buffer = lines.pop() ?? '';
 
  for (const line of lines) {
    if (line.startsWith('data: ')) {
      const data = line.slice(6);
      if (data === '[DONE]') {
        console.log('Stream complete');
        break;
      } else if (data.trim()) {
        const parsed = JSON.parse(data);
        const content = parsed.choices?.[0]?.delta?.content;
        if (content) {
          process.stdout.write(content);
        }
      }
    }
  }
}

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-opus-5', 'messages': [{'role': 'user', 'content': 'Write a one-sentence bedtime story about a unicorn.'}], 'stream': True}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    for line in response:
        print(line.decode(), end="")

streaming-chat.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
  }' \
  --no-buffer

Image analysis

image-analysis.ts

import fs from 'node:fs';
 
// Read the image file as base64
const imageBuffer = fs.readFileSync('./image.png');
const imageBase64 = imageBuffer.toString('base64');
 
const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-opus-5',
      messages: [
        {
          role: 'user',
          content: [
            { type: 'text', text: 'Describe this image in detail.' },
            {
              type: 'image_url',
              image_url: {
                url: `data:image/png;base64,${imageBase64}`,
                detail: 'auto',
              },
            },
          ],
        },
      ],
      stream: false,
    }),
  },
);
 
const result = await response.json();
console.log(result);

request.py

import json
import os
import urllib.request
import base64
from pathlib import Path
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-opus-5', 'messages': [{'role': 'user', 'content': [{'type': 'text', 'text': 'Describe this image in detail.'}, {'type': 'image_url', 'image_url': {'url': "data:image/png;base64," + base64.b64encode(Path("image.png").read_bytes()).decode(), 'detail': 'auto'}}]}], 'stream': False}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

image-analysis.sh

# First, convert your image to base64
IMAGE_BASE64=$(base64 -i ./image.png)
 
curl -X POST "https://ai-gateway.vercel.sh/v1/chat/completions" \
  -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-opus-5",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Describe this image in detail."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "data:image/png;base64,'"$IMAGE_BASE64"'",
              "detail": "auto"
            }
          }
        ]
      }
    ],
    "stream": false
  }'

Tool calls

tool-calls.ts

const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-opus-5',
      messages: [
        {
          role: 'user',
          content: 'What is the weather like in San Francisco?',
        },
      ],
      tools: [
        {
          type: 'function',
          function: {
            name: 'get_weather',
            description: 'Get the current weather in a given location',
            parameters: {
              type: 'object',
              properties: {
                location: {
                  type: 'string',
                  description: 'The city and state, e.g. San Francisco, CA',
                },
                unit: {
                  type: 'string',
                  enum: ['celsius', 'fahrenheit'],
                  description: 'The unit for temperature',
                },
              },
              required: ['location'],
            },
          },
        },
      ],
      tool_choice: 'auto',
      stream: false,
    }),
  },
);
 
const result = await response.json();
console.log(result);

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-opus-5', 'messages': [{'role': 'user', 'content': 'What is the weather like in San Francisco?'}], 'tools': [{'type': 'function', 'function': {'name': 'get_weather', 'description': 'Get the current weather in a given location', 'parameters': {'type': 'object', 'properties': {'location': {'type': 'string', 'description': 'The city and state, e.g. San Francisco, CA'}, 'unit': {'type': 'string', 'enum': ['celsius', 'fahrenheit'], 'description': 'The unit for temperature'}}, 'required': ['location']}}}], 'tool_choice': 'auto', 'stream': False}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

tool-calls.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": "What is the weather like in San Francisco?"
      }
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "get_weather",
          "description": "Get the current weather in a given location",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {
                "type": "string",
                "description": "The city and state, e.g. San Francisco, CA"
              },
              "unit": {
                "type": "string",
                "enum": ["celsius", "fahrenheit"],
                "description": "The unit for temperature"
              }
            },
            "required": ["location"]
          }
        }
      }
    ],
    "tool_choice": "auto",
    "stream": false
  }'

Provider options

provider-options.ts

const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-opus-5',
      messages: [
        {
          role: 'user',
          content:
            'Tell me the history of the San Francisco Mission-style burrito in two paragraphs.',
        },
      ],
      stream: false,
      providerOptions: {
        gateway: {
          order: ['vertex', 'anthropic'], // Try Vertex AI first, then Anthropic
        },
      },
    }),
  },
);
 
const result = await response.json();
console.log(result);

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-opus-5', 'messages': [{'role': 'user', 'content': 'Tell me the history of the San Francisco Mission-style burrito in two paragraphs.'}], 'stream': False, 'providerOptions': {'gateway': {'order': ['vertex', 'anthropic']}}}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

provider-options.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": "Tell me the history of the San Francisco Mission-style burrito in two paragraphs."
      }
    ],
    "stream": false,
    "providerOptions": {
      "gateway": {
        "order": ["vertex", "anthropic"]
      }
    }
  }'

Provider sorting

Sort providers by cost, latency, or throughput using the provider shorthand or providerOptions.gateway.sort. Accepted values: cost, ttft, tps.

provider-sort.ts

const response = await fetch(
  'https://ai-gateway.vercel.sh/v1/chat/completions',
  {
    method: 'POST',
    headers: {
      Authorization: `Bearer ${process.env.AI_GATEWAY_API_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'anthropic/claude-sonnet-5',
      messages: [
        {
          role: 'user',
          content: 'What is 2 + 2? Answer in one sentence.',
        },
      ],
      stream: false,
      provider: {
        sort: 'tps', // Use the highest throughput provider first
      },
    }),
  },
);
 
const result = await response.json();
console.log(result);

request.py

import json
import os
import urllib.request
 
request = urllib.request.Request(
    'https://ai-gateway.vercel.sh/v1/chat/completions',
    data=json.dumps({'model': 'anthropic/claude-sonnet-5', 'messages': [{'role': 'user', 'content': 'What is 2 + 2? Answer in one sentence.'}], 'stream': False, 'provider': {'sort': 'tps'}}).encode(),
    headers={'Authorization': "Bearer " + os.environ["AI_GATEWAY_API_KEY"], 'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))

provider-sort.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-sonnet-5",
    "messages": [
      {
        "role": "user",
        "content": "What is 2 + 2? Answer in one sentence."
      }
    ],
    "stream": false,
    "provider": {
      "sort": "tps"
    }
  }'

Last updated September 8, 2026

Cross-link map: Call AI Gateway Chat Completions with REST (/docs/ai-gateway/sdks-and-apis/openai-chat-completions/rest-api)

From the Vercel docs graph (built 2026-10-05T05:39:47.698Z), spanning vercel.com docs + KB, nextjs.org, ai-sdk.dev, and other Vercel documentation sites. Full graph as JSON: https://vercel.com/docs/graph.json

Semantically closest pages

AI Gateway Provider Filtering, Ordering, and Sorting — Control AI Gateway provider routing with order, only, and sort. Set preferences, restrict providers, and rank them by co
AI Gateway Provider Routing and Fallbacks — Configure provider routing, ordering, and fallback behavior in Vercel AI Gateway.
Python with AI Gateway: OpenAI and Anthropic SDKs — Use AI Gateway with Python through OpenAI or Anthropic SDKs with full streaming, tool calling, and async support.
AI Gateway Models and Providers — Choose AI Gateway models and providers. Configure routing, fallbacks, timeouts, prompt caching, reasoning, and web searc
OpenAI Chat Completions Configuration with AI Gateway — Configure provider options, model fallbacks, BYOK credentials, and prompt caching through AI Gateway.

Prerequisites

AI Gateway — Vercel MCP tools for ai gateway.

Pages that link here (1)

By site: vercel-docs (1)

OpenAI Chat Completions API with AI Gateway — Use OpenAI SDKs with the AI Gateway Chat Completions API. Configure the base URL and authentication for chat, streaming,

Image Generation

Anthropic Messages API

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